How a brand can better identify the right influencer within the fashion industry in the US by Alessandro Bogliari

IT UNIVERSITY OF COPENHAGEN

SUBMISSION OF WRITTEN WORK Class code: Name of course: Digital Innovation & Management Course manager: Course e-portfolio: Thesis or project title:

How a brand can better identify the right influencer within the fashion industry in the US for its influencer marketing campaign

Supervisor: Hanne Westh Nicolajsen

Full Name: 1.

Alessandro Bogliari

Birthdate (dd/mm-yyyy): 18/05/1991

E-mail: albog

@itu.dk

How a brand can better identify the right influencer within the fashion industry in the US for its influencer marketing campaign Master’s Thesis, MSc in Digital Innovation & Management Alessandro Bogliari Thesis supervisor: Hanne Westh Nicolajsen

Submission date: 2nd April 2017 Digital Innovation & Management, IT University of Copenhagen, Copenhagen, Denmark

Abstract The purpose of this thesis is to investigate how brands can better identify influencers on Instagram for their influencer marketing campaigns. For instance, this thesis analyzes the actual state of influencer marketing, its main issues and challenges through a quantitative survey to influencer marketing agencies and platforms and two qualitative interviews to experts. Moreover, this thesis presents quantitative findings about micro and macro-influencers within the fashion industry in the United States market, focusing especially on concepts such as engagement rate and price per promoted post. The application of mixed method approach, that included both qualitative and quantitative methods, provided me a wider overview of the data and a holistic understanding of the topic. In addition, the data scraping methodology has been used in order to automate the process of data gathering and a tool has been coded in JavaScript to display the information obtained. Finally, using the data gathered and the information obtained from experts, a guideline for brands was outlined. This guideline, which is the ultimate goal of this thesis, presents steps to follow in order to better identify influencers on Instagram within the fashion industry. Keywords: influencer marketing, influencer, influencers, micro-influencer, macro-influencer, Instagrammer, Instagrammers, influencer marketing guidelines, influencer marketing budgeting

Table of content Abstract

1.0 Introduction

1.1 What is Influencer Marketing

1.2 Who is an influencer

1.3 The growth of Influencer Marketing

2.0 Problem Area 2.1 Problem formulation 2.1.1 Research questions 3.0 Practical State of Influencer Marketing 3.1 Influencer Marketing Players – Influencers, Agencies and Platforms

9 10 11 12 13

3.1.1 Types of Influencers

3.1.2 Influencer Marketing Platform and Agencies

3.2 Influencer Marketing Channels

3.3 Engagement, impressions and reach

4.0 Methodology 4.1 Philosophy of Science

21 21

4.1.1 Ontology

4.1.2 Epistemology

4.2 Abduction

4.3 Literature review methodology

4.4 Data collection

4.5 Mixed methods approach

4.6 Qualitative research

4.6.1 Interviews

4.7 Quantitative research

4.7.1 Survey

4.7.2 Data scraping

4.8 Data analysis

4.9 Reliability and validity

4.9.1 Reliability

4.9.2 Validity

4.10 Limitations and Delimitations 4.10.1 Limitations

40 40

4.10.2 Delimitation

5.0 Literature review

6.0 Theories

6.1 Consumer buying process

6.2 Buying behaviour model

6.3 Combination of the theories - Creation of the operational model

7.0 Analysis

7.1 Survey results

7.2 Survey key findings

7.3 Interview results

7.4 Interviews key findings

7.5 Combining survey and interviews key findings and answering the first research question

7.6 Data scraper creation

7.6.1 Scraper code

7.7 Data scraping results

7.8 Data scraping key findings

7.9 Pay Per Promoted Post (PPPP) Formula Creation

7.10 Combination of PPPP Formula with Data Scraper Results and answer to the second research question

8.0 Discussion

9.0 Conclusion

10.0 Legal issues and ethical questions

11.0 Future perspectives

12.0 Bibliography

13.0 Sitography

Appendices

1.0 Introduction 1.1 What is Influencer Marketing Influencer marketing is a new practice within the digital marketing field that practitioners seem to use more and more. For instance, looking at the Google Trends for this term (Figure 1), it is easy to see a huge rise worldwide in the last 5 years. Figure 1: Interest over time on the term “Influencer Marketing” – Source: Google.com/trends

Influencer Marketing is a new approach to marketing that “directly addresses the most common sales barriers within prospective customers and focuses attention on those individuals who advise decision-makers” (Brown & Hayes, 2008, p. 12). In order to understand in practical terms what is this growing trend, a concrete example of an influencer marketing campaign was made by the brand Birchbox. This beauty company teamed up with Emily Schuman, a lifestyle blogger with more than 260,000 Instagram followers and she promoted Birchbox’s products posting five photos on Instagram, which received 18,000 likes and reached half a million of consumers (Furgison, 2016). Another interesting case study to mention is the product placement campaign of Lokai1, a company that produces wearables: during the Coachella festival – a festival that according to Digiday (Biron,

h ttps://www.instagram.com/livelokai/

2016) in 2015 had 200,000 attendees between the ages of 18–24 years old - Lokai made partnerships with different influencers on Instagram: one of those was the instagrammer Helenowen2 that published a single photo promoting Lokai products and receiving 36,600 likes. In total, “Live Lokai’s campaign reached over 40 million people, earned 2.2 million likes, and received 14,000 comments” stated Mediakix (2016). In other words, Influencer Marketing is a form of marketing in which brands and influencers collaborate to achieve a win-win result through a working partnership: brands win in terms of brand awareness, engagement which can turn into increasing sales, while influencers win in increasing their fan base and getting money for their service.

1.2 Who is an influencer We can define an influencer as “an individual with an online presence who has the potential to influence the opinions and behaviors” of his/her target audience, as stated on NeoReach by Talavera (2016), an influencer marketing platform. Influencers, unlike celebrities, can be anyone within any industry with an “audience” and a communication channel that allows him/her to speak his/her mind. Influencers are people always connected to consumer groups, community tribes and industry associations (Dizon, 2015). As outlined before with a couple of examples, influencers can help brands by affecting their followers and persuading them in their decision making process. A case study conducted by Defy Media – an American digital media agency that produces online content for 12-34 years old viewers – stated that 62% of 18-24 years old of the people interviewed would try – at least once – a product or brand recommended by a YouTuber (Defy Media, 2016).

h ttps://www.instagram.com/helenowen/

1.3 The growth of Influencer Marketing For the purposes and relevance of this thesis, it is important to stress the reason why Influencer Marketing is growing so much and the reason why a lot of brands are so interested in it. One of the major reasons is that “74% of consumers rely on social media to influence their purchasing decisions” (Bennett, 2014 in Woods, 2016, p.5) and also that, according to Nielsen, “92% of consumers believe recommendations from friends and family over all forms of advertising” (Whitler, 2014). Moreover the concept of trust between companies and consumers is changing: for instance, 88% of the consumers interviewed by BrightLocal (2014) on a Local Consumer Review Survey stated that they trust online reviews as much as personal suggestions and recommendations and this accentuate the soaring level of influence that influencers can have on their audience. In fact, from the same report it turns out that 72% of the same consumers interviewed will take some actions after reading a positive review of a product or service, as we can see in the graph below (Figure 2). Figure 2: How do online customer reviews affect your opinion of a local business? Source: BrightLocal (2014)

Moreover, if we take into accounts these information and we look at the data of one of the social media channels, Instagram, it is understandable why there is a lot of interest from brands in

investing in it: “There are more than 400 million monthly active users on Instagram, 3.5 billion likes daily and more than 80 million photos posted a day” (Instagram, 2016). Therefore, since customers trust a business that has a positive review from another customer and Instagram is a social network with million of monthly active users, brands are seizing this opportunity because of its business potential. But Instagram is not the only social media channel where brands are currently investing on. To mention another example, companies are present also on Snapchat: the adoption of this social media channel by brands grew by 50% between January and October 2016, as reported by Marketing Dive (Kirkpatrick, 2017) - an online magazine that provides news and analysis for marketing executives, covering topics such as social media marketing, marketing data and analytics. To mention another channel, an interesting fact provided by Google (O’Neil-Hart & Blumenstein, 2016) is that 70% of teenage YouTube subscribers (13-19 years old) say they relate to YouTubers more than traditional celebrities and this is mostly because of two reasons: the first one is that television has less effect and impact on Generation Z (Ibid.) – also known as Post-Millennials, are the people born in the range from the mid-1990s to early 2000s (Strauss & Howe, 1991) – , the second reason is that teenagers see VIPs and celebrities as people too distant from their habits and daily life, while they find their favourites YouTubers more similar to them and they perceive Youtubers as they would be like friends (O’Neil-Hart & Blumenstein, 2016). For instance, while the more traditional tv channel is less watched by the new generations (MarketingCharts, 2017), young people watch a lot of online videos: Facebook, in 2016, announced that 100-million hours of video were watched on a daily basis (Wagner, 2016) and Snapchat, during the same year, hit 10-billion video views each day (Frier, 2016). Also YouTube, the social media for video, in the early 2017 can count 1,300,000,000 users, with 300 hours of video uploaded every minute (Donchev, 2017). “6 out of 10 people prefer online video platforms to live TV”, states Google (O’Neil-Hart & Blumenstein, 2016). All in all, young people are moving from traditional channels to social media ones which are showing an increasing growth rate every year in terms of active users and brands are seizing this opportunity entering more and more within these channels pursuing new business techniques in order to keep up with this new trend, continuing to make

profits and not become outdated. This means that the prevalence of online videos can shape the future of the influencer marketing and the marketing itself. Another factor that is bringing brands to invest in influencer marketing is that “social media changes the relationship between companies and customers from master and servant, to peer to peer” as Jay Baer an American marketing consultant, speaker, and the author of the New York Times bestselling book, Youtility – stated on Convince & Convert (Baer, 2010), an award-winning magazine about digital marketing. This quote means that social media allowed the creation of a new type of relationship between brands and their customers from a traditional way of advertising, in which a company is used to have a unilateral communication (if we think for example of an advertisement on tv where the customers cannot leave any kind of feedback but only watch it) to a new bilateral type of communication where brands advertise (for example through a promoted post on Facebook from the official brand fan page) and customers can promptly express their feedbacks and point of view. Moreover a report written by Fashion and Beauty Monitor & Econsultancy (2016) called The Rise Of Influencers shows interesting facts and statistics collected from a survey sent to 348 practitioners. One of the most important key insights of this report is that the context is crucial: in fact, 72% of respondents say that “relevancy in relation to subject area is more important than influencer reach. By contrast, just 30% think it’s more important to have an influencer with reach, than one who relates specifically to the nature of the brand or campaign” (Ibid, p. 4). In the same report (Ibid.) Anna-Marie Solowij, founder of BeautyMART – an online beauty retailer – states that credibility is decisive and remarks how much is important that influencers not only have a lot of followers but know what they are talking about, giving real value to their fans. Another interesting statistic is that 57% of the respondents already have an influencer marketing strategy in place and 21% do not have one yet but is planning to have it over the next 12 months. This data provides us an overview of the high interest around the influencer marketing topic and its future possibile growth in the next years. On the one hand, although there is interest in influencer marketing, one of the biggest problem that emerges from the survey is that brands have difficulty in identifying the right influencers that are a good fit for them and that this turns out to be complicated

and time consuming. This insight relates perfectly to this thesis’ problem area and the aim of this thesis is to investigate how brands can better find the right influencer for an online influencer marketing campaign.

All in all, based on the information provided above, the way companies and brands communicate to consumers and advertise their products is changing. Television and traditional advertising techniques are not effective anymore and the rise of influencer marketing and social media channels is shaping a new way of advertising a product to consumers in a less aggressive and more targeted way.

2.0 Problem Area “We have no idea what to pay them. That’s the problem.” confessed a social media executive, answering to a question regarding how brands decide how much pay an influencer (Pathak, 2016). Moreover, “It’s hard to track the effect that influencers have on a brand’s sales, and the cost of employing influencers has risen drastically in recent years” highlights Willett (2016) regarding the relationship between brands and influencers. These mentioned above are only two examples of the challenges and uncertainties of practitioners towards influencer marketing that has raised in the last 2 years. Reading these interviews it emerges that unfortunately there are many more challenges, such as low control on pricing, pre-negotiated contracts, the lack of rules and regulamentation or at least guidelines on influencer marketing. Indeed, Influencer Marketing, although is a growing and appealing advertising practice, still needs to be considered as a new trend in the Marketing world and, as such, it is missing not only an academic background but also guidelines for all the players involved in the field. Based on these preliminary information, If we suppose that a brand wants to find the right influencer for its influencer marketing campaign, we can argue that it will not achieve this goal too easily and it will have to face many unknown factors. One example of preliminary challenge could be even identify the potential influencer: for instance, currently the influencer marketing platforms that support companies and brands in the research – and that I will explain in the next chapters in detail – provide only data on the influencers without any explanation to brands of which of the many influencers they should choose. Practically speaking,

this type of data includes, if we take in consideration the social media channel Instagram, the number of followers, the number of photos published, geolocation and influencer’s main topic. Giving only numerical data to brands interested in finding an influencer without any useful insights cannot help too much in terms of influencer identification, especially under a budgeting point of view, a crucial factor for a company. In fact, having merely the number of followers of an influencer is not enough to understand if she/he is the right one for the brand’s influencer marketing campaign, as I will stress throughout this thesis, because data have to be combined and processed together in order to give insights and useful information for the brand. Another critical factor in any marketing campaign, not only in an influencer one, is to define the correct amount of budget to allocate (Piercy, 1986). For instance, decisions around marketing budget are crucial for a business and should be based on facts and data rather than intuitions (Fisher et al., 2012). But, as stated previously, brands at the moment do not know how to allocate money for influencer marketing, since they are budgeting more on intuitions and guessing than on a data-driven perspective. A poor budgeting approach can sometimes totally ruin a business or at least can negatively affect it in terms of revenues and growth (Ryckman, 2011). For example, at the moment there are not tools that calculate how much a brand should pay a specific influencer per promoted post, an important insight that can help the brand in better manage the yearly budget of the marketing department. Said so, since marketing budgeting is a crucial process for brands and momentarily companies are not approaching it correctly regarding influencer marketing campaigns, it is fundamental to make a structure of it, creating a formula and a tool that can help brands in better understanding a fair price to pay influencers and organize the yearly budget for influencer marketing on a data-driven approach instead of a hypothesis-driven way.

2.1 Problem formulation

Based on the lack of knowledge that companies have towards the influencer field, as stated in the problem area section, this thesis aims to analyze which are the most important factors that a brand has to take into consideration before creating an influencer marketing campaign and also create a tool, based on a formula, that will suggest the Instagrammers’ price per promoted post that brands

should pay for. Moreover, the ultimate goal of this thesis will be to create a guideline that will guide brands in this process, optimizing the way of how to choose the right influencer for a successful digital promotion activity. Based on the information provided in the problem area chapter and at the beginning of the problem formulation one, I defined the following main question: How can a brand better identify the right influencer within the fashion industry in the US for its influencer marketing campaign? In other words the final aim of this thesis will be firstly to highlight the current challenges that brands are facing within influencer marketing field, and secondly to provide them some specific guidelines that will help them for their next influencer marketing campaigns.

2.1.1 Research questions In order to be able to fully answer the main problem formulation of this thesis, I decided to create two main sub-questions: 1) Which are currently the main challenges that brands face when looking for the right influencer? 2) How can brands measure the monetary value of a promoted post done by an US Instagrammer within the fashion industry? The first sub-question, that will be answered through both a quantitative survey and qualitative interviews done to influencer marketing practitioners, will help me in understanding the actual state of influencer marketing, which are the biggest challenges that brands are facing, especially during the research of influencers for a new influencer marketing campaign and how these challenges could be solved.

For what concerns the second sub-question, which aims to understand how can brands measure the monetary value of a promoted post done by an Instagrammer within the fashion industry, I decided to personally scrape and gather data instead of only using data collected from others and published on the Internet. Collecting my own data, I will be able to calculate an average engagement rate on Instagram, taking in consideration only the fashion industry in the US. Knowing the average engagement rate within a certain industry and a specific country, can help brands in having an overview of this important factor during the process of searching and selecting the right influencer. Moreover, I will use the average engagement rate as a variable in a formula I will create that will help brands in calculating the monetary value for a promoted post by an US Instagrammer within the fashion industry. In this way, brands can have a factor to take in consideration during the influencer research in terms of budgeting. All in all, these two sub-questions can help me in better identify the current challenges in the field and better understand the right commercial agreement that should happen between brands and influencers, filling the gap of knowledge that, as previously mentioned in the problem area, currently companies have. Moreover, based on the analysis of these information, the final aim of this thesis will be to help brands in better identify the right influencer for their influencer marketing campaign on Instagram, providing some common rules and general guidelines that brands can take in consideration when looking at which influencer to use for a campaign.

3.0 Practical State of Influencer Marketing This chapter is meant to introduce and investigate deeper the actual practices in the influencer marketing field. For instance, since this topic is new and not fully investigated yet, it is important to define some key concepts and therefore enable the reader to understand them.

3.1 Influencer Marketing Players – Influencers, Agencies and Platforms After reading several articles about influencer marketing, the first notion to mention is that in the Influencer Marketing field there are mostly four players: influencer marketing agencies, influencer

marketing platforms, influencers and brands. These players, that I will present in the next chapters, can use different channels and platforms to connect and promote products.

3.1.1 Types of Influencers

A fundamental point to mention is the distinction between macro-influencers and micro-influencers: the first ones can be defined as “influencers who have a significant but not massive following as compared to top influencers and celebrities. They aren’t your traditional celebrities but individuals who are considered to be experts in their relevant niche” (Barker, 2016) and these niches can be, for example, food blogging, fitness Instagrammer, mommy and travel bloggers. They usually have between 10,000 and 150,000 followers on Instagram (Boyd, 2016) and their average engagement rate is 2.4% (Smith, 2016). Is important to highlight that this average engagement rate just cited does not take in consideration any difference between countries or type of industry. The engagement rate is a concept that I will define and explain in the Engagement, Impressions and Reach chapter. It is the result of the sum of the engagement (likes + comments) divided by the number of followers. The average “engagement rate”, instead, is calculated on a selection of influencers (Influencer A has 3%, Influencer B has 5%, Influencers C has 2.4% and so on) and then all the engagement rate percentages are summed up and divided by the total number of influencers taken in consideration. In order to understand the concept I have created a table (Figure 3) that shows an example: Figure 3: 6 different influencers with their own engagement rate

Influencer A

Influencer B

Influencer C

Influencer D

Influencer E

Influencer F

2.4%

1.3%

0.7%

The average engagement rate will be: 3 + 5 + 2.4 + 1.3 + 0.7 + 7 6

= 2.77%

That being said, if a brand knows the average engagement rate of influencers in a certain country and a specific market, it can use it as a factor that has to be taken in consideration during the search

of influencers for an influencer marketing campaign. If we suppose that the average engagement rate of micro-influencers (10,000 - 150,000 followers) in the fashion industry in the US is 5% (this is only hypothetical, I will later calculate the real average engagement rate), brands will mostly take in consideration influencers that have an engagement rate around 5% and will possibly not start relationships with influencers with less than that specific engagement rate percentage to get the best from the marketing investment. On the other hand, instead, there are the macro-influencers have between 500,000 and 1,000,000 or more of subscribers or followers (Mathews, 2016); having more followers doesn’t mean directly get more engagement: on the contrary, the average engagement rate for macro-influencers is 1.75% (Adams, 2016). Also this average engagement rate, as already stated for the micro-influencers one, is generic and does not take in consideration any difference between types of industry nor countries. All the information cited are summarized in the Figure 4 below. Figure 4: Type of influencers (metrics based on Instagrammers)

Type of influencer

N. of followers

Average engagement rate

Micro-influencer

1,000 - 150,000

2.4%

Medium-influencer

150,000 - 500,000

No data available online

Macro-influencer

500,000 - ≈ 1,000,000

1.75%

Celebrities

1,000,000+

No data available online

Macro-influencers and micro-influencers are not the only type of influencers on social media. Since there are different promotional channels, there are also different types of influencers. It is vital that brands comprehend the distinction between influencers, from the small ones (micro-influencers) to the celebrities. Marketing departments should understand that a big number of followers does not directly mean a successful influencer marketing campaign. In fact, what is also important, as previously stated, is the engagement rate of the influencer, a factor that has to be calculated on a specific influencer and then compared to the average engagement rate of other influencers within the same industry and geolocation. This has to be done because it is important for a brand to find influencers with an average or more than average engagement rate (compared to other influencers in

the same field and geolocation) in order to get a positive return on investment or at least more interest in the promoted product. In fact, if a user engages with a promoted content of an influencer means that he or her is interested in it and this action would possibly bring to a purchasing of the product promoted. Instead, a low engagement rate on an Instagram photo could mean that the followers are not interested in the promoted content and possibly would not be interested nor buy the product. All in all, it is important to stress that if a brand knows the engagement rate of an influencer, it can be used as a key factor during the influencer research and selection. In other words, this division and explanation of different types of influencers is important for brands when they are looking for the right influencer before start a marketing campaign for two reasons. First of all, to know if that person is the right one that can spread the message of the brand (such as a promotion or sponsored content) and, secondly, how the brand can adapt its message with the influencer’s contents and style. Context is important and have to be taken in consideration when a brand is looking for an influencer. In fact, suppose that an influencer – a professional videogamer, for example – one day shows to his/her followers a content that promotes a perfume: this would appear not aligned with the existing Instagrammer’s contents and would affect not only the engagement rate of the influencer but also his/her credibility to the followers, since trust, as stated previously, is an important factor in influencer marketing. Not only the content but also the style is fundamental: if an Instagrammer is used to publish only black & white photos and his/her followers like them because of that color choice, if suddenly the influencer publishes a colorful promoted content in collaboration with a brand, the followers could find that choice too staged and not spontaneous and stop following the influencer.

3.1.2 Influencer Marketing Platform and Agencies Currently, there are influencer marketing agencies that connect influencers and brands. For example, IMAgency, an influencer marketing agency, operates as a middle-person between brand and influencer and offers to brands also specific expertises like brand activation (that includes activities such as community contests, in-store events and fashion weeks), brand ambassador management (which means educate the influencers in better communicate the brand’s message), but also content creation and influencer marketing strategy. This means that agencies not only connect influencers

and brands, but also offer services in terms of creativity and marketing analysis. By offering creativity advices and ideas, agencies can help both the brand and the influencer in creating a more effective marketing campaign, analyzing the latest market trends and the best ways to, for example, shoot a picture or edit a video. Agencies can also support the creation of the advertisement’s concept, setting up the content, the wording and the style of a picture, blog post or video, in order to better match the brand identity and influencer style, giving to the promoted post a more realistic approach and thus avoiding a too staged advertisement that is usually not liked by the followers and customers. But these agencies are not the only player in the influencer market. Influencer marketing platforms, which are SaaS (Software as a Service) – which means that they are web application with a monthly fee payment for the usage (Rouse, 2016) – provide specific tools in order to find the best influencers by category, location, hashtags, keywords, number of followers and other factors. Hypr, for example, is an influencer marketing platform that has a big database of influencers profiles across the most important social media channels and gives the opportunity to any brand to access its database and filter the influencers depending on the brand target and influencer marketing campaign’s goals. Explaining in a practical way how these platforms are currently used, it is important to remember that brands main goals are focused on increasing their sales, brand awareness and their paid reach. In order to do so, they pay agencies to get in contact with influencers in their field and start a partnership. Influencer marketing agencies use influencer marketing platforms in order to filter and find the right influencers on the social media channels and get them under their wing. But brands can also find influencers by themselves without using any platforms or paying any agencies. This is a business choice by the company depending on management decisions and on the yearly marketing budget. All these process and relationships are graphically explained in the Figure 5 below I created.

Figure 5: the relationship between Influencer Marketing Agencies, Platforms, Influencers and Brands.

3.2 Influencer Marketing Channels Influencers can decide to use different social media channels based on their expertise and industry. For example, if we take into consideration the fashion and beauty industries, Instagram is the most influential social platform where influencers can promote brand products (Desreumaux, 2015). Econsultancy, a global team of experts that offers to companies services like marketing strategy and planning – in association with Fashion and Beauty Monitor – made a report called Voice of the Influencer (Gilliland, 2016) in which outlines the social media channels where influencers focus their communication and what is the reason behind it. From the report shown in the Figure 6 below, it is possible to see the different channels ranked from highest to lowest exposure in terms of influence: Instagram (74%), Twitter (51%), Blog (45%), Facebook (25%), Snapchat (17%), YouTube (16%), Pinterest (13%), Tumblr (4%).

Figure 6: What platform are influencers most influential on? Source: Gilliland (2016

3.3 Engagement, impressions and reach If we investigate deeper the topic of online advertising, a poll taken by Infolinks – an advertising platform that offers ad solutions for both publishers and advertisers – shows that 50% of internet users never clicked an online advertisement (such as banner or video ads before a YouTube content) while 35% of internet users clicked on it less than 5 ads in a month (Adotas, 2013). If we relate these information to online advertising metrics, it is important to remember what Kristy Sammis, co-founder of CLEVER – an influencer marketing agency and TEDx speaker – stated during an episode of the podcast Half Our Intern in March 2016: “Engagement is the new impressions. It matters as much, if not more, than someone’s reach” (Blake, 2016). In order to understand this sentence, it is important to define all the three concepts cited in it: engagement, impressions and reach. “Impression” is a term used in online advertising when advertisers “paid flat fees to show their ads a fixed number of times – typically, 1,000 showings or impression” (Edelman et al., 2005, p. 245); to make it clear, if an advertiser allocates $ 50.00 in online advertising on an impression-based campaign that cost $ 1.00 every 1,000 impressions, the advertiser will be able to show an adv, for example a banner, 50,000 times. This type of advertising doesn’t take in consideration the number of clicks but only the number of impressions, which means how many

times the advertisement has been shown to the users. The same person could see the same advertisement more than one time and this means that, for example, 50,000 impressions would not necessarily mean that 50,000 different people that the advertisement. To continue with this example, if we suppose that an advertiser allocates $ 50.00 on a $1 CPM (Cost Per Mille Impressions) online campaign where a customer sees the advertisement twice, the impressions will be 50,000 ( 1 : 1,000 = 50 : 50,000 ) but the people that actually saw the advertisement will be 25,000 (50,000 / 2). Instead, the term reach is “the number of unique people who received impressions of a page post, which means that If the same person sees the same content two different times, the reach would remain at one.” (Nadeau, 2015). This means that the reach of the same advertising campaign previously used as an example will be 25,000 people. To better explain the concepts I created a table (Figure 7) that shows a couple of examples. Figure 7: 2 examples to show the difference between impressions and reach Budget

CPM (Cost Per Mille)

Frequency (how many times the adv is seen by the same person)

Impressions

Reach

$ 50,00

$ 1.00

50,000

25,000

$ 120,00

$ 3.00

40,000

The last term, “engagement” is “when someone cares and interacts” (Sterne, 2010, p.106) with a product, a brand or a person. Online engagement is when someone interacts doing certain actions, for example commenting on a blog or subscribing to its rss feed, replying to a tweet of another user on Twitter, leaving a review on a product on Amazon or liking a picture on Instagram. These are just few examples of online engagement shown on the “Relevant metrics for social media applications organized by key social media objectives table” on MIT Sloan Management Review (Hoffman & Fodor, 2010). If we take in consideration the social media Instagram, engagement can be defined as the sum of likes and comments on a photo, because these are the only engagement actions that an user can do on this specific social media. Once calculated the engagement, it is possible to calculate the engagement rate, an important factor that brands should take in

consideration when they plan an online marketing campaign and that I have already mentioned in chapter 3.1.1. Brands should think about the engagement rate because is a number, expressed as percentage, that can be used as a factor to understand if the contents (pictures, videos, status) of a certain influencer are interesting to his/her followers or not. An influencer with a high number of followers but a low engagement rate could bring less interest to the brand product and few sales compared to an influencer with less followers but an higher engagement rate. To show the concept in practice, the engagement rate formula (Batum & Ersoy, 2016) can be written as: (

T otal number of engagement to a single post ) number of f ans

100

In my case, since I focus on Instagram, the Engagement Rate formula has to take in consideration also the number of photos of an user. Instead of using all the photos of an Instagrammer, based on my previous experience on this topic I suggest to choose a number between 10 and 30. I decided to define also the number of photos to get the same snapshot among influencers. In fact, if I analyze for two times the engagement rate of the same Instagrammer taking in consideration the first time 10 photos and the second time 1000 photos, the engagement percentage would be different and the same would be if I calculate it among different influencers. For this reason, since I will use the engagement rate formula to gather the average engagement rate within fashion Instagrammer in the U.S. I decided to insert also the number of photos as a variable to use in the formula. After adding the number of photos variable, the formula can be written as:

(

T otal number of likes + total number of comments) N umber of photos

number of f ollowers

) 100

To make this clear to the reader, I will provide a practical example. I took my Instagram account summing up the engagement of my last three photos – I started only with three instead of ten to see how much time it would have required to finish the task – and this is the calculation:

(

1319 + 55 ) 3

5364

) 100 = 8.53%

1,319 is the sum of the total number of likes I received on my last three Instagram photos; while 55 is the sum of all the comments I got on the last three pictures. 5,346 is the number of my total followers. Using the formula, it is easy to see that my Instagram Engagement Rate is 8.53% and this information can be used as a factor during the process of influencer research and selection. In fact, if an Instagrammer has a lot of followers, for example 100,000 but only 0.5% of Engagement Rate, is plausible that his or her followers are not really interested in what she/he is publishing and a brand could not get enough return on investment or interest on the product it wants to promote on the influencer’s account.

4.0 Methodology The purpose of this chapter is to present considerations in terms of methodology regarding the modality and techniques used for data collection during the research process. Moreover, also the choice of philosophy of science will be introduced. Regarding the data collection, both qualitative and quantitative approaches have been applied in order to present a deeper and more complete overview of the problem researched. I will also state the reason why I chose a mixed methods approach, providing strengths and weaknesses of it, discussing its limitations and delimitations. Finally, this thesis reliability and validity will be also presented and discussed.

4.1 Philosophy of Science This section is meant to present an overview of the epistemological and ontological philosophies in order to understand how knowledge was sought in this thesis. Moreover, this section of the thesis is meant to define which philosophical approaches have been used, in particular the positivistic one and the interpretivism one, and it will argue why these chosen methods are applied throughout the all data collection process and methodological stances. For what concerns the relationship between

ontology and epistemology, Hay (2006) states that “ontology logically precedes epistemology ... we cannot know what we are capable of knowing (epistemology) until such time as we have settled on (a set of assumptions about) the nature of the context in which that knowledge must be acquired (ontology)” (p. 8). Said so, Philosophy of Science is important because it is responsible not only for checking specific scientific methodologies, but also to support them. In short, “it makes us think about what we are doing and why” (Machamer, 1998, p.1).

4.1.1 Ontology “Objectivist ontology sees social phenomena and their meanings as existing independently of social actions, whereas constructivist ontology infers that social phenomena are produced through social interaction and are therefore in a constant state of revision” (Bryman and Bell, 2003, p.19). Another ontological question that Bryman brings to attention is to understand if social entities can be viewed as objective ones, having reality to social actors (objectivism) or if they can be considered “social constructions built up from the perceptions and actions of social factors” (ibid). If we take in consideration the positivistic paradigm of ontology, positivists consider the researcher and the object (the phenomena to investigate) as two distinctive things, while interpretivists believe that reality and the observer cannot be separated. I personally believe that the world in general has both subjective and objective characteristics, and therefore my thesis reflects both the positivistic and the interpretivist ontology.

4.1.2 Epistemology Epistemology takes into consideration a perception of the world and phenomena around us. It clearly states what can be considered as an acceptable knowledge within a particular discipline, concerning the questions regarding availability and obtainability of the knowledge (Bryman, 2008, p. 13). Again there are two main distinctions: firstly, positivistic approach claims that it is possible to acquire knowledge about the world unmediated and with no interferences. Secondly, observation within interpretative approach is never objective but always affected by the social constructions of reality.

If we start defining what positivism is, the positivist philosophy of science believes that the world is external (Carson et al., 1988) and that “there is a single objective reality to any research phenomenon or situation regardless of the researcher’s perspective or belief” (Hudson and Ozanne, 1988). Moreover, in positivism studies, “the role of the researcher is limited to data collection and interpretation through objective approach and the research findings are usually observable and quantifiable” (Dudovskiy, 2012). Usually, in a positivistic study, the data collection and the preferred research methods are on a quantitative nature, such as surveys, questionnaires or official statistics (Ibid.). The reason behind the choice of using quantitative methods is that in this way the researcher can seek more objective and detached results to the phenomenon he or she is investigating. Relating these statements to my thesis, I can argue that the positivistic approach has been used and followed: for instance, starting from the decision of which data collection method to use, for this thesis the gathering of primary data was done through a survey and quantitative method such as data scraping. Other two key fundamental concepts of the positivism, are that the research must progress through hypotheses and the main concepts need to be operationalized so that they can be measured (Ibid). Also both of these statements can relate and fit my thesis, since I am not only creating hypotheses on which challenges influencer marketing might face and the reasons why this practice is at risk, but also I am converting these concepts into metrics, a tool and a formula in order to have measurable results and conclusions. As a second epistemological consideration I applied the interpretivist approach which allows to ensure an adequate understanding and meaning by implying the idea of interpretation of the reality by every subject. Thus, multiple realities exist because of the different individual and group perspectives (Ibid.). In other words interpretivists recognize that the knowledge they build reflects their particular goals, culture, experience and history. I think interpretivism is a good choice of philosophy because I am involved in the topic of influencer marketing, since I am working within this field and also because the knowledge I am trying to create thanks to this thesis reflects my personal goals. Moreover, interpretive approaches rely heavily on naturalistic methods, such as

interviewing (Schutz, A., 1962). This can be related to my thesis, since the two semi-structured interviews I conducted relate to a more qualitative approach. The reason behind using also the qualitative approach and therefore combining quantitative and qualitative into a mixed method methodology, is that I wanted to gather as many information as possible on the influencer marketing topic, and the easier and more comprehensive way to do so, was by interviewing experts in the field and interpret their feedbacks and answers. All in all, I decided to use both positivism and interpretivism in my thesis since I believe that through positivistic approach I can establish one objective truth and present generalizations on the influencer marketing topic, but also that by using the interpretivist approach, I can interpret individual experiences and create a generalization based on the interpretation of personal experiences.

4.2 Abduction Abductive reasoning was introduced by Charles Sanders Peirce (Yu, 1994) to denote a type of non-deductive inference that was different from the already familiar inductive type (Ibid). Acquiring knowledge from abduction is a way of reasoning that focuses on the search of explanatory hypotheses. According to Peirce, abductive reasoning is the only logical operation which introduces any new idea (Hookway, 2016). Abduction is one of the three possible reasoning within a study: the other two options are induction and deduction. Again Pierce differentiates the three saying that “abduction is the firstness (existence, actuality); deduction, the secondness (possibility, potentiality); and induction, the thirdness (generality, continuity)” (Yu, 1994, p. 15). The distinction between induction and deduction becomes very problematic when it comes to the actual research process. Croswell claims that the process of moving between theory and data never operates in only one direction (Creswell et al., 2011). However, during the actual design, collection, and analysis of data it is impossible to operate in either an exclusively theory - or data-driven way (Ibid). Therefore, abductive reasoning seems highly relevant since it moves back and forth between induction and deduction: first converting observations into theories and then assessing those theories through action. This particular version of the abductive process is quite familiar to

researchers who combine qualitative and quantitative methods in sequential fashion (Ivankova et al., 2006; Morgan, 2007), where the inductive results from a qualitative approach can serve as inputs for the deductive goals of a quantitative approach, and vice versa. All the considerations and definitions mentioned above relate and confirm that abduction could be seen as the right reasoning for this thesis. For instance, I am moving back and forth between converting observations from influencer marketing experts into a tool and formula and then I am again assessing the value of this formula through an actual application of it. Moreover, the abductive reasoning accepts both quantitative and qualitative data collection methods which I am both applying.

4.3 Literature review methodology Even though Influencer Marketing can be seen as a new topic in the academic field, there are however interesting papers about it. In order to create new knowledge I had to be aware of the existing researches written by others and literature review is a crucial step in the process of understanding a certain topic, both for funding the basics in identification of weaknesses and also for enabling problematization on a specific domain (Green et al. 2006; Hart, 1998, Khoo et al, 2011 in Boell & Cecez-Kecmanovic, 2014). For this reason, I decided to follow the hermeneutic framework for the literature review process explained by Boell & Cecez-Kecmanovic (2014). This framework is the combination of two hermeneutic circles: the search and acquisition circle and the analysis and interpretation circle that are both connected in a mutual way. The search and acquisition circle is composed of seven phases in a loop: searching, sorting, selecting, acquiring, reading, identifying, refining (Ibid.) as visible in Figure 8.

Figure 8: a hermeneutic framework for the literature review process consisting of two major hermeneutic circles - Source: Boell & Cecez-Kecmanovic (2014, p. 264)

Following this framework, I started the searching phase with the aim of identifying relevant publications: I looked for keywords related to influencer marketing on online libraries, university libraries and databases of scholarly literature. First of all, in order to have an overview of the influencer marketing concept I started searching articles, papers and thesis on Google Scholar, an online database powered by Google that allows everyone to search for resources looking for keywords. After a first search with the term influencer marketing, I decided to limit the search to “influencer marketing” using the quotation marks: this means that instead of looking for both the keywords “influencer” and “marketing” in the text, the system returns only the resources that have the term “influencer” followed by “marketing” with the intent to get only the papers that focus on that specific topic. In fact, looking for influencer marketing without quotation marks returned me also more generic marketing topics I was not

interested in. Moreover, after a previous Google search on influencer marketing, I discovered that the same topic is also called “influence marketing”. Knowing this, I decided then to look for both the terms on Google Scholar and I used the search operators to do this. Search operators are search parameters used in search engines to narrow down the focus of a search (Rouse, 2014). In my case I used “AND”, “OR”, and “NOT”. The first search operator, if used, narrows down the research for resources that have inside a keyword A and also a keyword B and it is mandatory that the keywords B is present. The second one, “OR”, instead, tells to the search engine to look for keyword A or keyword B and returns all the results that have inside the text both of the keywords. The last term operator is “NOT” and is used to exclude a certain keyword. To make this clear, I present here an example of one of the first searches I did on Google Scholar: "influencer marketing" OR "influence marketing" AND "theoretical framework" that means I wanted to look for both the terms “influencer marketing” and “influence marketing” but both of them had also to include the term “theoretical framework” in their texts. Doing so, I was able to narrow my research from more than 3,000 results to 450 texts more related to my research. I also used the advanced search feature that is built into Google Scholar in order to look for certain keywords only in the title and in a specific date range. To look for a term present only in the title of the paper I firstly used the command “allintitle:” followed by the term I was interested in. An example can be “allintitle: influencer marketing” and Google Scholar returned me 34 results. Secondly I limited the date range of publication between 2010 and 2016 in order to get the most updated possible resources and I got 22 results. I used Google Scholar also because next to every results is shown the number of times that a paper has been cited from other people and this can give an additional signal of the most important reviews to take in consideration during the literature review. After a first search on Google Scholar, I did the same search also on Scopus, an abstract and citation database of scientific journals and books. Scopus is accessible only from certain IPs (Internet Protocol Address) and for this reason I had to connect my computer to the KU (København Universitet) Wifi in order to obtain an IP present on Scopus list and access to the database. Scopus allowed me to find more papers on the topic that I wasn’t able to find on Google Scholar. In order to narrow down my search, I did not used only logical operators, as I did on Google Scholar, but

also the so called field codes3 that help the user in better identify certain keywords within field of the documents. For example, I used TITLE-ABS-KEY(influencer marketing) that returns papers where the terms between brackets – in this example the keyword “influencer marketing” – appears in the title, keywords, or abstract. This type of advanced search helped me in getting more related documents than a basic search would have given me. After a first search on the digital libraries previously cited, I sorted the documents by number of citations, to identify the most important papers about the topic I was interested in and publication date, to have the most updated papers on the matter, since it is a new topic. I then started selecting which were the most important and related documents for me in order to start acquiring them. Sometimes I was able to download on my computer the pdf file directly from Google Scholar, other times I could not download them for copyright reasons but I was able to read them through online documents preview tools. When the digital library did not show any download buttons for a document, I searched it on Google looking for the name of the document in quotation marks and followed by “filetype:pdf” in order to find only PDF files and download them. I then moved to the next phase, that is the reading of the documents selected in order to identify the documents to use and also find new search terms and additional publications or authors and widen my knowledge about the field and its related topics. Finally, I refined the search using a search strategy in order to improve my research called citation pearl growing strategy. This strategy “uses characteristics of relevant articles as a starting point for searching other relevant articles. In addition to using citation analysis, this method uses keywords assigned to documents” (Boell & Cecez-Kecmanovic, 2014, p. 281).

4.4 Data collection In order to answer the problem formulation and the related research questions, both qualitative and quantitative research were applied for the data collection process of this thesis. In detail, a survey and two interviews have been used: the survey provided me a statistical acknowledgement around the influencer marketing main challenges from the brands and companies perspectives, while the 3

http://help.elsevier.com/app/answers/detail/a_id/2347/p/8150/session/L2F2LzEvdGltZS8xNDkwNTI4MzMwL3N pZC9BVUNqRnZlbg%3D%3D

semi-structured interviews delivered a qualitative overview of the main factors that brands analyze in the process of choosing the right influencer for a campaign and the challenges this practice currently has. Both survey and interviews will help me in answering the first and research questions and also the main problem formulation of this thesis.

4.5 Mixed methods approach This section aims to explain what the mixed methods approach is, its main benefits and how it will be applied in this thesis. For instance, as I will argue, I believe that the mixed method approach is the most applicable method to understand a combination of quantitative and qualitative data. Bryman (2006) described it as a research that integrates together qualitative and quantitative research within the same project. Also Creswell (2013) defined the mixed methods approach as a technique for collecting, analyzing and combining both quantitative and qualitative methods in a specific study to comprehend a research problem. The biggest benefit of this method is to remove any implicit weaknesses of both quantitative and qualitative methods. In my case, on the one hand quantitative research avoids the lacks of the qualitative approach, giving me not biased data, on the other hand qualitative research will allow me to analyze the problem formulation deeper and with more detail.

4.6 Qualitative research Qualitative research can be defined as any type of research that gives outcomes and findings not using any statistical procedures or other methods and techniques in terms of quantification (Corbin & Strauss, 2008). Bryman (2008) states that the core characteristic of this type of research is to acquire information in a free form with the scope of understanding, explaining and interpreting of empirical data. Indeed, qualitative research often provide answers to questions that start with “why” and “how”. The main benefit of using the qualitative research method is the detailed level of comprehension and understanding of the research problem analyzing and interpreting the collected data gained through

the qualitative research (Ibid, p. 367). Within the qualitative research technique in the sociological studies, the most common used methods are interviews (Creswell, 2008). Interviews have been categorized in many ways but the most common are: unstructured, semi-structured and structured interviews (Longhurst, 2003). In my thesis, I chose the semi-structured interview: these type of interviews are organized around a prearranged number of questions that can change during the interview when new questions emerge between the interviewee and the interviewer. In this thesis, the interviews will be conducted with two practitioners in the influencer marketing field in order to collect general information within this marketing area and also more specific insights on actual issues and challenges in the next months. The first expert interviewed works as a Marketing Strategist at WowCrazy, a crowdfunding fashion platform that in the last months created an influencer marketing forecast agency called Call The Tune, which helps brands in saving time and investing wisely their marketing budget allocated for influencer marketing campaigns. The second expert is the Founder of Influencer Marketing Hub, the leading industry resource for Micro-Influencers, brands, agencies and platform that every week publishes posts influencer marketing best practices. Both the interviews lasted approximately 35 minutes and I interviewed the first expert on Skype, since he is located in another country, while the second expert was interviewed in person. These qualitative data will be essential in supporting the conclusions, answering the first research sub-question in this thesis and contributing to my problem formulation answer.

4.6.1 Interviews An interview is a “conversation between people in which one person has the role of the researcher” (Arksey and Knight 1999, p. 2) and, as previously stated, it can be unstructured, semi-structured or structured. The reason why I chose to use semi-structured interviews is because it allows new ideas to come up during the interview between interviewer and interviewee: the interviewer should remain flexible during the interview process so that the order of the questions can change during the conversation and the content itself can develop on a different path and the interviewer can get more in-depth answers. (Ibid.)

The data collected through an interview is usually recorded and transcribed later in order to analyze the text from a qualitative point of view (Gill et al., 2008). Generally, when a researcher uses interviews as a methodology, the sample size is small because of the amount of data to collect and the time that it takes to schedule the interview, its duration, the transcription time and the analysis. The questions asked during the two interviews were: 1. Based on articles and forums online, Instagram seems to be the best channels for Influencer Marketing. Do you agree? If so, why? 2. Why macro-influencers have a lower engagement rate compared to micro-influencers? 3. How much is important the context in influencer marketing? 4. Which are the two biggest issues you think influencer marketing has at the moment? 5. Which are the two biggest challenges that influencer marketing will have in the next year? I asked the first question in order to understand if Instagram is the best social network for influencer marketing not only in terms of users numbers but also to have a qualitative explanation of the phenomenon and confirm my choice of focusing only on Instagram for this thesis; for instance, the purpose of this question was to validate the many reports cited in this thesis that confirm Instagram as one of the most used channels by influencers within the fashion industry. The second question can give me an overview of the reasons why micro-influencers and macro-influencers have different engagement rates, helping me in understanding the monetary value per promoted post. In fact, engagement rate and number of followers are factors to take in consideration when analyzing how much brands should pay an Instagrammer for a promoted post. The third question was meant to analyze not only numerical and quantitative factors but also to have insights on qualitative data such as the importance of context in a influencer marketing campaign that can be, for example, a product placement of a brand in an Instagrammer’s picture. Knowing if also context is important, can be used as another guideline factor for brands to take in consideration during the process of influencer identification, and, as I stated in the problem area, this is one of the most crucial factor to consider when looking for an influencer.

The last two questions are meant to understand the actual situation of brands and influencer marketing and how these experts see this practice’s development in the next future. In this way I will be able to narrow down the main issues practitioners within this field are facing and this will be taken into consideration when investigating what this thesis can add as valuable resource in order to solve those challenges.

4.7 Quantitative research The quantitative research design is described as “entailing the collection of numerical data and as exhibiting a view of the relationship between theory and research” (Bryman, Bell, 2007, p. 160). This type of research is very structured and follows very clear and systematic steps: as a first step, the researcher structures the problem area in order to investigate a phenomenon; this step is then followed by the data gathering to answer the problem area previously formed. Then, once the data collection is over, the researcher start analyzing the collected data in order to make conclusions in terms of statistical insights (Trochim, 2002). On the one hand, a benefit of this type of research is that it provides numbers to investigate. On the other hand, a disadvantage of this approach is that the researcher needs a relevant sample in order to have an outcome as more statistically solid and accurate as possible. I decided to use the quantitative research method in order to better understand the main actual situation from practitioners within influencer marketing field and which are their challenges for the next months. For this reason I created a survey that is addressed to influencer marketing platforms and agencies in order to gather information about actual challenges and predictions for the next 12 months around the future of influencer marketing.

4.7.1 Survey As previously mentioned, I decided to create a survey in order to gather quantitative data about the actual situation and challenges around influencer marketing from platforms and agencies in the influencer marketing industry. This approach allows me to collect data faster than interviewing people one by one, helping me answer – in addition to the interviews – my first research question. Regarding the survey, I decided to create the first two questions in a semi-closed format, because it “offers the subject a limited number of choices and the freedom to include additional information”

(Del Greco & Walop, 1987, p.584). Regarding question number 2, I decided to give the respondents the opportunity to mark two options, using a multiple choice format:; in this way, I believed I could get a more comprehensive overview of the main challenges they think influencer marketing players are facing. Instead for questions n.3, n.4 and n.5 of the survey I applied a close questions format that offers only a limited number of choices (Ibid). In order to create a survey for my quantitative research, I used TypeForm, a freemium platform that allows everyone to easily create an online questionnaire, styling it and sharing it via a customized url. The survey I created does not influence in any way the respondents, since no one can see the others’ answers and it is also comfortable towards the survey’s participants because they are able to complete the questionnaire at their own preferred time. This type of questionnaire strengthen privacy and decreases social concerns of the respondents that may have had if this survey was done in person. An online survey is also faster, low cost and there are proofs that web questionnaires are completed with less unanswered questions than non-online surveys (Bell, Bryman, 2015). The survey has been sent by email and all the email addresses have been scraped using specific tools. I have used both Email Hunter4 and Anymail finder5 in order to find founders, CEOs (Chief Executive Office) and CMOs (Chief Marketing Officer) within the influencer marketing platforms and agencies environment in the US. I have chosen founders, CEOs and CMOs because they are the highest positions of a company with daily management challenges and they have an overview not only of their own company but also of what is happening in the influencer marketing field. I have intentionally omitted CTOs (Chief Technical Officer) since my survey focuses on marketing and not on technical questions. I sent a total of 97 emails because 97 is the number of email addresses that I was able to find using the tools previously cited. The first tool – Email Hunter – is a Google Chrome extension that automatically finds in the internet the email of a certain user when you visit his or her Linkedin profile; the second tool – Anymail Finder – is a platform in which the searcher has to insert name, surname and company domain (e.g. imagency.com) of a specific user and the tool will look for possible email addresses in the internet that could match with the real one. 4 5

https://hunter.io https://anymailfinder.com

Using a web survey such as TypeForm,data can be collected quickly and downloaded in a CSV (comma separated value) file easily readable with software like Microsoft Office6, OpenOffice7 or even Google Spreadsheet8. Here below there are the survey questions and possible answers I implemented in the survey: 1) Which channels do brands prefer to use when developing influencer marketing campaigns within the fashion industry? a) Instragram, b) Twitter, c) Facebook, d) Blog, e) Linkedin, f) YouTube, g) Snapchat, h) Other, specify 2) Which are the main issues that brands, in your experience as a platform or an agency, are now facing? a) Monetary issue: low budget from the brands for influencer marketing campaigns or too high prices requested from the influencers, b) Measurement: difficulty in measure the effectiveness of a campaign, c) Identification of influencers: brands still struggle in finding the right influencers by their own, d) Legal: manage monetary rewards and legal aspects with influencers, e) Other, specify 3) How much of brands' overall marketing budget is usually designated to influencer marketing? a) Less than 10%, b) 10-30%, c) 30-40%, d) 40-50%, e) 50-70%, f) more than 70% 4) Do the brands usually think that the price per post requested by an influencer is too high? a) Yes, a lot of times, b) Often, c) Sometimes, d) Never happened 5) How much more a brand would be willing to pay for an influencer if his/her engagement rate was higher? a) The same as influencers with a low engagement rate, b) 1,5X, c) 2X, d) More than 2X

https://products.office.com/en-us/home https://www.openoffice.org 8 https://spreadsheets.google.com 7

4.7.2 Data scraping

Data scraping “can be broadly defined as a data collection technique where a computer program extracts and reposts data from a user output” states Hirschey (2014). It is fundamental to say that the data scraping process I used helped me a lot in gathering the data needed for the purposes of this thesis and that, if instead it would had been done manually, it would had taken weeks of work. Instead, using the mentioned data scraper, I was able to gather the same data in few minutes. I used a data scraper to gather data such as engagement rate of single influencers and the average engagement rate of 1,500 Instagrammers within the fashion industry in the US, which were the data needed to implement in my formula. The formula created in this thesis - and that I will explain in detail in the data scraper creation paragraph - was meant to calculate the monetary value of an Instagrammer’s promoted post. In more details, in order to calculate the average engagement rate of American Instagrammers within the fashion industry, I had to gather the engagement rate of all the Instagrammers in this field (within a followers range between 10,000 and 1,500,000 in order to leave out non influencers – less than 10,000 – and celebrities –more than 1,500,000). For instance, the Instagram engagement rate of a specific Instagrammer, as previously stated under the “engagement, impressions and reach” chapter, is a percentage calculated dividing the total of engagement (likes and comments) by a certain number of photos and divided again by the total number of followers of the influencer. The average engagement rate, instead, is the average of all a set of engagement rates within the same social network or the same industry that gives and indication to influencers and brands on a factor to look at before starting a work relationship between them. To give the reader a deeper understanding of what is the practice of data scraping, this type of data collection extracts data from the HyperText Markup Language (“HTML”) of a page (or multipages) that a website displays (Lindenberg, 2012). Data scraping allows a programmer to seek and collect data faster, because once created the scraper – a tool that can be coded in different programming languages (e.g. PHP, R, Python, Java, Javascript) – it will run working in background, gathering the data sometimes in few minutes, which is way less than hours that could take if the same work was done manually. The main advantages of this method are: a fast data collection on hundreds or

thousands of data spread over several pages and the possibility to download the data in raw files as CSV (comma separated value) or JSON (JavaScript Object Notation). On the other hand, the main issue when applying a data scraping technique is that if a targeted website changes its HTML code, the scraper will not be able anymore to scrape certain data and the programmer will have to manually edit the source code in order to fix it. Even if there are already data regarding the average engagement rate on Instagram on the internet, I preferred to scrape and collect data, selecting only Instagrammer within the fashion industry and located in the US in order to obtain primary data, that are data gathered for a specific research problem and, for this reason, they totally fit with the purpose of this thesis, primary data are opposite to secondary data, which are the ones already existing and that can be found on specialized databases (Hox & Boeije, 2005). Two key benefits of primary data are that the data collection will be specific to the researcher's need and the researcher will control the quality of it (My Market Research Methods, 2011). I downloaded Instagrammers’ information in a CSV file from Scrunch, an influencer marketing platform that allows everyone to filter influencers based on variables such as country, follower number range, posting frequency and industry and I imported them into my scraper. In this thesis, the process of data collection and calculation has been the following: 1. Create the web scraper 2. Run the scrape on a list of 1500 Instagrammers within the fashion industry in US 3. Export a CSV file with all the engagement rates and number of followers for all the 1500 Instagrammers 4. Import the CSV file into Google Spreadsheet 5. Create a scattered graph from the data into the CSV file To better explain all the data collection process flow, I created a graphic (Figure 9) to show it.

Figure 9: How the data scraping collection flow works

4.8 Data analysis Once the data were collected through the semi-structured interviews, the survey and the data gathered through the scraper, I proceeded analyzing the data and start answering the research questions. For what concerns the survey, I used a statistical approach in order to align all the answers and get a numerical result out of it. In regards to the semi-structured interviews, I compared the answers to find similar replies among the interviewees whereby possible and get an overview of subjective practitioner's’ point of views and beliefs. For what concerns the data scraping, I scraped information such as number of likes, comments and followers from 1500 Instagrammers within the fashion industry in US, which enabled me to both analyze singular profiles of Instagrammers and also the average engagement rate of Instagrammers with a number of followers range between 10,000 and 1,000,000+. Knowing these data, I was able to use them to calculate the price for an Instagrammer’s promoted post that a brand should pay for.

4.9 Reliability and validity Reliability and validity are both fundamental quality criteria concepts of what is scientifically accepted as proof by scientists (Bryman & Bell, 2015). For instance, reliability and validity are two basic properties of empirical measurement (Carmines & Zeller, 1979). Reliability, fundamentally, “concerns the extent to which an experiment, test, or any measuring procedure yields the same results on repeated trials” (Ibid, p. 11). Validity, instead, is an important factor for the effectiveness of a research and this because if a part of research is invalid it means that is worthless (Cohen et al., 2013). For example, “in qualitative data validity might be addressed through the honesty, depth, richness and scope of the data achieved, the participants approached” and “quantitative data validity might be improved through careful sampling, appropriate instrumentation and appropriate statistical treatments of the data.” (Ibid, p. 133) The main purpose of this section is to make sure that the thesis is not influenced by contextual or subjective factors, aiming to reduce bias basing the study on objectivity. Bias are described as an affection of the research’s findings caused by researcher’s actions (Kerr, 1996). Davis (2011) attributed one of the causes of bias when a researcher considers the interviewees differently, treating them inconsistently and this difference in treatment shows the researcher’s assumptions about the results of the interview, moving from objectivity to subjectivity, tending to change the final outcome (Ibid). Throughout this thesis, I tried to implement these concepts and reduce as much as possible all the bias components, still taking into account that this cannot be avoided totally for the semi-structured interviews.

4.9.1 Reliability As previously mentioned, reliability “concerns the extent to which an experiment, test, or any measuring procedure yields the same results on repeated trials” state Carmines and Zeller (1979, p. 11). In quantitative research there are “three principal types of reliability: stability, equivalence and internal consistency” (Cohen et al., 2013). In my case I took in consideration the first type, stability, that measures the consistency over similar samples and over time (Ibid.) This means that in my case

when I created the survey in order to collect quantitative data, if tested and retested within a similar time span on the same sample, the answers to it should be very much alike if not exactly the same. The time span should be not too short because respondents could remember their answers and just replicate them without thinking about them, nor too long because in the meanwhile other external influential factor that could distort the data. The same concept can be applied also for the two interviews I made. For what concerns stability in the scraper, if tested on similar samples and over time, since it is a machine that executes commands in the code that I wrote, it will scrape the same requested fields such as name, number of followers, number of likes and comments.

4.9.2 Validity By validity “we mean that a research study, its parts, the conclusions drawn, and the applications based on it can be of high or low quality, or somewhere in between.” (Onwuegbuzie and Johnson, 2006, p.1). There are several different kinds of validity (Cohen et al., 2006) and I decided to take in consideration two of them: internal validity and external validity. The internal one can be defined as demonstration that a certain event or data set provided by a piece of research can be sustained by the data (Ibid.). The external validity “refers to the degree to which the results can be generalized to the wider population, cases or situations.” (Ibid, p. 136). In this thesis, the internal validity is provided since all the research done is based on data given by experts in the field and also the data scraped from real Instagram profiles. Therefore, the conclusions will be based entirely on real numbers and not just speculations. Also the external validity for this thesis can be considered high. For instance, the formula is a generic one that can be used across industries and countries. The only factor that will change is the monetary range of price that brands would be willing to pay for an Instagrammer with a higher engagement rate within a certain industry and country. Moreover, in order to validate the JavaScript code of the scraper I wrote, I showed it to a back-end developer expert in NodeJS to know if the code was valid or if it had bugs there could have affected in some way the scraping process. After reviewing my code, the developer assured me that everything was done correctly.

4.10 Limitations and Delimitations This section is meant to discuss all the limitations and delimitations of this thesis and therefore the many aspects that might influence this thesis aims, choice of methods, analysis of data and its conclusions.

4.10.1 Limitations Limitations can be defined as circumstances and concerns that emerge in a study that are out of the researcher’s control. “They limit the extensity to which a study can go, and sometimes affect the end result and conclusions that can be drawn.” (Simon & Goes, 2013, p. 1). For example, a study might have access only to certain data, restricted number of people or specific documents and these are all limitations (Ibid.). It is important to remember that generally limitations are a concern that are not in the researcher’s control and, as declared previously, a researcher not necessarily have to be concerned by limitations, since they affect all research projects. Following the above statements, a limitation of this thesis could be the unpredictability of the survey answers’ rate: for instance, prior to the data collection, I was not aware of how many of the 97 platforms and agencies I have contacted would answer my questions.

4.10.2 Delimitation Unlike limitations, that as stated previously are implicit characteristic of the methodology chosen or the access to certain data, delimitations are described as specific decisions made by the researcher (Simon & Goes, 2013). Moreover, delimitations create boundaries on the parameters of the study such as the sample chosen, setting and instrumentation (Bryman & Bell, 2015). I have decided to delimit my research mostly on the social network Instagram because, according to the data (Cohen, 2015), is the the best social channel in terms of average interaction rate and it has now more monthly active users than Twitter (AdWeek, 2016). Moreover, after choosing Instagram as main social platform, I decided to limit my data collection within the fashion industry, since a vast number of brands (Buryan, 2016) are active on Instagram operate in that field, as it has been

reported by MediaKix that in 2016 looked at the top 200 brands with the highest number of followers on Instagram and found that 51.5% were in the fashion industry (Mediakix, 2016). For instance, choosing only one industry allowed me to have a better, deeper and clearer understanding of the average engagement rate within fashion business. Another delimitation of this project is the decision to interview only two practitioners, and this was mostly decided due to the lack of time, using a non-probability sampling in order to collect information the most related possible to my thesis, having enough time to interview the experts, record and transcribe the conversations and analyze the data without the risk of running out of time. Lastly, I chose to focus on the US market because it is the #1 country for active monthly user on Instagram (Statista, 2016) and this helped me in having more possibility to find enough fashion Instagrammers for my study. For these reasons, choosing only one industry and one country, allowed me to have a better and clear understanding of the average engagement rate within fashion business and delimit my research in order to not have too many average engagement rates also from other industries or countries that could be very different from the market I am interested in.

5.0 Literature review As I previously outlined in the above chapters, unfortunately, since influencer marketing is a fairly new concept, there are not many academic papers on it so far. For this reason I preferred to focus the literature review on three main topics – Word-of-Mouth Marketing, Influencers and Native Advertising – that can explain the birth and growth of the advertising techniques which lead to the creation of the influencer marketing practice. For instance, as a point of departure, we could argue that influencer marketing relies most of its effectiveness on the so called Word-of-Mouth Marketing: this practice, also known by practitioners with the acronym “WOMM”, has been described by Kozinets et al. (2010) as a consumer-to-consumer communication strategy done by professional marketers with the aim of influence. WOMM has been studied also by Bughin et al. (2010) who states that – thanks to the digital revolution – the communication paradigm changed from one-to-one to one-to-many: this

means that previously Word-of-Mouth was more an act of private endorsement regarding a brand or a product and in the last years, instead, it has become a powerful marketing way to present brand products from one person to many users. Therefore, if we take Bughin’s words into consideration, the WOMM practice is the technique used by influencers to endorse a certain product to their audience. For example, this happens every time an influencer posts online a review of a product presenting pros and cons of it, and doing so, influencing the decision-making process of her/his followers, since they trust her/his expert opinion. If we stress more the word-of-mouth concept Brooks (1957), already in the ‘50s, recognized it as a phenomenon that affects a lot of the purchase decisions with the existence of opinion leaders within communities and groups that are sought by other people for advice and information regarding the field in which they are experts (Ibid.). The opinion leader concept has been analyzed also by Corey (1971) and defined as a person that exists in every socioeconomic group and influences that specific “group's ideas about product-related issues” (Ibid. p. 57). If we then compare these statements and definitions we can draw the conclusion that within influencer marketing the last years there has been a terminological shift from “opinion leader” to “influencer” still having almost the same meaning. Summing up it is possible to say that Influencer Marketing is an evolution of WOMM and there are similarities between them, such as the core concept of endorsing a brand or a product to other people. Anyhow, I personally believe that there are also differences regarding, for example, the language used, previously more private in a one-to-one communication and lately opened to the public, and also the media used to influence the others, from more traditional channels to the social media ones. To mention another example of how influencers are not a completely new player in our society, a study conducted by Gladwell (2000) concluded that there are three categories of people that can influence the others: mavens, connectors and salesmen. “These people are claimed to play a critical role in the word-of-mouth epidemics that dictate our tastes, trends and fashions” (Budak et al., 2010). The mavens are those who accumulate knowledge and know which are the best products and services are on the market and they are willing to share them with other consumers. If a consumer has a problem or a need, a maven tries to solve it sharing the accumulated knowledge about a certain

niche field. This makes mavens experts of a certain topic or niche market and the other users listen to their opinions, being affected from them (Ibid). The connectors are people with a big network of connections and mostly work with partnerships and deals. Finally, the salesmen are highly persuasive, motivated by monetary rewards willing to achieve certain financial goals. These three categories can be found also within the influencer marketing context and outline the influencer’s specific skills: for instance the influencer needs to know the topic or the product she/he is speaking about, like the maven category, she/he needs to be able to create a network and possible partnerships with brands and agencies, like connectors and ultimately, the influencer needs to help brands in driving more sales, like salesmen. on top, if implemented with the other statements on influencer marketing cited in the previous chapters, it could provide a better understanding of which kind of category a brand needs to look for before a specific influencer marketing campaign, depending on the brand and the goals it wants to achieve. For what concerns the fashion industry, which is the one I have decided to focus on for this thesis, the decision for practitioners and companies to start working and allocating resources on social media has been a successful change in direction (Mohr, 2013). Mohr, in his paper, highlights how much the rise of social media from 2009 and the growth of word-of-mouth marketing helped fashion brands in making partnerships with influencers getting the “opportunity to improve customer relationships and to ultimately capture a larger audience” (Ibid., p. 18). On top, also Wolny & Mueller (2013) argue that fashion trends are co-created by consumers and that fashion can be seen as a “powerful social symbol used to create and communicate personal as well as group identities” (Ibid., p. 563). Both the papers go in the direction of co-creation and improvement of the customer relationship, using social media as the channel where not only brands talk to the customers, but also a place where customers give feedbacks, co-create contents and influence other customers. This means that customers are not anymore only passive consumers but that have become in the last years active players that have the power to influence other customers through social media channels and therefore they could be considered influencers as well.

All in all, based on these two studies mentioned, the analysis of the fashion industry related to the social media environment is relevant when writing of influencer marketing: for instance, influencers are - even if partially - driving the communication between fashion brands and the audience, becoming a substitute of more offline and traditional advertising techniques. Another important term to take in consideration when we talk about influencer marketing is the one called “native advertising”. It has been described by Wojdynski & Evans (2016) as “any paid advertising that takes the specific form and appearance of editorial content from the publisher itself“ (Ibid. p. 1) and has been found that this type of advertising displays less skepticism from viewers if compared to a text or a banner advertising (Tutaj & Van Reijmersdal, 2012 in Howe & Teufel, 2014). If we take in consideration Instagram, which is the social media channel this thesis is focusing on, an example of native advertising could be a picture of an influencer that is having a good time with friends and is wearing a set of specific clothes, writing in the photo’s description information about the promoted brand products. Native advertising results more effective than banner advertising also because native ads “recorded an 18% higher lift in purchase intent and a 9% higher lift for brand affinity responses than traditional banner ads” (Einstein, 2015, p. 231). For instance Influencer Marketing can be seen as a form of native advertising because brands place their products in form of editorial contents in influencers’ pictures, video or blog posts, choosing a soft-selling approach instead of a hard-selling one: the first approach has been defined already in the 80s’ from Mueller as a selling approach more subtle and indirect compared to the second method, the hard-selling, that has been defined as a direct approach that has the main aim to encouraging a quick sale (Mueller, 1986). All in all, we are surrounded by people that can influence our choices. These people have been named in several ways throughout the years, as introduced above. Influencer Marketing is just a new way for brands to advertise their products in a more indirect and familiar way for us. The concepts I read and I added in the literature review have been fundamental for me in order to understand the background of the influencer marketing practice, where does it come from and how

it is grounded, the reasons why it is growing so fast and also that it is a combination of existing concepts and marketing strategies already applied in the past.

6.0 Theories This section is meant to introduce the two main theories that have been used as theoretical framework and that have been combined in an operational model in order to place the influencer marketing practice within the current and traditional consumer buying process and buying behavior model theoretical frameworks.

6.1 Consumer buying process The consumer buying process theory is a fundamental one that I decided to use for this thesis since it gave me not only an overview of this process step by step, but also because it helped me in identifying between which of the steps Influencer Marketing lays. Below in Figure 10, is it possible to see the consumer buying process model from Churchill and Peter (1998). Figure 10: Gilbert A. Churchill, Jr. J. Paul Peter Chapter 6 Consumer Behavior Marketing. Source of the slide: Charles (2016, p.3)9

Retrieved from http://slideplayer.com/slide/6509219

The model above shows that in the consumer buying process there are three main factors that influence consumers in the process of buying something: Social Influences, Marketing Influences and Situational Influences. These three factors are then divided into further six steps: Need/problem Recognition, Information Search, Alternative Evaluation, Purchase Decision and Postpurchase Evaluation. In my thesis, I will mostly focus on these two process steps: Alternative Evaluation and Purchase Decision. These two factors can be influenced by micro and macro-influencers since, as previously stated, influencers have the power to influence other people during the decision-making of the buying process, suggesting them to buy a certain product. All in all, this is the reason why I think this model is applicable to my research questions, since the consumer buying process model is a fundamental framework to better understand the relationship between consumers and influencers and where influencers can be positioned within this process.

6.2 Buying behaviour model Kotler & Armstrong state that “consumer purchases are influenced strongly by cultural, social, personal, and psychological characteristics” (2010, p. 135). The majority of these factors cannot be controlled by the marketers but have to be taken in consideration when creating a marketing campaign (Ibid.).

Figure 11: Factors influencing consumer behaviour (Kotler, 2012). Source: Lau (2009, p. 8)10

Figure 11 above shows the factors that influence the consumer behaviour categorized by Kotler. The figure includes seven clusters of factors: psychological, personal, marketing programs, environmental influences, cultural, social and buyer’s responses. To make some examples of factors for each of the cluster, the psychological ones can be the motivation of a consumer, his/her perception, beliefs and attitude; the personal ones are age, occupation, economic situation and lifestyle; for what concerns the social factors, they can be reference groups, family and status (Ibid.). In my case I will focus on the Marketing Programs factors with the aim to expand and combine them with some of the Social factors, especially the reference groups. This means adding Influencer Marketing as a strategy in between Marketing Programs factors and Social factors as I show in the Figure 12 below that I have created. 10

Retrieved from https://www.slideshare.net/alwynlau/bus169-kotler-chapter-05

Figure 12: Influencer Marketing as a strategy combination of Social Factors and Marketing Programs factors

For instance Influencer Marketing can be added in the middle of Social factors and Marketing Programs factors because it is a particular form of marketing that take in consideration not only the product and the marketing strategies to promote it but focuses also a lot on the target and its social aspects. Since the target, in case of influencer marketing, is the group of followers of an influencer, a factor as reference groups’ of a consumer can influence the buying process. In fact, as stated previously, “the personal words and recommendations of trusted friends, associates, and other consumers tend to be more credible than those coming from commercial sources” (Ibid., p. 139). Kotler & Armstrong cite word-of-mouth influence and influential people under the social factors, highlighting that when influencers talk, consumers listen to them, trusting their opinions and recommendations. (Ibid.) This is why I decided to place influencer marketing under the social factors and, moreover, this means that social factors as groups, community and also social networks (especially when I refer to this thesis that is about Instagram) can influence the decision making during the buying process and influencers play as opinion leaders of these groups and communities on social networks.

6.3 Combination of the theories - Creation of the operational model The two theories – consumer buying process and buying behavior model – previously explained can help in understanding where to place Influencer Marketing within the already existing theoretical landscape. I created a graphic visible in Figure 13 that shows the combination of the two theories and the placement of Influencer Marketing. Figure 13: Influencer Marketing in the middle of Alternative evaluation and Purchase decisions Consumer Buying Process’ steps and the Social factors and Marketing Programs factors’ of the buying behaviour model.

The purpose of this combination of theories was to fit the new influencer marketing practice within some pre-existing and traditional theories. For instance, based on all the evidences mentioned throughout the thesis and how influencer marketing can be seen as an evolution of the marketing and advertising practices, collocating it also on a theoretical level can provide academics a deeper understanding of where influencer marketing stands and how traditional theories could be

implemented. The figure created above will be used as the main operational model for this thesis and both the research questions and my formula will be circumscribed within this new framework.

7.0 Analysis As previously stated in the methodological paragraph, I have collected data through three different methods: a quantitative survey, two qualitative interviews and a quantitative data scraping. Here below all these three sets of data will be analyzed and thanks to their key findings, I will be able to answer my research questions and the main problem formulation.

7.1 Survey results This section is meant to analyze the survey results I collected from influencer platforms and agencies. As stated in the methodology, in order to gather the data, I have sent an email containing a link to my survey created with TypeForm to 97 founders, CEOs and CMOs of influencer marketing agencies and platforms and 46 of them filled it out. This means 47% of the people answered the survey. To better illustrate and analyse the answers given here below I will take one question at the time and visualize it through tables or graphs. The first question asked was: “Which channels do brands prefer to use when developing influencer marketing campaigns within the fashion industry?”. Here below in Figure 14 and 15 I summarized the answers by the percentage of channels preferred by brands. Figure 14: “Web channels preferred by brands for an influencer marketing campaign“ Instagram Twitter Facebook

Blog

Linkedin YouTube Snapchat Other, specify

58%

15%

Figure 15: the results of the first question shown in a pie chart

This answer validates that Instagram is considered the best social network to promote fashion products, since 58% of respondents chose this as the best channel. In second position we can see that personal blogs are featured - with a 15% and as well as YouTube with the same percentage. The second questions asked in the survey was “Which are the main issues that brands, in your experience, are now facing?”. As before, I have summarized in Figure 16 and 17 the results in a table and shown them also in form of a pie chart. The answer “monetary issue” referred to low budget allocated by the brands for influencer marketing campaigns or too high prices requested from the influencers. Then the answer “measurement” referred to any kind of difficulty in measure the effectiveness of a campaign. The other two answers where “Identification of influencers”, which was meant to illustrate if brands still struggle in finding the right influencers by their own and “legal”, which related to monetary rewards management and legal aspects when working with influencers.

Figure 16: answers results to the second questions Monetary issue

Measurement

Identification of influencers

Legal

Other, specify

30%

25%

35%

Figure 17: results to the second survey question shown in a pie chart

In order to gather a comprehensive overview on the main challenges in the influencer marketing field, respondents had the possibility to give not only one, but two answers to this question. This decision was made in order to get enough information on the two biggest issue that brands – from agencies and platforms’ opinion – are facing at the moment and not only delimit their answers to only one option. What is easily visible on the pie chart is that the two main actual issues that brands are facing in this moment are linked to monetary field and how to identify influencers respectively 35% and 25%. For what concerns the answers under “Other”, I will not take them in consideration due to low volume and not enough relevance. Due to this outcome, I will focus mostly on “monetary issue” and “identification of influencers” with the aim to create a tool to help brands in

solving those issues. For what concerns the identification of the right influencers, I will expand the framework I have created combining the Churchill and Kotler theories, going deeper in detail and giving to the brands practical tips to follow in order to find the best influencers for an influencer marketing campaign. For what concerns, instead, the monetary issue, I will create a formula that will help brands in getting a price suggestion (for a singular promoted post) for any influencer within the fashion industry in the US that I will explain in detail in the data scraper creation. In this way, the brand will be able to look for an influencer through my tool and get a price per promoted post based on the formula I will describe in details later. This will help both brands and influencers in starting a conversation to find the best price proposal for both. The third question was “How much of brands' overall marketing budget is usually designated to influencer marketing?” and the respondents had the possibility to choose one of the six answers below. This is important to know to get an overview (Figure 18) of how much brands are investing right now in influencer marketing and understand its potential in terms of business. Figure 18: the answer results to the third question Less than 10%

10-30%

30-40%

40-50%

50-70%

More than 70%

45%

36%

10%

This answer shows us that the budget for influencer marketing is still only a little percentage of the overall budget of a brand. This could be because brands, since do not know yet very well influencer marketing and how to leverage its potential are not sure if they should invest and allocate budget in it or not. Another perspective on the results could be that brands, not having enough factors to find the right influencers, did at least once a campaign with the wrong influencer and, not getting enough return on investment or interest for a certain product, decided to cut the investment for influencer marketing.

The fourth question was “Do the brands usually think that the price per post requested by an influencer is too high?” and the they answered for the 57% of the total that influencers, a lot of times, ask a too high price per promoted post (Figure 19 & 20). Figure 19: the answers results to the fourth question Yes, a lot of times

Often

Sometimes

Never happened

57%

28%

11%

Figure 20: the results to the fourth survey questions shown in a pie chart

For instance, as we can see from the pie chart, more than a half of the respondents say that influencers – a lot of times – ask a price per promoted post that brands find too high. Thanks also to this answer, it is possible to see that the influencers at the moment are asking more than what brands think would be fair. For this reason, as previously stated, I will create a tool that suggest the price per promoted post for any influencer in the fashion industry within the United States. This hopefully could help both the two players (brand and influencer) in starting a conversation and find a possible monetary deal.

The last survey question was “How much more a brand would be willing to pay for an influencer if his/her engagement rate was higher?”, whose results are shown in Figure 21. Figure 21: the answer results to the fifth survey question The same as influencers with a low engagement rate

1,5 times more

2 times more

More than 2 times more

24%

64%

11%

This question aimed to understand how much brands would be willing to pay more an influencer with a high engagement rate compared to one with a low engagement rate. I decided to combine together the answers #1 and #2 to create a range where the multiplicator number (how many times brands should pay more) is defined as X where 1 < X < 1,5. Knowing a number – in this case between 1X and 1,5X times more – I can use it in the formula I will create to define a suggested price per promoted post. In fact, my formula is based on the premise that a social media higher engagement rate usually brings to more sales or interest in a product than a low engagement rate (Morrison, 2015). For this reason, I suppose in my formula and tool that an Instagrammer with a higher engagement rate compared to the average in her/his follower number range (for example, an Instagrammer that has 500,000 followers have to be compared with other Instagrammers in the same industry that have around the same number of followers) should ask more money, since her/his contents will bring more interest and engagement than the ones created by other influencers with a lower engagement rate.

7.2 Survey key findings The survey answers confirmed that the preferred social network for Influencer Marketing in the fashion industry in US is Instagram but that the overall budget spent for it is still low, the majority of the times being less than 10% and in second position in a range between 10% and 30%. Another key finding from the survey is that the two main issues that brands are now facing in the influencer marketing field are related to monetary issues and the process of identification of

influencers. Moreover, brands find that a lot of the times influencers ask too much money to promote a product and that, in case they find an influencer with a higher engagement rate compared to other influencers, they are willing to pay more for a promoted post between 1X and 1,5X times. For this reason, as previously stated, I will create a tool to calculate a suggested price per promoted post for any influencer within the fashion industry in U.S. The suggested price will serve as a budgeting factor that brands can take in consideration during the process of identification of the best influencer for an influencer marketing campaign. All in all, these key findings entirely confirmed not only the issues I mentioned in the problem area, but also identify the most crucial challenges that brands are facing and how, if these were solved, they could benefit the influencer marketing field.

7.3 Interview results As stated in the interview methodology section, I had interviewed two experts in the influencer marketing field. The first person I interviewed is the Marketing Strategist at Call The Tune, an influencer marketing forecast agency. The second respondent is founder of Influencer Marketing Hub, one of the major industry resource for influencers, brands, agencies and platforms. I asked both five questions with the opportunity to express their broader opinion on the topic, since I decided to do semi-structured interviews and not a structured interview that would not allow the possibility for them to comment openly. I started asking if the interviewees confirmed the data I saw online, and afterwards validated also by the survey, regarding Instagram as the best social media channel to use for an influencer marketing campaign. Both the respondents, in each interview, answered me positively, confirming that Instagram is the best choice for brands when they want to create a campaign using influencer marketing. Especially the first respondent answered that, after having interviewed more than 20,000 partner influencers in the beauty, make-up and fashion industry, Instagram is the preferred social media because it has a more meritocratic algorithm. This because, on the contrary of Facebook where the contents with more likes and comments go on top of a user’s wall, on Instagram every picture has the same weight. If on Facebook, nowadays, in order to get enough coverage a company

or an influencer has to pay advertising, on Instagram influencers can still show their pictures with the organic, which means not paid, reach. As a second question, I asked why macro-influencers have an engagement rate lower if compared to micro-influencers. The interviewees provided me two main reasons: the first one is that a macro-influencer will have more generic type of followers that could not be necessarily interested in all the contents published by the influencer. In fact, the first interviewee stated that an influencer with 1,500,000 will quite impossibly have only followers all interested in the same topic and for this reason the engagement rate for each published post will be lower than a post of a micro-influencer whereas every his/her follower will enjoy it because he/she shares the same interest in the influencer’s topic”. The second interviewee provided also another reason: that is related to the law of large numbers that states “that the sample mean converges to the distribution mean as the sample size increases”11. In this case it means that the more people will follow an influencer, the bigger will be the number of followers and the bigger will be also the number of “ghost followers”. Ghost followers are inactive users (Peek, 2015) that once registered on a social network and have done only few actions (such as follow some influencers) then become inactive, for example signing in the social network few times a year or not at all. In other words it means that, applying the law of large number in regards of a macro-influencer, the amount of ghost followers could affect a lot his/her engagement rate more than what could happen to a micro-influencer. The third question was focused in investigating how much the context is important in influencer marketing since, as we saw in the previous chapters, if an influencer promotes a post not in line with her/his previous contents, it could be a fail for both the influencer and the brand. The first interviewee answered saying that context is fundamental in influencer marketing and provided me a practical example to illustrate me what he was meaning: an Instagrammer that works under Call The Tune collaborates all year long with only two brands, posting every week quality contents in line between them, with a constant storytelling and a stylistic main theme. This approach, so far, brought excellent results due to weekly perseverance, quality work and a good relationship with few brands

h ttp://www.math.uah.edu/stat/sample/LLN.html

where quality is preferred to quantity. The interviewee, in addition, said that it is not enough for an influencer to receive a present from a brand and talk about it without thinking about it but it needs to have the right content in the right context. Also the second interviewee said that context must come before the product, emphasizing the importance of how much an influencer should be contextually relevant to the brand’s niche market. As fourth question I asked which were the two biggest issues that, in their opinion as practitioners and experts, influencer marketing was facing at the moment. The first interviewee highlighted again the context, this time in terms of dissonance between the goals that the brand wants to achieve and the platform used. For example, he said that if a brand wants to directly sell a product online, Instagram does not allow users to place a direct link to the product in the photo description yet and this means that followers cannot buy the promoted product directly from the influencer’s photo. This does not mean that Influencer Marketing is not effective on this social media channel, but just that the impossibility to directly purchase a product through it could lead for the eventual customer, to hesitate in the purchasing and thus it could not lead to a fast sale. The second main issue that the first interviewee stated, is the pricing: in fact, since influencer marketing is a hot trend lately, a lot of influencers are asking more money than they should ask to brands and when brands pay more than what they were expecting and they do not see enough results, they will end the partnership with the influencer. The second interviewee said the first main issue that brands are facing at the moment in the influencer marketing field is an unstructured pricing system that should be used to regulate the influencers business. Right now, the interviewee stated, every influencer asks for what he/she perceives as a fair monetary reward and the brand has not enough data to base its decision on and the majority of the time it has just to believe the influencer and start negotiating. The second issue raised by the second interviewee is the lack of information about influencer marketing from the majority of the brands: in fact, a lot of the times when companies look for an influencer, do not analyze the right metrics but they still look at some numbers like the total number of followers which, as plenty of time stressed also in this thesis, is not enough in order to understand if an influencer is good enough for an online campaign.

Knowing the actual main issues for brands in influencer marketing can help me in creating the right tips and tool in order to give them more factors to look at before start a collaboration with an influencer for an influencer marketing campaign. The last question focused on the two biggest challenges within the influencer marketing practice for the upcoming year. The first interviewee answered that, first of all, it is important to bring more information about what is influencer marketing also in terms of technicality. Right now, in his opinion, information about it are mostly generic and that do not provide enough insights on, for example, how much brands should pay an influencer for an influencer marketing campaign. This is because if brands continue investing too much in influencers that are not giving back enough, brands will just stop investing in influencer marketing because they will think that the return on investment is not good. A similar answer was provided by the second interviewee, which highlighted again the importance of providing more structured information about influencer marketing and the best practices to implement. The second biggest challenge, for the first interviewee, is the link between sales and influencer marketing and the challenge in better explaining to brands that the two things have not directly been linked yet. For instance the first interviewee said that brands cannot only think in terms of direct return on investment of an influencer marketing campaign, but that influencer marketing has to help brands first of all in terms of awareness of their products and brand identity and only in a second moment, additionally but not necessarily, bring to a sale. For what concerns the second interviewee, the second challenge is to give a structure to the influencer marketing economy: in this moment there are not any historical references regarding how much an influencer should be paid and brands usually manage this process without any rules of guidelines. This can affect negatively not only the relationship between brands and influencers but also the influencer marketing itself.

7.4 Interviews key findings What it is possible to see from the answers given during the interviews, is that Instagram is the best social media channel for influencer marketing campaigns and this not only confirms the data I found on the internet, but it matches with the results of the quantitative survey. Moreover, knowing the reason why micro-influencers have higher engagement rate than macro-influencers, will help me in giving more insights regarding the best strategy that brands can implement depending on their goals. Another important point is that context is crucial in influencer marketing and that brands and influencers, in order to get the best from each other, have to create a solid partnership in which, on the one hand the influencer knows very well the brand that will sponsor - or at least the industry that the brand operates into - and, on the other hand, the brand leaves some freedom to the influencer to continue publishing contents in line with her/his previous ones and have a constant main theme. Finally, the results of the interviews gave me important insights regarding the main actual issues and the future challenges for influencer marketing. The actual problems are related to context, whose importance I have explained earlier, and to pricing: this last point confirms my initial willing to create a tool that can give brands the monetary value of a promoted post of a specific influencer. In fact, if a brand and an influencer both know which could be the best price per promoted post they can start a conversation with the aim of making a collaboration. For what concerns, instead, the challenges for the future it mostly came out that it is fundamental that brands start understanding more about what influencer marketing is and which is its potential in terms not only of direct return on investment, but also indirect ROI and improvement of brand awareness and identity.

7.5 Combining survey and interviews key findings and answering the first research question In order to answer the first research question which was: “Which are currently the main challenges that brands face when looking for the right influencer”, this chapter will summarize the key findings retrieved from both the survey and the interviews.

The survey responses highlighted that the main challenges are the creation of a monetary structure within influencer marketing, which is momentarily based more on assumptions than real data, and the lack of a good process for influencers identification. Also the interviewees stressed that there is a lack of a clear pricing of how much brands should pay influencers, and an information gap about influencer marketing best practices. All in all, combining these two sets of information, we can answer the first research question stating that the current main challenges that brands are facing are mainly two: a pricing model showing how much influencer should be paid brands can relate to and best practices to take in consideration in order to create a successful influencer marketing campaign.

7.6 Data scraper creation In order to calculate the average engagement rate of fashion Instagrammers in the US and get data about any influencer I wanted (such as number of likes, comments, followers) and also calculate the monetary value that brands should give to an influencer for a promoted post, the first thing I did was to go on Instagram.com and look for influencers that used hashtags related to the fashion industry such as #fashion, #fashionist, #fashionart. Then I started browsing some Instagrammers that published pictures using some of those keywords and I start looking at their public profiles. To calculate the engagement rate of every single Instagrammer (taking in consideration the last 20 photos in order to have enough data to calculate the engagement rate) I needed to find these data: ● Number of total likes on the last 20 photos ● Number of total comments on the last 20 photos ● Number of total followers In order to calculate how much time it would have be taken to gather those information, I started doing it manually. After I found some Instagrammers that published a picture with one of the keywords previously cited, I clicked on their profile picture and I firstly started looking at their total number of followers and secondly I went with the mouse over every single picture in order to see the number of likes and comments they got, writing down these data on a notepad. After having done this on all the last 20 pictures of a single Instagrammer, I opened my calculator and start summing up all the likes and comments in order to have the total amount. Once finished I had a

number of the total engagement and I divided it by the number of photos (20) and then by number of followers. Once done all this process I saw that to calculate the engagement rate of an Instagrammer it took almost 10 minutes. Since for this thesis I wanted to analyze 1,500 Instagram profiles, it would have taken, without considering any brake, 15,000 minutes that means 250 hours of time just to do that. Knowing that I would not have so much time I decided to automatize the process of data collection. As mentioned in the methodology section, a scraper helps a user in automatizing certain actions such as data gathering. Since I needed data that could mostly be found displayed on a web page, I decided to create the scraper using NodeJS, “a JavaScript runtime built on Chrome's V8 JavaScript engine”12. This scraper visits the Instagram accounts of a target list (in my case only American Instagrammers within the fashion industry) and scrapes these following data: ● Account name ● Number of total followers ● Number of total likes on the last 20 photos ● Number of total comments on the last 20 photos ● Email address (for the purpose of enabling brands to contact the influencer) The purpose of this scraper was to gather Instagrammer data and use them in order to calculate: 1. Instagrammer’s Engagement Rate 2. Average Engagement Rate among Instagrammers within a specific field and country 3. The monetary value for an Instagrammer’s promoted post The first point, the engagement rate of an influencer on Instagram, is fundamental to understand if the contents of that specific Instagrammer are found interesting from her/his followers. To make an example, we could have two Instagram users: the first one has 500,000 followers, a total of 6,000 likes and 3,400 comments on the last 20 photos; the second one, instead, has 70,000 followers, a total of 11,500 likes and 3,700 comments on the last 20 photos.

https://nodejs.org/en/

If we apply the Instagram Engagement Rate formula – already explained in the “engagement, impressions and reach” chapter – that is: [(number of likes + number of comments) / n. of photos)] / n. of f ollowers And that can be visualized also as:

We will have: User #1 (500,000 followers)

User #2 (70,000 followers)

[(6000 + 3400) / 20) / 500,000] x 100 = 0.09% [(11,500+3,700) / 20 / 70,000] x 100 = 1.08% The first user, even though has more followers than the second user, has a lower engagement rate (0.09%) than the second user (1.08%). This means that the follower number cannot be the only factor to take in consideration during the research of an influencer. For what concerns how I obtained the 1500 Instagrammers for this analysis, I downloaded a list of them from Scrunch, an influencer marketing platform where it is possible to filter influencers by country, hashtags, industry and number of followers as shown in Figure 22.

Figure 22: the filtering process on the Scrunch dashboard

As second step I used the obtained average engagement rate – that I will explain in details in the next section – to use it within the formula I created called “Pay Per Promoted Post (PPPP)”. This formula, using data such as followers, number of likes, comments and engagement rate, suggests the best price per post that an Instagrammer should ask to the brand. This can help both the Instagrammer and the brand in finding a monetary agreement based on quantitative and objective data and not only on the perceived value that the Instagrammer has in her/his mind.

7.6.1 Scraper code In this section I will present some of the most important parts of the scraper code in order to give an overview of how the code works. One of the first variable, visible in purple in Figure 23, is the number of pictures that the scraper has to take in consideration once launched the run command.

Figure 23: numerical variable that indicates to the scraper how many photos data analyze

The figure 24 below shows, instead, which data the scraper has to gather. The code tells the scraper to obtain the name of the user on Instagram and the total number of likes and comments on the last number of photos previously shown in the constant HOW_MANY_POST. Figure 24: the data that the scraper has to obtain for each Instagrammer

Finally, Figure 25 shows the code for the engagement rate calculation that I will use as variable in my formula “Pay Per Promoted Post (PPPP)” that I will explain in its dedicated paragraph later. Figure 25: the engagement formula written as a function in javascript

7.7 Data scraping results Once I collected the 1500 American fashion Instagrammers data using the influencer marketing platform Scrunch – that I introduced in the Data Scraping Creation section – I copied their Instagram account name and I pasted them into my javascript scraper and I run it, as visible in Figure 26.

Figure 26: my scraper running and obtaining data from a list of 1,500 Instagrammers

Then I selected all the data and I created a scattered graph (Figure 27), copying and pasting the raw data (in CSV format) into Google Spreadsheet, a Google free alternative to Google Excel, to show an overview of the engagement rates of all the 1,500 Instagrammers I took in consideration (that have between 10,000 and 1,500,000 of followers). Figure 27: a scattered graph that show the engagement rate and its linear trend on 1,500 Instagrammers within the fashion industry in the U.S.

As stated during the interviews to the experts, the engagement rate becomes lower going from micro-influencers to macro-influencers and the scattered graph based on my research confirmed the practitioner's words. In the graph is also visible that the majority of Instagrammers have less than 200,000 followers and that also shifting to macro-influencers, the number of influencers decreases. I then grouped all the 1,500 Instagrammers in 20 different groups based on the range of amount of followers splitted by 50,000. In this way I had 20 main groups: influencers with 10,000 - 60,000 followers, influencers with 60,000 - 110,000 followers, influencers 110,000 - 160,000 followers and so on, until 1,000,000+ followers. For each group, I calculated the average engagement rate using the trimmed mean, which is a statistical measure that doesn’t take in consideration sample at the high and low end to give an overall score removing those data that could affect the final outcome. So I calculated the average engagement rate of each Instagrammers group removing from the engagement rate column the MIN (the smallest engagement rate) and the MAX (the biggest engagement rate). The first thing that it is possible to easily recognize, is that with the increasing number of followers there is a decrease in terms of influencers, as visible in Figure 28 that I created. For example, in the first range (Instagrammers with 10,000 - 60,000 followers) there are 975 Instagrammers, in the second range (60,000 - 110,000 followers), instead, 297, in the third (110,000 - 160,000 followers) only 76 and this number decreases constantly. Figure 28: Number of influencers vs. Range of amount of followers

The second thing that I found out looking at the 20 groups of Instagrammers, is that, on the contrary of a first overview of the engagement rate on all the 1,500 Instagrammer (shown previously in the Figure 27) – where on a macro-view it seemed constantly decreasing with the increase of the amount of followers of an Instagrammer – the engagement rate is not actually decreasing constantly but it has some bumps, as visible in Figure 29. Figure 29: average engagement rate splitted by 20 groups of Instagrammers

Figure 29 above does not show a constant decrease how it seemed looking at the overview engagement rate in Figure 27. There is still an overall decrease, as it is possible to see in Figure 30, but there are also bumps as we saw in Figure 29 and this means that a brand has to take in consideration not only a macro-overview of the influencers but also a micro-overview in order to get the most precise average engagement rates possible on a specific Instagrammer’s range amount of followers range.

Figure 30: overall decrease in engagement rate and local bumps compared

7.8 Data scraping key findings As previously stated in the data scraping results, the first key finding is that there is a decrease in terms of average engagement rate with an increasing amount of followers. If looked on a macro-overview level, this decrease seems constant and could not give the right numbers that a brand should look for. This is why the brand should analyze the average engagement rate on a micro-overview analysis in order to to the calculation not on generic numbers but on the more precise ones possible. The second key finding is that the number of influencers decreases with increasing of the amount of an influencer’s followers. This is an important factor in terms of competition and demand/supply economics outcomes. The supply and demand law of economy states that when the supply increases, the price decreases and when the supply decreases, the prices – on the contrary – increase. (Robinson, 1962). This means that in the area of Instagrammers, for example, with a range amount of followers between 10,000 and 50,000, since it is really cluttered and saturate, there will be a lot of competition: this will bring the brands in having more leverage and decrease the monetary reward for influencers. On the contrary, in the area of Instagrammers with a range amount of followers

between 700,000 and 1,000,000, where there are just few players, the Instagrammers in there will be able to leverage on a situation of high demand and low supply, and using their contractual power in order to get more money from brands.

7.9 Pay Per Promoted Post (PPPP) Formula Creation This chapter is meant to introduce and explain the formula I created in order to calculate the price per promoted post of an Instagrammer within the fashion industry in the US. The formula, which I am going to explain in detail, is showcased in Figure 31: Figure 31: Pay Per Promoted Post formula written in JavasScript

Before starting introducing the details of this formula and how it works, it is important to stress again why I needed to scrape Instagrammers’ data and how I used them. First of all, I needed to calculate an average engagement rate of American Instagrammers within the fashion industry in order to get average engagement rate for different ranges of followers numbers: for example, using the data visible in Figure 27, it is possible to calculate the average engagement rate of Instagrammers with a number of follower between 100,000 and 200,000 or between 550,000 and 650,000. This depends by which Instagrammer the brand is interested in, in order to be able to compare his/her engagement rate with the average one of the other Instagrammer in the same industry and with a similar number of followers. Secondly, once I obtained the average engagement rate among Instagrammers and the engagement rate of a specific Instagrammer I wanted to analyze, I was able to calculate the monetary value for a promoted post. In order to give brands a suggested price to pay per promoted post of a specific Instagrammer, I created a formula that I called Pay Per Promoted Post, that I shorten in PPPP.

First of all, it is important to say that the amount 0.01 present in the formula is the average Cost Per Follower on Instagram suggested from the Huffington Post (Sharman, 2017). That number has to be read as $ 0.01. To make an example, an Instagrammer with 100,000 followers could ask to a brand $ 1,000 to promote a content. Secondly, for what concerns the Average Engagement Rate, I firstly wanted to just calculate an average number spanned on all the 1,500 Instagrammer without taking in consideration the number of followers. But then, in a second moment, when I saw that the number of followers and engagement are correlated (as we saw in the previous chapters) it would not be wise to not take this fact in consideration. In fact, if I had decided to calculate the average engagement rate not taking in consideration any difference between an influencer with 10,000 followers and one with 500,000 followers, the one with 500,000 would have been affected negatively when analyzed using the “PPPP” formula. The average engagement rate of the 1500 Instagrammers I analyzed – within the fashion industry in US in a range between 10,000 and 1,500,000 followers – is 2.43%. But as we saw in the scattered graph previously presented in Figure 27, the engagement rate percentage decreases with the increase of the number of followers. Said so, if we do not take into account the specific information of the range an influencer is in, an influencer with 500,000 followers with 2.3% engagement rate would be negatively affected by the formula, because it would get only $ 5,000 (0.01 $ * 500,000 followers), since 2.3% is less than 2.43%, that is the average engagement rate of all the 1,500 Instagrammers analyzed. In fact, the average engagement rate of followers within a range of 450,000 and 550,000 is 1.9%, and an Instagrammer with 500,000 followers and an engagement rate of 2.3% should get more money compared to other Instagrammers within the same industry and around the same number of followers. The formula shown in Figure 31 has to be read as the following: If the “engagement” (the engagement rate of the analyzed influencer) is minor than than “AVERAGE_ENGAGEMENT” (the average engagement rate among the other Instagrammer that have a similar number of followers), then the code just calculate $ 0.01 multiplied by number of followers.

This means that, since the engagement of the analyzed influencer is less than the average, that Instagrammer is not giving any additional value to the brand in terms of engagement and he/she only deserves a monetary reward based on a pay per follower payment ($ 0.01 * n. of followers). Instead, if the analyzed Instagrammer has an engagement rate higher than the average engagement rate, there are two possibilities:

1. If the difference of the subtraction between engagement rate and average engagement rate is a number between 1 and 2, then the cost has to be calculated as: 2 (0.01 n. of f ollowers) (√ engagement

averageengagement

1. If the difference of the subtraction between engagement rate and average engagement rate is a number major than two, then the cost has to be calculated as: 3 (0.01 n. of f ollowers) (√ engagement

averageengagement

This means that, since the Instagrammer has a better engagement rate than the average, she/he can give an additional value in terms of more interest from her/his followers towards the product promoted and, for this reason, the brands should give to the Instagrammer a monetary bonus. The only difference between the two formulas presented is the use of the square and cubic root. The reason why I used the square and cubic root is because, after analyzing the answer to question 5 of my survey (“How much more a brand would be willing to pay for an influencer if his/her engagement rate was higher?”), I saw that brands were willing to pay an amount between 1X and 1.5X times more an Instagrammer with a higher engagement rate compared to one with an average engagement rate among other Instagrammers with the same amount of followers. In fact, after having done different tests, I saw that in order to obtain a suggested price consistent with the brands value perception, I had to use a square root (if the subtraction of engagement and average engagement rate returns a number between 1 and 2) and a third root (if the subtraction of

engagement and average engagement rate returns a number be higher than 2) in my formula to have a result near to a range between 1X and 1.5X. Knowing the engagement rate of an Instagrammer and an indicative amount of money to pay for a promoted post, it can help on the one hand the Instagrammer in better understanding his or her suggested and potential monetary reward and on the other hand it can give an indication to brands in understanding the price range of specific influencers on Instagram. Since one of the biggest problems at the moment for brands – as saw in the results of the survey and in the interviews with practitioners – is the budget to invest in terms of influencer marketing campaigns, having the possibility to use a tool that gives insights such as Engagement Rate and Pay Per Promote Post, it can guide the brands in better choosing the influencers based also on budget decisions.

7.10 Combination of PPPP Formula with Data Scraper Results and answer to the second research question This chapter is meant to combine the theoretical PPPP formula I created with the real data retrieved from the data scraper. For instance, the ultimate goal is to concretely test the formula and the tool with real Instagrammers’ data in order to check the validity and reliability of the formula. For instance, if a brand wants to calculate how much to pay an American Instagrammer within the fashion industry that has, for example, 316,265 followers (this is practical example using an existing Instagrammer located in the red frame in Figure 32 that I have created) and an engagement rate of 3.17%, the brand has to look at the average engagement rate around the area of influencers with the same amount of followers, which is 2%.

Figure 32: average engagement rate for Instagrammer with an amount of followers around 300,000

Knowing that the average engagement rate of the other Instagrammers with a similar amount of followers is 2%, it is possible to calculate the monetary value per promoted post that is shown in Figure 33. This calculation is done using my formula previously showed that can be written, in this case, as: 2

(0.01 316, 265) (√3.17

2 = (3, 162.65)(1.082) = 3420.93 $

Where:

I used the formula with the square root – already described in detail under the Pay Per Promoted Post (PPPP) Formula Creation chapter - since the difference between 3.17% (the engagement rate

of the analyzed Instagrammer) and 2% (the average engagement rate of other Instagrammers with the a similar number of followers) is 1.17 and this number is included between 1 and 2. The result of this calculation is visible in Figure 33 below. Figure 33: the scraper that shows information about the last 20 photos of an Instagrammer with 316,625 followers and the suggested price per promoted post.

Figure 33 above shows the scraped information of the Instagrammer used as practical example. The scraper obtain the total likes and comments of the last 20 photos, the total number of followers of the Instagrammer and, using these data, calculated the engagement rate and suggested price per promoted post.

We can do the same also for every other Instagrammers within the list of 1,500 that I scraped. In fact, if I analyze an Instagrammer that has 211,298 followers with an engagement rate of 3.97% and we know that the average engagement rate of other influencers in the same industry – if we look at the graph of the 1,500 Instagrammer is 1.72%, we will apply the formula in this way: 3 (0.01 211, 298) (√ 3.97%

1.72%) = 2, 112.98 1.31 = 2, 768.79 $

Where:

Since the difference between the engagement of that specific Instagrammer (3.97%) minus the average of other Instagrammer with a similar amount of followers (1.72%) returns 2.02, the formula that involves the cubic root is used. The result of this calculation is visible in the Figure 34 below.

Figure 34: the scraper that shows information about the last 20 photos of an Instagrammer with 211,298 followers and the suggested price per promoted post.

Figure 34 above shows the data scraped such as number of likes and comments on the last 20 photos and number of followers from the second Instagrammer used as example. As seen in the first screenshot example, also in this case the tool calculated the engagement rate and the suggested price per promoted post. Both the multiplicators of the two examples above (1.08 and 1.31) are included between the range 1 and 1.5, the range of number that brands are willing to pay more for an Instagrammer with a higher engagement rate.

If we take again the first example of Instagrammer analyzed above, that specific influencer with a higher engagement rate compared to other similar influencers, should be paid from the brand $ 3,420 ($ 3,162 * 1.08) instead of $ 3,162 (that is the result of the multiplication of 0.01 $ by the number of followers, in that case 316,265). As previously stated, a high engagement rate means more interest in a promoted product that can convert in sales. Said so, the brand should recognize this value to the Instagrammer and give her/him a monetary bonus considering the higher engagement compared to the average ones of other Instagrammers with a similar amount of followers within the same country and industry. All in all, with this tool, now brands have the opportunity to know, thanks to certain metrics, how much an influencer should be paid, based not only on his/her number of followers, but also on the engagement rate, which as mentioned many times throughout this thesis, is one of the most important factor to know if an influencer engages enough with his/her audience. These analysis, combination and results answer my second research question, which was “How can brands measure the monetary value of a promoted post done by an U.S. Instagrammer within the fashion industry?”. For instance, thanks to the creation of the PPPP formula, which was validated through implementing real data of Instagrammers within the fashion industry, I can argue that now brands could be able to measure and know the monetary value of a promoted post, and thus start allocating budget for influencer marketing not basing it anymore on speculations or random information, but based on a real integration of data, which combined provide a rational suggested price.

8.0 Discussion This section is meant to provide a critical overview of this thesis findings and its implications. To briefly recap, the purpose of this thesis was to investigate the influencer marketing field in order to understand the reason behind its born and growth, its actual state, the theoretical framework around it and its practices. As stressed in the introduction and in the literature review, influencer marketing evolution of existing models and marketing strategies from a more traditional type of communication to a more native way of doing advertising, especially on social networks.

The core of this thesis was understanding the main issues that brands are facing at the moment in the influencer marketing field and the future challenges they want to take on. Knowing them, I thought how to solve those issues and help brands in optimizing the process of influencer identification for an influencer marketing campaign. The survey and the interviews conducted outlined that brands are mostly looking for a better way to identify the right influencer, especially in terms of budgeting and monetary rewards to give to the influencers. The data scraping, instead, showed the average engagement rate of 1,500 Instagrammers within the fashion industry in US giving a result of 2.3%. This number, as previously stated, is only generic and cannot be taken in consideration when a brand wants to calculate the price per promoted post of a specific Instagrammer; instead, the average engagement rate percentage of other Instagrammers with a similar amount of follower of the analyzed Instagrammer has to be used. The formula Pay Per Promoted Post, on the one hand, has been tested several times on tens of US fashion Instagrammers, giving mathematical correct results. On the other hand, though, in order to validate the outcome and see if brands could actually base their allocations of budget using this tool, I would need to have these results to be revised by influencer marketing experts. Moreover, although the data scraper and formula work correctly, there are a couple of things that should be improved in order to give to brands a more precise suggested price per promoted post. The first one is the different weight of likes and comments: in my formula I do not take in consideration the different value of a “like” and a “comment” but I only count them. With this I mean that a like, a social action that is easy to do since it takes only one second to perform it, cannot be compared in terms of the same value to a comment that requires a user’s thoughts and it takes more time to be completed. Said so, the formula should count, for example, a value of 1.0 for every comment and 0.5 for every like a photo received. The values 1.0 and 0.5 are only hypotheses that have to be calculated based on studies about the value of actions on social networks. The second discussion point regards the engagement rate: in my formula I only calculated the suggested price per promoted post as the results of a fixed rate (0.01 $) by number of followers and, in case the engagement rate of an Instagrammer was higher than the average engagement rate, I suggested to add a monetary bonus to add up at the total monetary reward. I did not write any rules in my formula, for instance, for the cases where the engagement rate of an Instagrammer is lower than the

average: in that case, as I thought that brands should offer a bonus for Instagrammer with a higher engagement rate, brands should give to that Instagrammer less money, since a low engagement rate could translate in low interest from her/his followers, meaning less sales or at least interest in buying the promoted product in future. Both those points have not be taken in consideration only for a matter of time lack. To conclude the discussion chapter, I can state that the scraper and formula created work but can be seen as a preliminary first version and that of course these can be improved, adding the main items previously cited, such as the weight differentiation between likes and comments. We could define the actual formula and tool as PPPP 1.0, which means Version 1, and the next formula, once improved, PPPP 2.0, which will be Version 2.

9.0 Conclusion In this thesis I raised the issue regarding the lack of information and budgeting structure for brands in the influencer marketing field. I focused my research on American Instagrammers within the fashion industry. I did it to find an average engagement rate among them in order to use it in a formula and a tool I created that has the aim of calculating how much should brands pay a specific influencer per promoted post. In fact, using my tool can help brands in better understanding how much to pay influencers and, thanks to that, allocate marketing budget in a proper way, without wasting money on vanity metrics, which have not any business value and are useless in terms of return of investment. First of all I investigated the topic on a qualitative level regarding the actual state of influencer marketing in order to understand issues and challenges of practitioners in the field. This allowed me to get an overview of the current situation of the problems that brands are facing and what they would like to see improved in the next year. After having this confirmed by experts in influencer marketing that Instagram is the most preferred social media channel for influencer marketing, I started scraping information such as number of followers and engagement rate of 1,500 Instagrammers. Thanks to data scraping and graph visualization, I found out that there is a correlation between increase of number of followers and

decrease in the engagement rate, confirming the experts opinion and data found in internet about micro and macro-influencers. Then, after a first generic scraping of all my sample of influencers, I tested my formula running it on several micro and macro-influencers in order to verify whether the price I got had sense or not. The tool, in fact, not only gives information about an Instagrammer such as amount of followers and engagement rate, but calculates a suggested price per promoted post of an Instagrammer (in my case only in US within the fashion industry) that brands should pay for. Finally, in order to answer my main problem formulation which was “How can a brand better identify the right influencer within the fashion industry in the U.S. for its influencer marketing campaign?”, after interviewing experts and analyzing the survey’s data, I was able to outline a 3-point guidelines to follow in order to better identify the right influencer – within the fashion industry in the US on Instagram – before starting an influencer marketing campaign: 1. Brand should look at the style and history of an Instagrammer. Context is crucial and it is important that the brand and the influencer have a solid and qualitative relationship. Brands should analyze the Instagrammer’s color palette, her/his main theme and previous campaigns with other brands 2. Brands should do not look only at the number of followers but analyze also the engagement rate, comparing it to the average engagement rate of similar Instagrammers with the same amount of followers within the same industry and country 3. Brands should calculate how much to pay an Instagrammer using the tool that returns the PPPP – Pay Per Promoted Post – in order to start a conversation with the influencer in terms of monetary reward based on data

Figure 35: the 3-point guidelines implemented in this thesis operational model

In bringing this thesis to a close, I provided a 3-point guidelines as shown in Figure n. 35 above, which includes also a tool to calculate how much brands should pay an influencer. These guidelines can help brands in better identify influencers on Instagram before starting an influencer marketing campaign, in order to get the best results possible and allocate the marketing budget properly. With these guidelines, I aimed to support and avoid the current challenges and issues that practitioners are seeing within the influencer marketing field and hopefully provide to brands more structured suggestions on how to work with influencers from now on.

10.0 Legal issues and ethical questions Since online reviews and opinions are such an important factor in the decision making process for the consumers – as a BrightLocal local consumer review survey showed in 2014 (BrightLocal, 2014) - it is important to open a parenthesis on an even more important discussion point, which is how to properly disclose a sponsored post done by an influencer. For instance, the FTC (Federal Trade Commission) wrote guidelines under its “FTC’s endorsements guides” (FTC, 2015) on when an influencer needs to disclose that a post or video is sponsored and how this should be done. In this document, the Federal Trade Commission states that on social

media all the influencers that promote a content have to clearly explain to their followers that is a paid post adding to their content keywords such as “#ad”, “#sponsored”, “#promotion”, “#promoted”. In March 2015, Lord & Taylor, a clothes brand, launched through a social media campaign its new collection and involved 50 influencers on Instagram, paying them between $1,000 and $4,000 to post a photo of themselves wearing a Paisley Asymmetrical Dress. The brand asked the influencers to tag the company on Instagram but it did not say to openly disclose the partnership. Since the influencers did not put any hashtag that clearly showed that was a sponsored post, FTC moved a legal action against the brand for lack of disclosure and clear communication to the influencers’ followers.13 The need of a regulamentation and a critical ethical consideration is crucial for every new form of marketing (Murphy, 2010) and FTC is already structurizing it for the influencer marketing field. In fact, this is essential because, as we previously saw in the theoretical framework, users that view a promoted post can be influenced and brought to a sale; for this reason it is important that the influencer clearly states when she/he is promoting a product as a form of deontological consideration towards her/his followers that trust her/him acting as opinion leader.

11.0 Future perspectives The formula and data scraper I created are not only theoretical concepts to base an influencer analysis, but a real tool that brands can use to identify the right influencer for an influencer marketing campaign. For this reason, my goal is to improve the data scraper and the formula and publish it online as a Software-as-a-Service (SaaS) with a freemium model. This means that everyone can access and try it, but after a certain amount of searches, the user will need to upgrade to a monthly payment in order to access the data. In order to create a SaaS, the first step will be the beta-testing. With beta-testing is meant the process of find tester to try the tool and get feedbacks from them so I will be able to improve it and be ready for a first public version of it. For instance, as I stated in the discussion chapter, my PPPP formula should now be validated by practitioners. Only after the beta-testing and having fixed possible issues 13

R etrieved from https://www.ftc.gov/news-events/press-releases/2016/03/lord-taylor-settles-ftc-charges-it-deceived-consumers-throug h

reported from the testers, I will be able to present it to the public, focusing mostly on brands and influencer marketing agencies. Brands and agencies will be able to pay a monthly fee and have access not only to the PPPP tool, but also to historical data that, month by month, the server will constantly obtain using the scraper which will work 24/7.

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19. Pathak, S. (2016, May 12). Confessions of a social media exec on influencer marketing: ‘We threw too much money at them’ [Blog post] Retrieved from https://digiday.com/marketing/confessions-social-media-exec-no-idea-pay-influencers/ 20. Willett, M. (2016, May 18). A war is brewing between brands and the social media 'influencers' they pay [Blog post] Retrieved from http://www.businessinsider.com/how-much-do-influencers-get-paid-2016-5 21. Barker, S. (2016, September 6). Influencer Marketing: The Beginner’s Guide To Micro-Influencers [Blog post] Retrieved from https://www.hostgator.com/blog/influencer-marketing-the-beginners-guide-to-micro-influe ncers/ 22. Boyd, S. (2016, January 28). How Instagram Micro-Influencers Are Changing Your Mind One Sponsored Post at a Time [Online article] Retrieved from https://www.forbes.com/sites/sboyd/2016/06/28/how-instagram-micro-influencers-are-c hanging-your-mind-one-sponsored-post-at-a-time/ 23. Smith, K. (2016, August 11). Marketing with Micro-Influencers: Engagement, Relevance and Authenticity [Blog post] Retrieved from https://www.brandwatch.com/blog/marketing-micro-influencers/ 24. Mathews, C. (2016, October 21). WHAT ARE MICRO INFLUENCERS AND HOW TO USE THEM TO REACH YOUR AUDIENCE [Blog post] Retrieved from http://www.rocksdigital.com/micro-influencers/ 25. Adams, N. (2016, June 16). MICRO INFLUENCERS VS. MACRO INFLUENCERS [Linkedin Post] Retrieved from https://www.linkedin.com/pulse/micro-influencers-vs-macro-nicole-adams 26. Rouse, M. (2016, May 11). What is a Software-as-a-Service [Blog post] Retrieved from http://searchcloudcomputing.techtarget.com/definition/Software-as-a-Service 27. Desreumaux, G. (2015, November 17). Instagram Is Now The Most Influential Social Marketing Platform [Blog post] Retrieved from http://wersm.com/instagram-is-now-the-most-influential-social-marketing-platform/

28. Gilliland, N. (2016, November 29). What are the most effective channels for influencer marketing? [Blog post] Retrieved from https://econsultancy.com/blog/68566-what-are-the-most-effective-channels-for-influencermarketing/ 29. Adotas (2013, March 19). Study: 86% Of Consumers Suffer From Banner Blindness [Blog post] Retrieved from http://www.adotas.com/2013/03/study-86-of-consumers-suffer-from-banner-blindness/ 30. Blake, F. (2016, March 28). INFLUENCER MARKETING (WITH KRISTY SAMMIS) [Blog post] http://www.halfhourintern.com/careers/influencer-marketing 31. Rouse, M. (2014, September). What is a search operator? [Blog post] Retrieved from http://whatis.techtarget.com/definition/search-operator 32. My Market Research Method (2011, October 27). Primary vs. Secondary Market Research: What’s the Difference? [Blog post] Retrieved from http://www.mymarketresearchmethods.com/primary-secondary-market-research-difference / 33. Cohen, D. (2015, July 29). 2Q Benchmarks for Facebook, Instagram, Twitter (Infographic) [Blog post] Retrieved from http://www.adweek.com/digital/quintly-2q-benchmarks-facebook-instagram-twitter-infogra phic/ 34. AdWeek (2016, April 4). Here’s How Many People Are on Facebook, Instagram, Twitter and Other Big Social Networks [Blog post] Retrieved from http://www.adweek.com/digital/heres-how-many-people-are-on-facebook-instagram-twitte r-other-big-social-networks/ 35. Buryan, M. (2016, September 19). Why Fashion Brands Are Thriving on Instagram [Blog post] Retrieved from https://www.socialbakers.com/blog/2626-why-fashion-brands-are-thriving-on-instagram 36. Mediakix (2016, July 21). DOES YOUR ENGAGEMENT RATE MEASURE UP TO INSTAGRAM’S BEST BRANDS? [Blog post] Retrieved from http://mediakix.com/2016/06/best-brands-instagram-engagement-rates-case-study/

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Appendices Translated interview with Call The Tune (originally in Italian): So, first of all I’d like to start asking you about Instagram and see if it is a good idea to focus on it. It seems to be the best channel for influencer marketing, do you agree? If yes, why? Totally agree. The industries that work the best on Instagram are beauty, makeup and fashion. Although Facebook has more profiled information about users, Instagram is more direct and easy to use and for these reasons a lot of brands invest in it. We interviewed our 20,000 partner influencers and they told us that it’s their favourite channel. Instagram has a more meritocratic algorithm compared to Faceook, whereas nowadays you have to pay to get enough reach. So yes, Instagram is the best social media, especially for videos. Data say that an Instagrammer that publishes a video can get 10X in terms of engagement compared to when posts a photo. And what about the average engagement rate on Instagram? Is a crucial factor, isn’t it? I see that online data states that average engagement rate on Instagram is around 3%. Do you confirm this data? And what can you add about it? Yes, absolutely, in the moment we refer to micro-influencers with a maximum of 100,000 followers, then the engagement rate decreases a lot. I’d like to add that now the trend is all about micro-influencers, but then if you have 60,000 followers and only 200 likes, however you are a micro-influencer, your engagement rate is still low and not valuable for a brand. Ok so this was about micro, but what about macro? Why macro-influencers have an engagement rate lower than micro-influencers? Mostly because the more followers a macro-influencers has, the more these will be generic and without the same niche interests. So this will bring to a lower engagement rate since not all the followers will be interested in a certain post. Imagine an Instagrammer with 5 million of followers: a lot of them can be inactive or access to Instagram only few times a month and don’t interact too much. Sometimes macro-influencers are followed just because they are famous and not for real interest from the follower. Some people just follow VIPs and celebrities on the social media because everyone does that but doesn’t necessarily means that then you are interested in that macro-influencer and you could never interact with him/her in future.

Great. So, if we move the conversation a bit from numbers to a more qualitative point of view, how much is important the context in influencer marketing? It’s fundamental. One of our Instagrammer collaborates with only two brands and every week publishes quality contents on her Instagram with a good storytelling and a main theme in terms of style and in fact her photos bring all the time good results, this because is the right context and is a work done with precision with love for each promoted post. Is not enough receive a box from a brand and review it online without even thinking or knowing well the brand identify. The interview is almost over, which are in your opinion the biggest issues that brands are facing at the moment in the influencer marketing field? The problem about the context that I have already told you for sure. Also in terms of correlation between the brand’s goals and the platform used. For example, if the goal of an online campaign is to sale online a product, Instagram is not the best social media because there is not yet the possibility to insert a link to directly buy the product and so for this reason is not easy to track the results of that campaign. Then the second issue is the pricing: a lot of influencers that have tons of followers are exploiting this situation and asking more money than how much they should actually ask, this is because they are in charge now. A lot of companies still live in the era of vanity metrics and look only at factors such as the number of followers or total reach without looking at other metrics, for example the engagement rate, so a lot of influencers just ask more money also if they shouldn’t buy they can do it because brands don’t even have any comparison to know how much they should give them. And the two biggest challenge for influencer marketing? Bring more information about which investments brands should to do and how. But not general information but also a technical point of view that give a less “romantic” approach to influencer marketing and more data-driven taking in consideration goals and budgets. In fact if brands continue to invest in influencers that ask more money than what they would deserve and don’t see enough results in time, they will not invest anymore in influencer marketing. Ok, interesting, so this is linked in some way to the actual information lack you were referring previously, correct? Yes, that’s right, that issue actually brings to the first challenge I just told you. For what concerns the second challenge, I think is the link between sales and influencer marketing and explain to the brands that those two

things are not necessarily linked. Influencer marketing is supposed to influence, not to directly sell products. So the most important thing is that influencers show the brand product and in some way influence the followers in generate interest and word of mouth, then the sale process is secondary and should not seen as the only goal of the campaign. So the sale step is not important? No, I don’t mean that. I mean that brands cannot only look at the direct sales from a specific campaign, for example tracking a specific link, but that they have to take in consideration that a campaign can brings to sale not the same day but maybe days or weeks later. Ok so what about the ROI, is it possible to calculate it in influencer marketing? It is really difficult to say. In our experience with Candy Crush on Facebook we were able to see a return on investment in terms of signups and sales thanks to a quantitative analysis on the adv dashboard. Knowing that one was the only active campaign it was easy to monitor the conversions. More complicated is when a brand has more than one active campaign on different channels: in that moment, at the end of the campaign, is not easy to attribute sales to a certain influencer. For example, in some cases some Instagrammer’s followers couldn’t like a picture posted from the influencer but then they could buy the clothes promoted in it, this unfortunately is impossible to monitor.

Interview with Influencer Marketing Hub: Ok, let’s start with the first question about Instagram: this social media seems to be the best channel for influencer marketing, do you agree? If yes, why? Yes it is, in fact the majority of the brands are investing in it. Our articles about Instagram and influencer marketing are the most read and shared. Is a social media easy to use, direct and great to show your interests. Way better than Facebook or Twitter. This is why brands are investing in it, not only buying advertisement but paying influencer to promote their product. Sure. So on Instagram there are both micro and macro-influencer. Can you explain me why macro-influencers have an engagement rate lower than micro-influencers?

You have to think about the law of large numbers: the more people will follow an Instagrammer, the bigger can be the number of inactive users, also called ghost users. Imagine a macro-influencers with one million of followers: it is easy to guess that a lot of them will be inactive. Ok so what happens if you have a lot of ghost followers? Well, it negatively affects your engagement rate, of course. For both micro and macro influencers brands cannot only take in consideration numbers but also context, is this correct? If yes, why? And how much it is important? Fundamental. Context should come before the product. Actually is must come before the product. The influencer have to be relevant to the brand’s niche market and can’t just randomly promote something because is paid, it doesn’t work like that. I mean he/she can, but will be a short-term strategy, I can guarantee you.

Thanks, and what about the two biggest issue that in your opinion influencer marketing is facing at the moment? Well, first of all the pricing structure. Now is the chaos. Prices are based on assumptions and no one control them. It is mostly an anarchic situation. I mean, influencers ask to brands what they think is fair based sometimes on previous work with other brands, sometimes just on what thei perceive is fair on assumptions. But in this way brands have not enough data to decide if the price is fair or not and so they just believe the influencer and start negotiating based on the amount starting price. And what about the second issue? Lack of information: we at influencer marketing hub work exactly on giving to brands and practitioners articles, infographic, data and tutorials to understand better how this game works. For example a lot of the times brands to don’t analyze correctly the marketing metrics but still look at vanity metrics such as number of followers of an Instagrammer that is clearly not enough to validate the quality of an influencer.

Ok, last question: what about the to biggest challenges for influencer marketing for the next 12 months? As I was saying before, more information about what influencer marketing is and its potential. We give to micro-influencers and brands a lot of resources about influencer marketing, so that they can get tips and best practices to make a structure out of it and optimize the work. And for what concerns the second challenges is

linked to what I was saying previously regarding the pricing: is crucial to give a structure to the influencer marketing economy. There’s not historical reference or any data about it. No one know how much you should pay an influencer and this is giving a lot of troubles to marketing departments during the budgeting process. This can affect negatively also in terms of relationship between brand and influencer and also towards to influencer marketing in general.

Survey created with TypeForm An extract of the quantitative survey created with TypeForm visible in Figure A1: Figure A1: an highlight on the first three questions of the survey