Research that sparks

Introduction

Shifting consumer habits It was 1876 and Alexander Graham Bell was pitching his start-up. He offered Western Union his telephone technology for a rumored $100,000. The company dismissed it as “an electrical toy” (Anderson,2005).

“Technically, we do not see that this device will be ever capable of sending recognizable speech…

Messer Hubbard and Bell want to install one of their “telephone devices” in every city. The idea is idiotic…

Furthermore, why would any person want to use this ungainly and impractical device when he can send a messenger to the telegraph office…”

The quote, although recently challenged for its authenticity, is an accurate reflection of the factors

that drive product adoption. What is recognizable speech if not product readiness, telephone devices in every city, a means of distribution and the question of why anyone would use it - that of shifting consumer habits?

Fast forward 130 years and the questions are the same about video communications. Video communications are nothing new. The goal of making it easier to see the person you’re talking to is a consistent theme in telephony. And yet by far the fastest growing communication method in the last 50 years has been short, asynchronous text messaging, with WhatsApp alone generating 18.3 trillion messages annually and an aggregated SMS volume at 8.16 trillion (Portio Research, 2013). So why is

video communication not mainstream yet and what can we do to accelerate its adoption?

‘My Life in Video’ The Comms Services team at Telefonica decided to set up a study to uncover opportunities in

consumer video communication. We tackled the challenge on video communication by setting up a Consumer Consulting Board. A Consumer Consulting Board is a small group of highly-engaged consumers, connected online for a longer period and systematically engaged to take part in research challenges (Willems, Schillewaert and De Ruyck, 2013). For the ‘My Life in Video’

project, we engaged 65 consumers from the UK and Mexico, each in a Consumer Consulting Board of their own language.

Through ethnography tasks on their communication habits, we collected 957 contributions in two weeks’ time for the project. But disruptive innovations

are difficult to research and the challenge is twofold.

The Challenge

1.

Consumers have a hard time imagining how innovations will influence their lives. Most likely, if we would have set up market research in Graham Bell’s era, the results would not have predicted the future success of the telephone. Likewise, we can of course ask consumers to report on their video consumer communication, but will this lead to useful angles to change

future communication patterns?

2.

The future will need to be created by marketers and product managers at the client side. As it is for consumers, for them also a crucial aspect for this long-term change is the ability to IMAGINE an improved future state (Carleton, Cockayne and Tahvanainen, 2013). Like an athlete, if employees can imagine winning the race, you will increase your chances to realize the outcome that you want.

The reality however is that we often miss this stakeholder

involvement and willingness to act upon the insights. A recent study among 184 consumer insight managers and researchers showed the most important criterion for impactful research is that it should change the attitudes and decisions of marketing executives. The same study revealed that especially on this matter, we still have a long way to go. We conduct great research but are often unable to ignite the spark that engages, inspires and drives action. How can we

better activate our insights within organizations?

Looking at the challenges above, it was clear that we were in

need for inspirational research and research that inspires in an equal matter. During our journey with the ‘My Life in Video’ project, we tried to create a recipe for research that has that spark. We decided to put some common research beliefs when it comes to gathering consumer insights to the test. By investigating what we will further call in this paper ‘research myths’, we aimed to discover best practices on how to best

generate new consumer insights that can serve a springboard for innovation and brand activation.

Myth

#1

Research is about solving problems

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Research is about solving problems If we would ask research practitioners to describe the business we are in, many of them would claim that we help marketers and consumer insights managers to solve a marketing challenge. During the proposal stage and in the kick-off meeting, our client explains

their challenge as detailed as possible and in the subsequent stages, we formulate an answer on the stated problem based on research data.

But are we really in the business of problem

solving?

Recent thinking coming from a world that is completely different from research but breathes inspiration and creativity (being the world of art), suggests that our focus on problem solving

is limiting us to create inspirational research. In his latest book, Pink (2012) describes the following experiment explaining why:

“In the 60’s, social scientists Jacob Getzels and Mihaly Csikszentmihalyi recruited three dozen fourth-year art students for an experiment. They brought the young artists into a studio with two large tables. The first table displayed 27 eclectic objects that the school used in its drawing classes. The students were instructed to select one or more objects, then arrange a still life on the second table and draw it.What happened next reveals an essential pattern about how creativity works: The young artists approached their task in two distinct ways. Some examined relatively few objects, outlined their idea swiftly, and moved quickly to draw their still life. Others took their time. They handled more objects, turned them this way and that, rearranged them several times, and needed much longer to complete the drawing. As Csikszentmihalyi saw it, the first group was trying to solve a problem: How can I produce a good drawing? The second was trying to find a problem: What good drawing can I produce? As Csikszentmihalyi then assembled a group of art experts to evaluate the resulting works, he found that the problemfinders’ drawings had been ranked much higher in creativity than the problem-solvers’.

Ten years later, the researchers tracked down these art students, who at that point were working for a living, and found that about half had left the art world, while the other half had gone on to become professional artists. That latter group was composed almost entirely of problem-finders. Another decade later, the researchers checked in again and discovered that the problem-finders were “significantly more successful — by the standards of the artistic community — than their peers. Getzels concluded: It is in fact the discovery and creation of problems rather than any superior knowledge, technical skill, or craftsmanship that often sets the creative person apart from others in his field.”

The parallel with our research world is obvious: we are so focused on solving the

research problem that we forget about problem creation. Often we cannot be inspirational because we did not understand sufficiently what would create this positive disruption among the users of research. We are experts in doing research with consumers, but we forget to research our client!

Better problem creation So how can we engage in better problem creation? Let me start by saying that it will not be

If we want research to be more impactful, we should not think in silos; we rather need to know how the

easy. When it comes to generating insights, most clients would agree that they are looking into research to detect something they did not know before. This implies that they can tell you what they already know, but are unable to tell you what they don’t know. The latter is often the problem. In addition, several internal stakeholders can be spread across countries, making it harder to collect all relevant information needs.

research fits within the strategic focus of the company.In the ‘My Life in Video’ project, we

Fig 1. Mind-mapping tool

decided to engage in problem creation by engaging Telefonica employees in a mind map exercise (Fig 1). Several people in the company got access to an online portal where they were asked to collaborate with their colleagues in a couple of challenges helping us to clarify the research goals. The challenges could generally be divided into two buckets. The first was to capture current knowledge of video consumer communication. Telefonica Comms Services employees could for example add their own predictions to the outcome of the research or create archetypes of the current and future users of digital and video communication. The second challenge set was focused on how this project could lead to action. People were asked for example to describe how they could use this project in their daily work or how they could engage in a collective SWOT analysis.

So, did our time spent on problem creation pay off?

1.

To start with, a total of 37 employees took part in the mind-mapping exercise, adding 253 relevant entries to the collaboration tool. This number exceeds normal participation in a kick-off meeting meaning that this approach lead to an

2.

increased internal buy-in for the study even before starting.

It helped us identify common beliefs in the organization and spot polarized opinions that would allow us to create a positive disruption with the research.

At the reporting stage, we were therefore able to contrast internal perceptions on certain consumer topics with the findings. For example, one of the deliverables that the research lead to was the development of needs-based segmentation. Upfront in the mind-mapping exercise, we asked Telefonica Comms employees to describe current and future users and nonusers of video communication. Based on the input of the mind map, we created a first set of personas – existing only in the head of the employees prior to the research. When our Consumer Consulting Boards were finished, we compared them with the segments based on the research data highlighting gaps and similarities with previous thinking.

3.

The additional research stage helped us make the research more impactful by focusing on the right topics from the start. We decided to adapt the initial conversation guide by adding 3 new topics and fine-tuning 7 of the existing topics. It also helped us to narrow down our gaze during analysis focusing on those consumer stories that were most relevant for the different internal stakeholders. Overall, we did not just decide to answer research questions put forward at the start of the research, but extended our scope. Upon presentation, our study appeared to be a hit because it did NOT give answers. It was powerful because it helped the organization to raise the

right strategic questions. An example: one of the outcomes of the research was that in a world where consumer privacy is often neglected, Telecom providers are perceived by consumers as taking privacy and data security seriously. This made Telefonica Comms Services pursue this message in marketing communications.

Overall, we can conclude that research is only partial about problem solving.

Problem creation is equally important and deserves more attention!

Myth

#2

Big data leads to big insights

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Big data lead to big insights?

When looking at the research industry, we have focused predominantly on collecting data. In our struggle to engage consumers in research, we have invested in new research techniques such as

research communities, mobile surveys and social media data harvesting. Today, we can even add tons of behavioral data to that package.

We talk about ‘big data’ where we try to interconnect different sources into enormous data ecosystems. But has our focus on more data truly increased our chances of finding golden nuggets? In order to investigate this research belief, it is important to make a distinction between data

What is important is that it is objective. It contains no judgment or explanation and is free from feeling or thoughts. Observations need an interpretation before you can turn them into insights (Fig 2). An insight is an

understanding of the inner nature of things, leading to a discovery of something that is not obvious yet but at the same time recognizable and real, providing the basis for actionable marketing decisions, ultimately leading to competitive advantage (Verhaeghe et al., 2013).

and insights. When we talk about data we refer to factual observations that can come from many sources. It can be a percentage found in quantitative research, a consumer quote originating from in-depth interviews, a picture uploaded in an ethnography study, a type of complaint received most frequently by the customer care center, a clickthrough rate on your website, etc.

Fig 2. The process of turning data into insights

Big = Meaningful + Noise The ultimate question to research this myth is the extent to which a lot of data also lead to more meaningful observations or can only be considered as more noise. We decided to put the data we had collected for the ‘My Life in Video’ project to the test by analyzing to what extent each of the 957 posts truly contributed to

finding new insights by giving them a rating from 1 to 5. We came to the following conclusions:

1.

55% of our data could be considered as noise (obtaining a 1 or 2 out of 5 score).

They consisted of three types of contributions: a minority were posts that were off-topic.

Next, we had a set of conversations that needed to ensure the smooth functioning of the Consumer Consulting Board but did not immediately contribute to any results. This could be a conversation in the social lounge or questions from participants on how to handle a certain task. A substantial part of the posts however did not add anything interesting to use for further ‘insighting’. They were typically posts that were a description of communication that did not reveal any clues on the ‘why’ behind the behavior (e.g. ‘My last video communication was with my mother on Sunday using FaceTime’) or posts that described well-known communication facts (‘I feel laptop is better than mobile as part of video communication because the laptop screen is big and much clearer than mobile’).

They were also dominantly neutral in sentiment. It was not that the participants necessarily did a bad job in participating, but the input they provided did not immediately help us with our research challenge. As results only 45% of the contributions

helped in shaping the final insights we found on the adoption of video communication and hence could be considered as meaningful. It meant that at least one insight that made it to the final report was based on this observation.

2.

With only 28% of all posts made in the ‘My Life in Video’ project, we would have obtained exactly the same results. The difference between a rating 3, 4 or 5 was based on the uniqueness of the contributions taking similar criteria into account that were put forward by Weger and Canary (2010). The 5-star rating was most valuable since it meant that this post lead to the discovery of an insight that we did not encounter before in the community. Only 13% of the posts met this ‘freshness’ criterion. A post obtained a 4 out of 5 if it helped further refining an insight that we already built based on previous posts. 15% of the posts belonged to that bucket. The 3 out of 5 ratings were posts that were a pure repetition of what had been set before. It did add to building the final insights, but since many people in the community already reported this before, our final report would not have been different if this contribution was not there. They encompassed 17% of the posts.

Our results show that even in a set of data which cannot even be considered as big (‘only’ 957 posts), we already have a lot of ‘waste’. This illustrates the power of even one single observation to come to a powerful insight (Willems, Schillewaert and De Ruyck, 2013).

Although future benchmarking with other studies is needed, we do not believe that the

results in the ‘My Life in Video’ project are exceptional in any kind. Moreover, we realize that this analysis is not a proof that recent big data approaches cannot lead to big insights. We would however like to make a case for small data with less noise or duplicates.

Having a lot of data is neither the Holy Grail for insight detection nor a guarantee for impactful research. Our focus should be on getting more meaningful data that helps

us to really make a change.

Myth

#3

Only expert users can help us detect insights

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Expert users vs. engaged participants It is a common belief that advanced users of

a product can help us detect more unusual use cases (Von Hippel, 1986 and 2005). Since they have a more in-depth experience with the topic and often are early adopters, they can teach us a lot about which needs new innovations fulfil. Alternatively, one could argue that it does not matter whether a person is an ‘expert user’ or not, as long as he or she is engaged in the project. In this case, this would mean that getting more

meaningful data is a matter of getting people to post more often on different topics and put more effort into longer posts.

Although all participants in the community had an affinity with the topic (Willems, Schillewaert and De Ruyck, 2013), there was considerable variation in the extent to which they already used digital and video communication. Therefore we decided to

check if more relevant posts came from more advanced users of digital and video communication or if participant engagement factors like average post length or total number of contributions were more determining.

The general linear model we created based on the data (Fig 3) appeared to be significant, with a predictive power of 76%. Only two of our determinants were significant: the average post length and the total number of contributions to the project. Those were the two key parameters describing participant engagement in the project. This means that participants who are more engaged in the project, also posted information that leads to insights more often. We did not find any

significant effect of expertise with digital or video communication. Our results suggest that a good insight can come from anybody as long as you get them engaged. We need to create the right conditions to get people involved because our analysis shows that engaged people will make more relevant contributions!

Fig 3: General linear model explaining which factor in a Consumer Consulting Board contributes to insight detection Post relevance = percentage of posts from one participant that have a 4- or 5-star rating Average length = average character length of posts from one participant Number of topics = number of topics or research challenges a participant took part in Usage of digital communication = degree to which a participant is a light or advanced digital communication user Usage of video communication = degree to which a participant is a light or advanced video communication user

This conclusion was also confirmed by looking at the relevance of posts over the lifetime of the community, we could observe a pattern of peaks of ‘relevant posts’ over time in both communities (see Fig 4 for an example in Mexico). Analysis of the peaks revealed that they typically appeared one

Fig 4: Relevance (percentage 4- and 5-star ratings) over time in the Mexican ‘My Life in Video’ community

day after giving new research challenges to participants meaning that burst of ‘meaningfulness’ can

be obtained by stimulating our participants to think harder and better. Overall, our results show that any consumers can contribute as long as they are triggered in the right way. Again, we do not claim that using extreme users in research does not have any value. It is just not a necessary condition to find powerful insights!

Myth

#4

The best way to find insights is by probing current behavior

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Bringing our participants outside their comfort zone A standard approach to find insights is to invite the participant ‘on the Freudian couch’ and stimulate them to reflect on

their latent needs and desires. In the ‘My Life in Video’ project, this meant that we would ask people to report and reflect on their daily communication means. One can wonder if studying only current consumer behavior will not only lead to discovering what is already known. An additional pitfall of this approach is that you do not learn much about how to break away from habits.

Moreover, in typical ethnographic or indepth interview settings, we can only

collect information on communication habits that people remember at the moment of the research, so gathered in a specific context and mood.

We belief that one way to get more diverse data is by NOT investigating current

consumer behavior, but by bringing our participants outside their comfort zone. This could be done by engaging them in activities they are not used to and by allowing them to take part in research in different contexts. We tested the potential of this approach within the ‘My Life in

we also applied activation tasks where consumers were, for example, asked to place video calls as replacement of other ways of digital communication than they were used to. This way we hoped to learn more on speeding up the

adoption of video communications.

Video’ project by introducing mobile only ‘do it now’ tasks. At certain moments during the fieldwork, consumers got a challenge they had to complete within a limited time frame. By putting them under time pressure and enabling the challenge with mobile, they were stimulated to report

about their communication habits in a different context than they would usually do. Next to asking them to report on their daily communication habits in the heat of the moment,

Fig 5: Example ‘do it now’ task

The ‘do it now’ tasks proved to be very successful in obtaining more diversified data. When comparing the number of tags to a certain post, the ‘do it now’ tasks obtained 36% new tags that did not pop up in the other research challenges. People reported using more communication devices and alternative goals for the communication that were not mentioned before. Qualitative analysis clearly indicated that the heat of the moment consumer feedback often lead to a less staged

representation of consumer behavior.

Example: in one of the tasks consumers were asked to describe a typical day in their life. As shown in Fig 6, they typically reported

aspects they did not think of before such as playing with the cat or oversleeping. Being in the right context stimulated participants to report different things than they would otherwise do.

Fig 6: Example ‘day in my life’ task obtained through ‘do it now’ tasks

We found that the activation tasks that

Our findings suggest that insight generation is best

challenged consumers to do something outside of their comfort zone lead to meaningful contributions that were not discovered before. They basically triggered

done by exploring different consumer contexts preferable also outside normal consumer behavior. We do not claim that we should abandon

participants to imagine a potential future with video communication by experiencing it first hand, which helped them realize which barriers or triggers would help them adopt this technology more rapidly. Example: one of the British participants reported on having videocalled with his friend during an actual Chelsea football game to experience the game together, yet still apart. During the experience only did he realize that one barrier for this

specific usage of video communication for him was the level of concentration: he had a hard time focusing on the game and having visual input from his friend.

classic approaches towards ethnography but we should at least strive for more diversity on what we do with our participants.

Myth

#5

Only researchers can turn data into insights

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Participant as co-researcher?

Despite more empowered methodologies of doing research, getting insights out of the

data is still an exclusive job for the researcher. Our participants provide us with

Moreover, maybe they would come up with different interpretations and insights by looking at the same reality with their own individual perspective. We decided to set

data and it is up to the researcher to decide which data are meaningful and to turn them into insights. But what if we would allow

up a separate condition where participants could do the observation in groups. They got similar challenges as

participants to help us out with this process? If we would explain upfront to

other participants in the research, but were asked to build further on each other’s observations. They were stimulated to add conclusions based on what they observed in their environment and not just to give feedback on their own habits. In addition, we

participants as co-researcher what we are looking for, we could maybe get a reduced amount of noise and more meaningful data.

Moreover, if we would ask consumers not only to report on their own behavior, but also on what they observe among others, we include not only communication habits from people who are willing to take part in research, but also observations from people who are less easy to recruit for online ethnography (such as the elderly or people who are more reluctant towards using digital communication in general).

provided them with a framework to both report meaningful observations and make interpretations.

What’s the result?

The networked communication lead to almost half of the amount of data in comparison with the individual sessions. What is important however is that we obtained the same richness: by using the power of the crowd

to observe their environment, we discovered exactly the same amount of relevant data as in the individual condition, but with a lot less effort. For the moderator, it was easier to moderate the group observation than to dig into all the individual blogs. Moreover, we had to digest far less data during analysis. Hence, by involving consumers as co-researchers, we could reduce the noise versus signal data ratio significantly.

It is important nonetheless to mention that success depended largely on the country. In Mexico the networked observation worked significantly better than in the UK. Participants were really building on each other’s conclusions, whereas in the UK community people often kept on adding similar observations. Although

further research is required to clarify the parameters to make group observation a success, we have two theories:

Firstly, when looking for example at Hofstede (Hofstede, n.d.) dimensions describing cultural differences in values, we learn that the Mexican culture is far more oriented towards collectivism than the British culture - which is more individualistic. This orientation could entail that

the social condition of group observation suits Mexican participants better than the individual reporting mode. A second explanation can be found in the group dynamics. The British group was characterized by fewer interactions between community members.

Fig 7: Evolving group dynamics in the Mexican group

They mainly interacted with the moderator but the social glue was difficult to increase. The Mexican community by contrast showed much more collaboration between members. One

explanation for the different dynamics might be the different motivation of participants in the target countries to take part in the consumer consulting board (Deci and Ryan, 1985). We noticed from the start that the Mexican group was dominated by participants who like to socialize or find it important to show their topic expertise to the others, whereas the UK group consisted of participants interested in new communication technologies. The more outerdirected participants (socially or reputation motivated) in Mexico made efforts to really collaborate with each other, especially at the beginning of the community. They used the

knowledge of the more topic-directed community members to increase the strength of the group instead of their individual postings (see Fig 7).

Our results suggest that having outer-oriented

participants is an important condition to get group observations started. They form the necessary social glue between participants. Our results show that a more in-depth collaboration with consumers where we make them an ‘insider’ in turning data into insights is definitely beneficial. We must admit however that this myth is not completely busted. Although we found a more efficient way of finding meaningful data, our approach did not lead

to new insights in comparison with the benchmark. Moreover, actually turning the data into insights could not be taken over by consumers. They were powerful companions in pointing out where to put our attention and helped out to give potential interpretations but did not deliver us insights ready for our report.

Myth

#6

Our work is done when we present the results

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Inside-out vs outside-in Market researchers often see their role within an organization merely as a facilitator between the business and the external agency. They facilitate the selection of a vendor, manage the project and deliver the report at the end of the research. In contrast to this vision, we would like to claim that the research only really starts once the

results have been presented. As mentioned before, even when we involve stakeholders in problem creation or use approaches to get more meaningful data, there is still a huge challenge

to create an impact from that research. It is therefore crucial to have an internal champion on the client side that helps to change the culture of an organization from one that thinks inside-out to one that has an outside-in vision.

Within the ‘My Life in Video’ project we were lucky to have this kind of ‘chief consumer

officer’ (De Ruyck, 2014) whose role is to activate peer employees to take relevant action.

How was this achieved? To begin with, as in contemporary marketing, careful content planning that takes the needs of different departments into consideration was mandatory. Therefore the initial research report was ‘translated’ in four different ways: Rich

A report containing all details on the research was passed on to researchers in the company.

Those people also got the chance to access the research community and see some of the

participant contributions first hand.

Analyzed

The product owners within the Telefonica group got a distilled version where the implication of the research for their specific technology or product was highlighted.

Condensed

Condensed reporting was foreseen for management highlighting strategic challenges that were put forward based on the research.

Popularized

General interest for the research was evoked by creating some more digestible information that was made available for the entire organization. For example, an infographic was created to visualize key results and generate additional interest for the research on a larger scale.

Next we tried to bring the consumer into the hearts of employees by organizing an event where

consumers and employees of Telefonica Digital could meet in real life. As a marketer or product manager, it is easy to lose track of consumer reality. Despite research results, we often make decisions based on ourselves as consumers or on people around us. Organizing a physical meet up with the

research participants might help to get people out of that ivory tower. Through several sessions, product managers had the chance to share with the participants the innovations they had been working on and also to get some firsthand feedback. Afterwards a speed-dating session was organized between consumers and product owners to elaborate on the research and product info sessions. This speed dating allowed for more informal contact between the employees and the consumers.

As mentioned before, evangelizing the research

results is a continuous process. At this very moment, when writing this paper, the following impact of the work of our consumer chief officer could be observed:

1.

The different formats of presenting the research made it possible for the outcome of the research to find its way to a larger number of internal teams than usual. The constant work of our internal ambassador also meant that months after the research had been conducted, the news on ‘have you heard about the consumer video research’ was still spreading and inbound requests from other parts of the organization found its way to the insight department as a result. On top of the mileage Telefonica Comms Services got out of the research, some ‘power slides’

from the final report started circulating in product presentations. We learned that slides that went viral often contained insights that helped make existing presentations more credible. The voice of the consumer was therefore used to support and leverage internal ideas.

2.

We were not only able to change the minds but also the hearts of the

Telefonica Comms Services team. Especially the offline consumer event created a positive disruption with key stakeholders. Telefonica Comms Services employees work in a cocoon of technological inspiration. They get confronted

on a daily base with the newest and most thought provoking innovations. For them, attending the consumer event was a reality check: they were confronted with the fact that the technical understanding of consumers on how communication works was far more limited than they anticipated. Despite the research report that supported these findings, hearing a consumer paraphrasing certain key conclusions in his or her own words appeared to be so much more powerful to evoke that mental shift.

3.

Our research did not really impact how the technological side of the video communication products Telefonica Comms Services will evolve. This is where the role of the expert at Telefonica Digital lays. The research had a direct impact on fine-tuning future video communication offerings. Our work piece

is being used to help better position the different video communication products to consumers. As such, it had not only changed the hearts and minds of employees but it also triggered action.

Creating research that sparks

Despite the fact that as an industry we are experts in finding new consumer insights, we often still fail in creating an impact. We do not always succeed in delivering something new and refreshing and fail to inspire internal stakeholders to act upon the research.

Our experiments in the ‘My Life in Video’ project illustrate that we will not be able to be more inspirational by conducting our research over and over again in the same way. In our journey towards more inspirational research, we will need to spend more time in researching our

clients before we dig into solving the research problem. Although methodologies to research consumers are well developed, we still have a lot to learn when it comes to our client research toolbox. It will be about researching new techniques that trigger consumers to contribute with data that are meaningful and lead to something refreshing and inspiring. Our findings suggest that the solution

should not only be found in bigger volumes of data but can lay in getting more meaning out of small data by smart probing of consumers or even involving our consumers as coresearchers.

And last but not least, it is about the realization that

only half of the work is done upon the presentation of the results. We are in need of consumer chief officers who apply content marketing on research data and constantly look for ways in which they can bring the voice of consumers alive within organizations. Will we succeed? It is clear that on our road to research that sparks, we will

need to develop new skills that go far beyond an in-depth knowledge of methods, tools and analysis techniques. It will also imply courage to leave the beaten tracks. It is time for a generation of brave researchers on both client and agency sides to venture onto new research tracks. As with many things in life, the magic starts outside our comfort zone.

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Natalie Malevsky

Annelies Verhaeghe

Thijs Van de Broek

Product Strategy Telefonica Digital

Head of Research Innovation and Managing partner InSites Consulting

Research Consultant InSites Consulting

Thank you!

@InSites marketing@insites-consulting.com www.facebook.com/insitesconsulting www.slideshare.net/InSitesConsulting

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