+24% Sales
Significant sales increase
-43%
Marketingratio Sharp marketing ratio decrease
CASE STUDY MARKETING INTELLIGENCE Fashion | November / 2011
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1. Our Client
Our client is one of the leading online addresses for luxury fashion goods worldwide. The company offers a wide range of high-class products from main collections of all important international designers. The retailers’ buyers attend all the important fashion shows around the world and order directly from the designers. For several renowned designers the company is the exclusive sales partner on the European market.
2. Initial Situation Since the beginning of 2009 QUISMA has handled the client’s entire spectrum of online marketing measures. The overall goal is to increase awareness and the number of sales using the following channels: affiliate marketing, display advertising, retargeting, search engine advertising and search engine optimization. All measures aim at directing relevant traffic to the website – people with a high income and an interest in luxury lady’s fashion. In addition, QUISMA draws a detailed media plan for the implementation of online marketing measures, answering the crucial questions: „How to do it? When to execute? How much capital is needed?”
3. Goals In the past years the client had to allocate much of its budget to advertising and communication measures in order to continually increase brand awareness and sales. The expenses were based on a marketing ratio that had been defined beforehand, albeit, each channel’s performance was considered separately. In order to increase growth, QUISMA was assigned to develop a method that enables the client to efficiently allocate the total budget to different online advertising channels based on an overall marketing ratio. Hence, not the performance of a single channel but the overall performance of all channels defined the decision making process. 2
4. Implementation QUISMA analysed and compared various methods for optimal budget allocation. The spotlight fell on the customer journey, which describes the route a user takes from the initial contact with the respective product through to the ultimate sale. Knowing which paths customers normally take helps companies focus their advertising activities on the specific channels through which they can best reach the target group. Particularly promising combinations of communication measures can also be defined. Using this method, the available advertising budgets are divided across the channels with the best likelihood of a favourable outcome. Success is reflected in increased sales and a reduced marketing ratio. In the fast-paced online world in particular, the budget allocation must be permanently monitored in order to respond to short-term changes and thereby ensure budgets are optimally allocated at all times. Companies that invest the majority of their advertising budget online have two principal means of analysing the customer journey – using the technical method or the econometric method. Taking the customary technical approach, the analysis is based on tracking data alone. An accurate result can only be achieved with this method under certain conditions. Firstly, all advertising measures must be focused on the Internet, and secondly, all channels must be monitored using one single tracking system. Although both prerequisites applied to our customer, we chose not to go with the technical solution for various reasons: Device change cannot be mapped using tracking systems A technical tracking solution cannot take device changes into account. Most users nowadays use various end devices (mobile phone, laptop, tablet PC, etc.) to find out about products online. For example, a user may notice a particular product while surfing at work, but do more in-depth research later on his home PC. He then carries out further checks via his smartphone, before finally completing the purchase on his work computer. This path cannot be tracked using the technical method as the tracking system can only record the (different) unique IDs. Therefore, the one user will have a different unique ID for each piece of equipment he uses. In the case of our example, this means that the system would only register and uniquely ascribe the first and last click. 3
The customer journey cannot be completely illustrated and traced as a result. Such a restriction automatically introduces errors into the representation of the customer journey. The contributions of the individual channels are not mapped as it is not possible to record all user clicks and thus all stations.
Cookie deletions cannot be taken into account A similar problem arises with users who regularly delete their cookies. A complete customer journey cannot be mapped without cookies.
External factors cannot be incorporated into the calculation For example, offline advertising activities cannot be recorded by tracking systems. It is not possible to map contact which the user may have had with e.g. TV, newspaper or magazine advertising using online tracking systems. In addition to this, special offers and seasonal fluctuations cannot be recorded and therefore taken into account.This path cannot be tracked using the technical method as the tracking system can only record the (different) unique IDs. Therefore, the one user will have a different unique ID for each piece of equipment he uses. In the case of our example, this means that the system would only register and uniquely ascribe the first and last click. The customer journey cannot be completely illustrated and traced as a result. Such a restriction automatically introduces errors into the representation of the customer journey. The contributions of the individual channels are not mapped as it is not possible to record all user clicks and thus all stations.
Use of different tracking systems from different providers This scenario didn’t apply in this instance, but should be mentioned for completeness. If companies use different providers to track their online advertising activities, the customer journey can only be mapped to a limited extent. For example, if provider A is tracking display and affiliate activities, while SEA and SEO monitoring falls under the remit of provider B, each provider can only provide a coherent representation of their own particular area of responsibility. It is not possible in this instance to advise on the optimal budget allocation taking all aspects into account. Tracking Partner A
Tracking Partner B
Tracking Partner C
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The factors outlined above distort the picture of the customer journey, resulting in less than optimal distribution of the advertising budget. Because of this, QUISMA selected the econometric method, an approach which facilitates the calculation and clear demonstration of the contribution made by each channel to the sales that were generated. This calculation is not based on individual user paths but on interdependencies and contributions. QUISMA performed modelling to calculate the contribution. This is a multivariate analysis technique which establishes a direct cause-and-effect relationship between the actual sales made and all of the data collected about advertising activities (offline and online). The extent to which each individual channel actually contributed to sales generation can be precisely demonstrated using this method. Supposedly promising advertising activities can be exposed as less effective, while underappreciated channels may prove themselves to be sales boosters. The results of the modelling are compared with the investments made. This involves looking at the budget invested in each individual channel, resulting in a detailed breakdown of the ROI for each individual channel. Particular relationships between channels and sales that would not have been ‘visible to the naked eye’ can be uncovered using this method. This approach allows customers to permanently optimise their budgets, thereby avoiding poor investments, sustainably increasing sales and reducing marketing ratios.
6. Result Modelling which served as the basis for recording the effects of the channels on overall performance, including cross-media effects, was initially generated retrospectively for the period from January 2009 to June 2010. The virtually unchanged budget for the last two quarters of 2010 was then redirected on the basis of these results and compared with the last two quarters of 2009. Half of the budget went on SEA in the 2009 business year. The main investment went into generic keywords with the aim of raising awareness. Other advertising channels were considered of somewhat lesser importance. The focus on SEA led to an increased deterioration in the marketing ratio. The modelling showed that the display advertising channel triggered sales in other channels, from which the retargeting, SEA and SEO channels benefited in particular. Thanks to the cross-over effects identified using this modelling, the budget was redistributed with a greater allocation for display advertising and significantly less for SEA. The results have been remarkable. Although the budgets in all channels were reduced, apart from display advertising 5
(strongly increased) and SEO (marginally increased), the sales generated only fell slightly or not at all. On the other hand, display advertising triggered sales in the SEA, SEO and retargeting channels. Budget Allocation – Initial Situation: Affiliate Marketing
15%
Retargeting
5%
SEA
50%
SEO
10% Display Advertising
Q3-Q4 2009 Source: QUISMA
20%
Budget Allocation Based on the Modelling: Affiliate Marketing
15%
Retargeting
5%
SEA
38%
SEO
12% Display Advertising
Q3-Q4 2010 Source: QUISMA
30%
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Business Year (Q3-Q4) 2009
10.000 7.500 5.000 2.500 0
9,326
3,206
3,261
1,362
1,456 Source: QUISMA
SEA
DisplayAdvertising
SEO
Retargeting
AffiliateMarketing
Business Year (Q3-Q4) 2010
10.000 7.500 5.000 2.500 0
9,312
3,455
6,191
2,695
1,425 Source: QUISMA
SEA
DisplayAdvertising
SEO
Retargeting
AffiliateMarketing
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A comparison of the two last quarters of 2009 and 2010 shows that sales rose 24 percent with a virtually unchanged budget, while the marketing ratio fell 43 percent.
Sales
30.000
+24%
20.000 18,611
10.000 0
23,078
Q3-Q4 Sales Increase, Source: QUISMA
Sales 2010 Q3-Q4
Sales 2009 Q3-Q4
Marketingratio
15%
-43%
10% 5% 0
13.13%
MR 2009 Q3-Q4
7.50%
Q3-Q4 Marketing Ratio Reduction, Source: QUISMA
MR 2010 Q3-Q4 8
7. Outlook With QUISMA’s assumption of responsibility for the customer’s online marketing measures, campaigns are being optimised daily in terms of sales and the marketing ratio. Furthermore, the company is currently planning an additional test campaign for TV advertising which would be included as another modelling component in the future and take the cross-effects between online and offline media into consideration.
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