The Belgian DIY market is still driven by in-store sales. The top reason consumers prefer to shop in physical stores is to see, experience and test products in person before buying them. Brico, the DIY/Home improvement market leader, is no exception. Physical stores are accountable for 97,5% of the revenue. In the peak pandemic, home improvement smashed new records, shopper behaviour changed almost overnight and online became a fundamental channel.  

Despite the organic growth in online orders throughout this period, the offline results still represent by far the largest part of the revenue for Brico. Bringing people to stores and making sure they come back is still the key driver of Brico’s business. 

That is why, for many years, Brico’s main advertising tactics have been print ads. A conventional technique that had proven its success. Shoppers were bringing their print ads to the store.

Semetis monitored closely the change in research behavior through Google Trends, where a clear spike in online research can be seen since the pandemic. The question arises: should Brico change their marketing strategy?  To answer this question, we dug a little deeper into where and when the shopper journey actually begins. By combining Google Trends data, Google Analytics data and in-store data provided by Brico it became clear that consumers today conduct pre-shopping product research online before heading into the store. Our conclusion was that retailers that leverage best-in-class digital content and findability based on keywords are more likely to win over the final sale. This meant that assessing the results of our digital campaigns solely based on e-commerce performances no longer made sense.

Our recommendation was clear: we have to transition from e-commerce targets towards ROPO (research online, purchase offline). To do so, we are challenged technically on how to value the ROPO impact of our digital marketing strategy. Part of our answer could be found through Google, by leveraging the metric “store visits”, which measures the in-store visits of users who clicked on our ads.  By completely shifting our strategy and taking into account offline behaviour, we could work “hand in hand” with the stores, all striving for the same objective: developing the business of Brico. 

Even though this was our recommendation, Brico was rather skeptical about transitioning to a store visit optimization. It was clear that the online buzz should be accompanied by proven increased financial returns. We needed more than “store visits’ data to be convincing. To overcome this, we proposed an O2O A/B test that would be measuring the success of the campaign based on real store revenue data. 

 

  1. Leveraging the power of precise targeting to conduct experimental research

  

We opted for an experimental research, where the effect of the intervention (in this case digital marketing) is tested by comparing two groups. The first group is exposed to the digital marketing campaign, and the other group isn’t. The experimental and control group were composed of similar stores in terms of sizes and in terms of business. For this test to be statistically significant, the correlation between the performances of the two groups needed to be very high. We made sure in the classification of the stores that the revenue of the experimental and the control group had a 93% correlation, which was crucial to be statistically conclusive. Right before and during the campaign, we made sure that nothing unusual happened for the stores (campaigning, promotions, etc). 

We created a perfect context to compare apples with apples.

a) The situation without any digital campaign for the test group

 

b) The situation that we hope to get

 



The experiment ran for one month. By applying strict targeting rules, it was guaranteed that the stores from the control group were not exposed to the local campaign. For the set-up of the campaign itself, we opted for Google Local Campaigns. Our reasoning for the media selection: 

 

The experiment design is not yet completed at this stage, as we still need to tackle the challenge of assessing the in-store revenue generation.  

Putting in place a tech ecosystem was too costly and excessive. Therefore, we decided to approach the question through regression analyses, which is a powerful statistical method that allows you to examine the relationship between two or more variables. Given that from a statistical point of view both groups could be considered equal (93% correlation), performance changes in the experiment group could be examined through a regression analysis. 

Finally, the purpose is to estimate the effect of digital marketing on the dependent variable, in this case, in-store revenue. The in-store revenue was measured by Brico daily and shared with our Business Intelligence teams, allowing them to calculate if there is a dependency and if there is, calculate precisely the incremental revenue. 

 

 

  1. Results

 

The results exceeded everyone's expectations. The stores of the Experiment group generated a 2.9% uplift in revenue compared to the prediction. The incremental ROAS of this uplift of revenue was 4.3. In other words, for every euro invested in our campaign, we were able to generate a 4.3 incremental return in terms of in-store revenue.  Furthermore, we were able to assess if Google store visits are a good representation of what actually happens offline. The metric succeeded in the test. We are now convinced that it’s a very qualitative metric to measure the offline impact of our campaigns.

 

The test helped Brico figure out how to deliver fantastic omnichannel customer experiences. The human touch is still an important part of the retail experience, but the synergy between online and offline became key to Brico’s retail success. This was the acceleration point for Brico, and the proof needed for digital marketing transition to an omnichannel focus. As of now, our digital campaigns are optimizing to omnichannel performances. 

 

 

 

  1. Learnings and next steps

  

Very often, marketers and other departments have difficulties understanding each other. In our industry, we have the tendency to talk in acronyms (CPC, ROAS, CPA, COS, etc) which can make our message difficult to grasp. With our approach, we were able to talk in a language that everybody understands. Therefore, our conclusions and learnings were actionable at the entire company level. 

 

Because of the experiment, leveraging actual Brico sales data, we were able to prove that an extrapolated metric such as Google store visits is a good representation of what happens within the stores. From now on, Brico feels comfortable trusting and relying on this metric to assess the offline impact of digital advertising. We completely changed the mindset of our digital advertising strategy: from an e-commerce approach to an omnichannel full-funnel strategy.


publication auteur Sebastiaan Reeskamp
AUTEUR
Sebastiaan Reeskamp

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