Since the pandemic, changes in consumer behavior have had a considerable impact on Canadian retailers. Predicting consumer trends has become almost impossible, as historical data has become irrelevant over the past two exceptional years. Sports Experts needed to gather real-time information to differentiate itself in the crowded Black Friday advertising space, in order to increase traffic share and revenues.

The qualitative data collected through our survey contributed to give Sports Experts a head start to win Black Friday

Increase in overall sales
3%
Increase in in-store traffic
5%
Increase in average time spent on the website
+75%

The Context

After a rough couple of years, punctuated by growing health and economic insecurities, retail consumers were more unpredictable and irrational than ever. Like most of retailers, it was impossible for Sports Experts, a Canadian sports retailer, to forecast consumer behavior. We were facing total darkness for this year's Black Friday. 

Were people missing the feeling of shopping in store? Would the 2020-2021 product scarcity pressure them into shopping earlier? Or considering all the boredom shopping and Covid-related new hobbies, did they even need anything?

No external database, no internal data set could answer these decisive questions. We needed our own solution to predict our future consumers’ behaviour, nonetheless.

The challenge quickly became an opportunity. If we had no tangible consumer insight to work from, we created a solution to generate some tailored insights, based on every possible scenario.

Introducing the Crystal Ball

Sports Experts set up an ambitious promotional campaign powered by a unique, custom-made, predictive data ecosystem called the Crystal Ball.

We got a head start working with a blank canvas. While our biggest competitors were mining some outdated data for guidance, Sports Experts was already building their own set of learnings.

Powered by multiple data touch points, the Crystal Ball allowed us to predict and understand consumers’ mindset. No decision was made blindly.

First, the predictive data ecosystem combined first party data, allowing a real-time understanding of the consumer needs, and how they were expected to behave online and offline. It also integrated data from the competition for a market overview.

Secondly, and most importantly, we collected zero party data: thanks to an innovating pooling tool, we were able to collect exclusive and extremely precious data at the source.

Gathered and well analyzed, we were able to detect and create predictive and real-time insights that would then help build the upcoming promotional campaign.

The Crystal Ball

We planned, activated and optimized what would become Sports Experts’ all-time best Black Friday campaign

The Crystal Ball
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The Crystal Ball

Step 1

First, we collected all the data that would help us predict and plan our 2022 campaign. Alongside with the usual research tools, we created custom survey that would be used to pool our future consumers and inquire about their needs and intentions. The strength of this solution is it surveyed the exact same audiences we were looking to activate during the promotional campaign, allowing a deep understanding of their motivations to build out messages and offers.

Step 2

Second, a deep analysis emerged from the survey data that had been collected. In addition to the 1st party data and competitive metrics, we dissected 1000+ responses with over 64 answers paths. This step was crucial to correlate three important data points to extract actionable insights: consumer motivations, product types they were looking for, and their key buying timing for Black Friday.

Step 3

Lastly, thanks to our Crystal Ball, we made impactful and smart decisions. We created personalized messages based on predictive insights of our consumers’ motivations. For example, winter sports enthusiasts who wanted to make sure the best gear would not go out of stock were exposed to a different message than those who were looking for the best discounts on winter boots. We also built programmatic and social audiences based on behaviour, modified our bidding strategies for anticipated products, and optimized the timing of our messages in real time.

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