It’s no surprise that holidays are highly important for retailers every year, starting from Valentine’s Day to Easter and of course the Christmas season. These days can make or break a retailer’s performance for the year. With such an importance placed on holiday shopping, digital marketers have an opportunity to leverage these shopping occasions to drive sales across channels.
Unfortunately, many retailers approach major shopping days from an “all systems are a go” perspective, in which they are focused on executing as many strategies as possible to drive traffic in the key weeks before the important day. These strategies can include offering large “door buster” promotions (both online and in-store), ensuring shelves are stocked, adding in-store labor, running ads, and more. Because of the large focus on execution, many retailers may not have the time to step back and evaluate which elements of their strategies are profitable, which end up giving away money, and which strategies can be fine-tuned and rolled out. Adding to this challenge is the large number of touchpoints retailers are using today to engage consumers, from emails with loyalty offers to mobile communications to direct mail. Further, with shopping seasons starting earlier, this outreach is extending over longer periods of time and consumers are transacting at more points in time, across more channels.
With this challenge at hand, it’s difficult to understand how each business action really impacts consumer behavior. For example, while some digital marketers may be left to rely on click-through rates to judge the effectiveness of an email campaign or re-targeted ad, and some sophisticated teams will be able to measure a large, incremental online impact with confidence, both groups may be drastically underestimating the ROI of that action without also accounting for the harder to measure, but financially important, impact that the campaign has on in-store sales.
To solve this challenge, some retailers are using advanced, automated software to test different holiday strategies and compare the performance of a group receiving a given offer or communication (the “test” group) against the performance of a highly similar group not receiving that action (the “control” group). This type of “Test & Learn” process helps overcome key challenges associated with traditional analytical processes, including isolating the impact of one action amidst the broad range of concurrent campaigns, the limited amount of time and resources for analysis, and the multiple (often-siloed) channels to evaluate.
By moving beyond traditional marketing measurement strategies, retailers are beginning to answer important questions about their holiday strategies, such as: What is the cross-channel impact of a digital ad campaign for Valentine’s Day? Does an Easter promotion simply pull forward demand during the promotional period or does it increase sales in total? Does a deep discount cause a customer to become more loyal during the next year? For a loss-leading promotion, do customers purchase enough additional items to make giving away margin on a Valentine’s Day gift set profitable? And most importantly, how can we target each of our strategies to the customers, markets, or stores predicted to respond best to generate maximum impact across all channels?
As holiday shopping spreads over longer periods, consumers receive more information about products and promotions, and more shopping channels become available, there is more of a premium on answering these questions to understand which strategies work best, and how to best implement those strategies. Retailers who test business actions during major shopping periods will be able to confidently focus on executing the strategies that are predicted to maximize profits.
By John Howard, Applied Predictive Technologies.
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