Forging the Future of Attribution for Retail Marketing

Google is full steam ahead on depreciating cookies by the end of 2024, forcing retail marketers to confront the effectiveness of their campaign measurement tools. To look toward the future, marketers first have to take a step back and recall that tools are only effective when they solve the right problem.

This means a measurement tool needs to be delivering insights at the frequency and granularity of decision-making. If you are making your budgeting decisions at the campaign level, knowing which platform has the highest average ROI is helpful but… knowing which campaigns have the highest ROI would be more impactful. Similarly, knowing the ROI of a campaign once a quarter is helpful, but knowing it daily is an order of magnitude more valuable.

The need for innovation in marketing measurement didn’t begin with Google’s privacy restrictions. Customer acquisition costs are already on the rise. While technological advancements have allowed marketers to reach prospective consumers through increasingly more sophisticated means, in-platform measurement has remained predominantly last-touch, an approach that many (including TikTok) have noted is inherently flawed. To drive efficiency, as well as sustainable and profitable growth for their businesses, brands must utilize more robust measurement that separates coincidence from true causation and delivers those insights at the speed and granularity they make decisions.

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Measurement in Retail Media

More robust approaches than last-touch attribution like multi-touch attribution, media mix modeling, and lift testing were designed to provide that type of detailed measurement to marketers. However, these tools were built for the specific paradigm they operate in, be it through television or the Internet.

Retail media, in particular shoppable media, requires a different approach. You have a highly dynamic environment where pricing, promotion, placement, and product changes alongside your media in near-real time. A measurement tool needs to account for the dynamic nature of this environment by taking in the rich signals unique to retail media related to pricing changes, promotions, search rank, etc. while also delivering measurement back at the granularity of decision-making.

Why Incrementality Measurement for Retail Media?

Incremental measurement in retail media is a two-sided coin, answering the following questions:

1. What sales took place as a result of my actions?
2. What sales happen without it?

This two-fold approach allows marketers to analyze the lift in revenue a marketing action provides and in doing so drive a more effective use of their marketing dollars.

While the output is reminiscent of other measurement approaches, the speed needed for decision-making has to be aligned with the operating cadence of retail. The quarterly or semi-annual measurement with lags of months between campaigns common to approaches like MMM and MTA drastically reduces the utility of measurement when applied to retail media. With hundreds of campaigns supporting a wide range of SKUs measurement needs to be calibrated daily to keep pace with the dynamic environment.

As retail media continues to grow, measurement will need to evolve to the specific environments of marketplaces and the needs of retailer media buyers. By leveraging the rich signals unique to this space with an emphasis on the granularity and speed of insights, new tools can equip marketers with the insights they need to drive conversions, build consumer relationships and propel their brands forward.

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