“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Ramez Karkar, director of data architecture at Mediavest Spark.
The current data landscape in which CPG marketers find themselves resembles an island without access to clean water. Luckily, supplies may be within their grasp, and the situation is finally starting to change for the better.
Akin to finding fresh water on a desert island, clean data is great when you have it because the value of customer information is huge in today’s advertising world. Customer data allows marketers to garner attribution insights, build lookalike models for prospecting and cross-sell current customers. Most financial, tech, retail and travel brands have reaped the biggest benefits of precision marketing from their access to swarms of first-party data.
Yet most CPG brands have been left behind to target third-party CPG audiences modeled off a small panel of users to establish some sense of precision marketing. It is not that CPG brands don’t desire greater precision; they just don’t own the rights to the “shelf space” in the stores, and therefore have no clean data supply flowing in.
Without owning any shelf space in the stores, CPG brands are forced to accept modeled data from providers who claim that it’s clean. Modeled data might be good for mid- or upper-funnel targeting tactics, but it is not ideal for measurement, lookalike modeling or retargeting. Most CPG data providers are also not willing to share the seed set used for their models, which could be licensed, as they don’t want anyone to know the ingredients and how small their sample size actually is.
More concerning is that data providers make quality claims about their products through the attribution reporting they provide. While working with modeled CPG data is still a step in the right direction toward being more data-driven, compared to the previous tactics of broader demographic targeting, CPG brands’ reliance on data partners is unhealthy and should only be regarded as a temporary solution.
For data-starved CPG professionals, clean supplies should arrive soon. The shipments are coming in small amounts, but newer providers in the form of reward apps or online marketplaces are collecting data on the products users purchase off store shelves or online.
For example, Shopkick, Ibotta and other reward apps provide digital coupons and give cash back when users purchase certain promoted products at the grocery store. Shopkick even rewards users for simply scanning the product’s barcode – essentially giving partial rewards to users to interact with the product on the shelf – which also guarantees viewability. Ibotta links directly with some stores’ rewards programs to help streamline cashback and simultaneously collect more data.
Connexity, formerly Shopzilla, collects valuable online shopping data from Bizrate, PriceGrabber and other sources to provide marketers with highly relevant shopper data and insights at scale.
And let’s not forget Amazon. While many brands may have mixed emotions about fueling Amazon’s online shelf sales, the power of its shopper data is immense. It has pure data on who real customers are at great scale, which can be used for retargeting, lookalike modeling and insights within its programmatic platform – either on or off Amazon properties.
Additionally, there are other companies in this space, including Instacart and MiniBar, that do the in-store shopping for customers; they should also be coming to CPG’s rescue soon.
This should be the year that first-party data finally starts to trickle down from the “stores” to the “shelves” in large quantities as data collection tactics become increasingly sophisticated and vendors capitalize on this large gap in data equality. Everyone can and should have data access.
CPG marketers need to be more mindful of the data they are putting into their data management platforms and media plans and push the industry to get as much access to clean, unmodeled data as possible.
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