Instacart Ads

What’s in the Basket? Instacart Ads Webinar Recap

What’s in the Basket? Instacart Ads Webinar Recap

What’s in the Basket? Instacart Ads Webinar Recap

Jul 27, 2021

In this article we go over some of the data and insights shared by Brian Gillis, director of CPG Insights, during our last webinar and offer a sneak peek into June’s webinar on ‘path to cart’ data.

The webinar started with a review of Instacart’s rich and diverse data source which forms the basis for the analysis that Brian’s team performs. With access to millions of orders over time from over 600 retail partners, across 45,000 stores, involving millions of households, Instacart aggregates and anonymizes a vast amount of data into a tremendously valuable data set. And since this data is updated every night, the asset is not only rich, but timely.

Brian then talked about the types of analysis Instacart can do with this combination of point-of-sale (POS), transaction log (TLOG), and out of stock (OOS) data, going over some broad categories like operational metrics, panel data, and loyalty metrics before zeroing in on the main topic: basket affinities.

Basket affinities describe what else is likely to be in the same basket as a given product, brand, or category. Leveraging all its rich basket data, Instacart can basically go find every single basket the target was found in, across the continent, and analyze what else was bought at the same time.

The analysis involves adjusting for common items, like bananas, found in many baskets irrespective of what else was bought at the same time, to calculate a ‘basket affinity index’ which describes how likely products (or brands, categories, or sub-categories) are to be bought together.

Basket affinities helps Instacart, and its brand partners, to create consumer ‘types’, discover product interactions, understand mission-dominant baskets, and identify trigger products — ultimately building a picture of how brands are bought online that we then share with our partners to build a better plan to acquire and retain valuable consumers.

Under the umbrella term of basket affinities, which Brian tried (and failed) to rebrand as ‘cart cartographies’, there are several types of analyses that examine relationships between items in the basket. The term ‘basket affinity’ covers examining the one-to-one, group-to-group, or many-to-many relationships between products, as well as identifying consumer shopping missions and consumer profiles.

For an interesting example of a cross-shop, we looked at the relationship between meat and meat alternatives — which includes ‘faux meat’ items like vegetarian hot dogs and burger patties — with the initial assumption that consumers who buy meat are not likely to purchase meat alternatives.

But that’s not what the data showed —

Another real-world example discussed during the webinar used coconut water as a trigger product to help identify a consumer profile — the health-conscious eater. Here we saw the consumer trend for healthier alternatives to sugar-based drinks driving not only coconut water sales, but a ton of other health-conscious food items. With high basket affinities for pomegranates, probiotic drinks, kombucha, non-dairy yogurt, and oat milk.

The next webinar looks at ‘path to cart’ data — which show how consumers are finding the products they put in their cart on Instacart marketplace. What’s interesting about this data is that it changes over time, both in terms of seasonality and as consumers progress from their first shop on Instacart to their tenth, thirtieth, or hundredth shop. We’ll look at how this data changes, both in general when looking at a typical consumer, and for specific categories, drawing insights from real data to explain this aspect of how consumers shop for groceries online.

Register to attend our next webinar, on June 25th at 11:30 a.m. EST and get access to all the path to cart data and insights we’ll share.

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