Amazon and Chewy are two of the biggest names in US pet retail — but Amazon's own data can't tell it how many of its pet customers are also spending on Chewy, or how much. Digital behavioral intelligence closes that blind spot. This worked example shows what a cross-platform competitor overlap analysis looks like in practice.

Amazon is the dominant platform for pet product purchases in the US. Chewy has built a specialist challenger business on subscription, loyalty, and pet-category depth. Both companies have their own analytics. Neither can see the other's customers.

That's the digital blind spot at the center of this analysis. First-party data tells you what happens inside your ecosystem. It tells you nothing about the share of wallet that's quietly moving elsewhere — or which customers are driving it.

Digital behavioral intelligence is built to close that gap. This piece walks through an illustrative competitor overlap analysis using RealityMine® data on Amazon and Chewy, two of the biggest players in the US pet products market.

Tracking share of wallet across competing platforms

Amazon dominates US pet product purchases. Chewy has carved out a loyal, subscription-driven customer base in the same category. The question is: how many of Amazon's pet-product customers are also buying from Chewy, and what does that mean for share-of-wallet?

Answering this question requires data that no first-party analytics stack can answer. You need to see behavior across both platforms simultaneously, at the individual level, over time.

What the data showed

Key methods included using search behavior to identify pet owners, creating a behavioral segmentation, examining cross-platform usage patterns, and comparing in-platform Amazon behaviour - product views, purchases, spend levels - between cohorts. Here’s what we found.

Chewy reaches a meaningful, consistent share of Amazon's pet customers

Across every month in the analysis, roughly 1 in 6 Amazon pet owners also used Chewy — an overlap rate of 17–19% that held steady without seasonal fluctuation. That consistency matters. It means Chewy isn't picking up Amazon customers at moments of dissatisfaction or price sensitivity. It has established, habitual reach into Amazon's customer base.

Dual users are more valuable overall — but Amazon isn't capturing it in pet

Customers who use both Amazon and Chewy buy 42% more products on Amazon overall and spend around 9% more in total compared to Amazon-only users. They're higher-value customers by every general measure.

But in pet products specifically, dual users and Amazon-only users spend the same amount on Amazon per month — $21 each.

Dual users buy more products on average (1.6 vs 1.3 for Amazon only), but that additional volume doesn't translate into additional spend. It raises the question: how much of that spend is going to Chewy instead?

Category mix reveals where Chewy is capturing share

Dual users' Amazon pet purchases skew toward food, treats, and healthcare — consumable, replenishment-driven categories. Their share of discretionary and lifestyle categories (habitat, clothing, accessories, toys) is lower than Amazon-only users.

That pattern suggests Amazon is holding onto routine, repeat purchases even among users who also shop Chewy, but losing ground in the higher-margin, one-off discretionary categories where basket size tends to be larger.

So what: The size of the opportunity

36% of Chewy users made pet-related purchases on Amazon in the past three months. Scaled against Chewy's reported active customer base of 21.3 million and $12.6 billion in net sales, the dual-user pool represents approximately 7.7 million customers spending around $4.5 billion per year on Chewy.

If even a fraction of that spend shifted back to Amazon, the revenue impact would be substantial. That’s why cross-platform behavior is worth tracking: it’s the starting point for understanding where share of wallet is going and how you might win more of it.

What cross-platform digital behavioral intelligence makes possible

This example uses Amazon and Chewy, but the same approach applies whether you're a delivery platform analyzing ride-hailing crossover, a streaming service mapping attention share, or a fintech tracking wallet share across payment apps.

What our data makes possible:

• Identifying dual-platform behavior before it shows in your own metrics. Cross-platform overlap is often a leading indicator of spend shift. The data surfaces it continuously, not in retrospect.

• Building accurate share-of-wallet models. Because the feed captures real behavior across competing platforms simultaneously, wallet share estimates aren't modeled or inferred — they're observed.

• Understanding category-level competitive dynamics. Product-level purchase data reveals not just that a competitor is winning customers, but which categories they're winning on and why.

The feed is the foundation. What you build on top of it depends on the questions your team is trying to answer.

About the data

The analysis above was built on RealityMine^® data, from passive collection of real app and web usage across platforms, sourced through a consented US panel of approximately 160,000 monthly active users. The data is behavioral, not modeled. It reflects what people actually did across platforms, not what they reported or what an algorithm inferred.

That distinction matters for the quality of any analysis built on top of it. Digital behavioral intelligence of this kind is structurally different from single-platform signals or survey-based estimates — and the gap tends to be largest in exactly the categories where competitive dynamics are most active.

RealityMine data via MFour panel (US market), app and web data combined, Android. Based on December 2025 – February 2026 usage. Base size: approximately 10,000 pet-owner panelists. Market-level figures derived from Chewy investor report data (21.3 million active customers, $12.6 billion net sales).