What’s Missing in Agentic Commerce - Part III

Purchase History Is the Strongest Signal in Commerce — Ads Lie. Purchases Don’t.

Agentic commerce lives in the browser….and there’s no bigger browser than Chrome. That’s why we believe extensions will be a critical component in powering agentic commerce for consumers. Extensions can act as the agent, leveraging an MCP server to build a rich context graph of the user and intelligently apply it across the web. As we’ve said before, agentic commerce works best on structured, repeatable, and price-sensitive datasets - and no purchase is more frequent or predictable than groceries.

We see extensions as the path forward: assisting, advising, and automating tasks on behalf of the user, with every step guided by explicit user consent, informed by purchase history, and fully controlled by the user.

We believe this is the future of commerce. While truly autonomous, agentic systems will reach full fruition over time, the near term is defined by organized, controlled, and intelligent connections between data and context. For consumers, the most powerful context is purchase history - it’s the cleanest and most informative signal for decision-making.

This trajectory of ecommerce, and the future of truly agentic commerce, depends on clean, structured retailer data. Today, especially in grocery, product catalogs are often inconsistent, opaque, and poorly maintained. We’ve spent months rebuilding these catalogs to create reliable, structured datasets - tedious work that few are willing to do, including the retailers themselves. The consequences are obvious on today’s retailer sites: women’s razors categorized as yogurt and Star Trek toys listed under cheese.

The Path Forward: Assist → Advise → Automate

Purchase history tells the true story of a consumer. When combined with real-time search and intent signals, it enables a genuine 360-degree understanding of who a consumer is. The ad industry, by contrast, has long relied on inferred data - signals that are often noisy, delayed, or simply wrong. That’s why you still see ads for the same pair of shoes even after you’ve already bought them.

Purchase history is uniquely powerful because it’s unaffected by ads, uninfluenced by behavioral tracking, immune to third-party data noise, and anchored in what a person or household actually buys.

For dietary patterns, replenishment cycles, brand loyalty, sizing, product substitutions, and affordability, no signal is more predictive. That’s why we believe purchase history is the most reliable foundation model for grocery intelligence. It’s cleaner, more private, and far more actionable than cross-channel profiles or ad-driven personalization - and when paired with real-time browsing data, it becomes extraordinarily powerful.

History predicts intent. Real-time browsing verifies truth.

Together, they make agentic commerce possible today - even before retailers modernize their systems.

Conclusion: Building Toward an Agentic Future

Agentic commerce isn’t waiting for retailers to modernize. It’s already emerging - first through browser-level access, then through hybrid models, and eventually through fully structured retailer APIs. Real-time browsing isn’t the end state, but it is the essential starting point. At CartHappy, we’re building the bridge between today’s messy reality and tomorrow’s autonomous, intelligent shopping ecosystem.

We believe the future of commerce is built on accurate, trustworthy data - structured in a way AI can understand to deliver deeply personalized, automated shopping experiences for consumers.

That’s why we’re building agentic commerce that unifies cross-store purchase history with real-time pricing - automatically creating the most optimized, lowest-cost grocery cart for every household.