As tools to understand shopper behavior advance, shopper journeys shift modes.
Wednesday, Dec 16th at 12:00 PM ET
Introductory Presentation by Greenbook + Tech Demos with Live Q&A
Some aspects of the shopper journey are very familiar, and the tools to understand them continue to advance. Less familiar aspects, however, create unprecedented challenges.
Innovations in such familiar aspects as eye-tracking, virtual shelf and store simulation, and video ethnography improve our understanding of shopping and point-of-purchase behavior. Tools for collecting and interpreting data for digital shelf and media analytics yield more insight into performance within online storefronts and the increasingly important area of retail media placement. POS/scanner feeds leveraged with household purchase panels span store and online purchases. Overall, tech for commerce intelligence continues to improve shopper behavior data collection, integration of data sources, and an increasingly unified view of the omnichannel experience.
However, the escalating use of AI agents for purchases creates new challenges for shopper research on top of the familiar ones. ChatGPT alone handles tens of millions of shopping queries a day, Alexa for Shopping has more than 100 million users, and Google launched a Universal Commerce Protocol at NRF 2026. Compared to human shoppers, AI agents are likely to be less sensitive to marketing tactics, agents can find and consider more alternatives, and much or all of what an agent does is unobservable.
At the same time as researchers and marketers have to keep up with how to understand the evolving human shopper, they now have to divide their attention toward an enigmatic assistant. The agent will proceed according to the criteria it is given, and those instructions, which can vary widely across shoppers, are invisible to researchers. Unlike a human that makes impulse purchases or changes its mind, the agent will focus solely on matching and evaluating the criteria it is given, and this makes it more critical for marketers to anticipate these criteria and express them convincingly.
Who should attend?
Agenda
Detailed program for this showcase will be revealed on November 11.

Key Takeaways
Major types of Commerce Intelligence Tech
A structured way to look at solutions for retail and purchase measurement, digital shelf and retail media analytics, and shopper behavior and purchase-point testing.
What Capabilities to Look For
Basic, extended, and emerging features of commerce intelligence solutions.
What’s Next for Commerce Intelligence
How future capabilities will address today’s unmet needs, including researching AI-mediated shopping.
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