Framework
Four things to research about AI-assisted shoppers
When an AI assistant does the searching and comparing, the variables that decide the sale sit with the shopper: what they actually asked, whether they checked the recommendation, what made them override it, and what they believed they were buying. Use these four as the backbone of a recurring interview study with recent category buyers who used an assistant.
Where this appears
What's in this framework
- What they actually asked: The prompt is the new query: constraints, occasions, budgets and past bad experiences no keyword tool sees.
- Whether they verified: Did they click through, check reviews or just accept the recommendation? This splits buyers into two groups.
- What made them override it: Why someone rejected the agent's pick shows the brand trust that survived a recommendation against you.
- What they believed they were getting: Agents summarise and summaries drop caveats. The gap lands on your reviews and returns.
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<a href="https://www.koji.so/visuals/agentic-commerce-four-research-variables"><img src="https://www.koji.so/visuals/agentic-commerce-four-research-variables/agentic-commerce-four-research-variables.png" alt="Framework of four things to research with shoppers who use AI agents: what they asked, whether they checked, why they overrode it and what they expected." width="1200" height="802" /></a>
<p>Source: <a href="https://www.koji.so/visuals/agentic-commerce-four-research-variables">Four things to research about AI-assisted shoppers</a>, Koji</p>
