Profound Launches Shopping Analysis
Shopping Analysis is a new solution that tackles a major blind spot in modern retail: understanding how products are discovered, described, and recommended within AI Answer Engines.
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Profound, the marketing platform that helps businesses control how they appear in AI responses and create optimised content that increases product awareness, has announced the launch of Shopping Analysis, a solution that addresses a critical blind spot in modern retail: how products are discovered, described, and recommended within AI Answer Engines.
With the launch of the Agentic Commerce Protocol (ACP), retail is accelerating at a pace we’ve never seen. Yet retailers still lack visibility into how and why their products are recommended by Answer Engines or compared with competitors.
“AI is the new front door to every business. It may not seem like it, but Answer Engines are commerce engines,” said James Cadwallader, Co-Founder and CEO of Profound. “Now, when you ask a question, a machine steps through the door for you. It explores, reads, interprets, and returns with a product recommendation.”
“The internet is no longer a place you visit. It’s a shopping assistant that knows you personally and recommends products. This is what we call the invisible commerce layer, and until now, it’s been completely invisible to retailers.”
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The New Reality of Retail Discovery
According to a recent Profound study, more than 60% of consumers now start product research with AI assistants, not traditional search engines.
Every conversation has the potential to turn into a purchase funnel, but retailers have no insight into when, where, or how their products surface in these AI-powered shopping experiences, or how Answer Engines are speaking on their behalf.
Profound research analysing 10,000 ChatGPT conversations found that when users were talking to AI about their problems, more than one-third of conversations contained completely unprompted product recommendations directly to the user.
Answer Engines provided unprompted recommendations across conversations, including sleep problems (41%), productivity issues (42%), health concerns (47%), and relationship challenges (23%).
Answer Engines suggested a purchase solution to address the users’ problem, despite not being prompted to provide product recommendations.
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Shopping Analysis makes the invisible visible.
The platform enables retailers to track which products appear in AI shopping conversations, monitor their visibility rates and positioning against competitors, and understand the specific attributes Answer Engines assign to their products, whether it’s “best budget shoes” or “premium performance trainers.”
Built for the AI-First Shopping Experience
Unlike traditional Answer Engine Optimisation (AEO) tools that only analyse text-based responses, Shopping Analysis captures actual product images, their placement within conversations, and comprehensive response details, giving retailers a complete picture of their AI commerce presence.
The platform also enables teams to evaluate merchant and channel performance, helping prioritise relationships and optimisations that drive the most visibility and conversions.
“Profound’s new shopping features are game-changing for us. Until now, we’ve used Profound mainly for brand awareness and content visibility. This update moves it directly into the growth and performance space,” said Stephen Racano, Senior Director of Growth at Coterie.
“The ability to tie shopping and non-shopping results together will give us a clearer view of how content drives conversions. It will help us understand where demand is coming from and how to optimise product visibility.”
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