When shopping becomes invisible
For years, retailers have obsessed over the perfect purchase funnel. Investing in personalized experiences, clear filtering, tailored content, preference saving, and beautifully optimized browsing paths. They aimed to remove friction from every corner of the user journey.
As someone who spent years in behavioral analytics working with large retailers, I saw first hand how much effort went into understanding every tap, scroll, and hesitation. Analytics became the lens through which retailers made sense of shopper intent.
The hard truth? A growing number of customers no longer begin by visiting a website and browsing through pages of products. They begin by asking a question. And when they ask, a machine does the browsing for them and recommends a set of products. Chat has equipped everyone with a personal shopper. Every conversation has the potential to turn into a shopping moment, yet retailers have no idea what products are being recommended, how their products are being described or what brands they are being compared to.
Retailers spent the past decade optimizing an experience that has moved to a completely different channel. Until now, they had no way to understand and control this new purchase funnel.
Insight into the conversational shopping funnel
Today we are introducing Shopping Analysis. Profound’s latest feature that shows retailers exactly how their products are discovered, described, and recommended inside Answer Engine shopping experiences. It reveals which products are surfacing in conversations, how often they appear, how they stack up against competitors, and which attributes answer engines assign to them.
This is the type of insight retailers used to get from behavioral and web analytics. Except now these user journeys are happening in a place that looks nothing like a website. There is still a funnel, it just looks very different. Shopping analysis lets retailers deeply understand the new retail customer journey.
Shopping Analysis also captures product images, placement inside conversations, and complete response details. Most tools only analyze text. We analyze what the user actually sees. This allows retailers to understand how AI represents their products across the journey from discovery to decision.
In chat commerce is still in its infancy
The emergence of agentic commerce (fueled by ACP) is accelerating the shift from website browsing to in-chat purchase at a pace the industry has never seen. This is one of the largest distribution changes in retail since ecommerce itself. Retailers need visibility into how they appear in Answer Engines or risk losing their place in the modern shopping journey entirely.
Your content, product pages, and product data influence how AI recommends your products. Proprietary Profound research across thousands of product pages shows that the products most frequently shown in AI shopping had significantly richer content. They had more FAQs, more videos, more detailed specifications, and even clearer URL structures. These patterns give retailers a roadmap for improving their AI visibility. We are diving deep into this research at Zero Click London next week. While Shopping Analysis is focused on visibility now - the immediate future is focused retail oriented content generation.
In the past, optimizing product visibility meant optimizing for search ranking and human browsing. Now it means optimizing for Answer Engines and machine browsing.
The opportunity for retailers
Retailers have spent years designing for on site browsing. Now they must design for conversational exploration. The best retailers will leverage this channel to create incredible shopping experiences for their customers - and expand their reach to entirely new customer bases.
The ones who don’t adapt risk becoming practically invisible.
Answer Engines is the new front door to every retailer - make sure you're open for business with Shopping Analysis.
Talk to our team about Shopping Analysis today.
