Buyers research on ChatGPT, Perplexity, and Reddit — then buy on your site, on Amazon, or in-store. The shortlist gets built outside the channel where the purchase happens. We get your products into that shortlist, regardless of where the buyer eventually checks out.
A buyer asks ChatGPT for a recommendation, narrows to three names, checks Reddit, then opens whichever store they normally use. The shortlist closes on a research surface. The cart closes on a buying surface. They are rarely the same place.
If your primary channel is Amazon, the AI shortlist work shows up as branded-search lift in Brand Analytics and a corresponding bump in PDP conversion. We run the off-site work; you watch the channel that makes you money.
A brand with no D2C site at all is invisible online — and now invisible to AI too. Pre-store buyer research has shifted to AI shortlists in the past year. Showing up there is the cheapest awareness program a retail-distributed brand can run.
The Reddit threads, listicles, and creator content that earn AI citations don’t care where you sell. The way you measure the lift does. We tune the attribution layer to the channel that actually books revenue for you — D2C, Amazon, retail, or any combination.
D2C clients see GA4 conversion lift and post-purchase “how did you hear about us” signal. Amazon-first sellers watch branded-search in Brand Analytics and PDP conversion. Retail-distributed brands measure with retailer first-party data and branded-search at the category level. Same engine, three dashboards.
We ran a structured study of where ChatGPT actually pulls citations from across consumer-shopping queries — across discovery, comparison, and validation intents. Two of the more useful charts for ecom teams are below. The rest of the study has the full breakdown by category, intent, and content age.
Five source types — brand sites, retailers, editorial, marketplaces, UGC — split the citation pie across every shopping query we indexed. Your category page is one slice of one slice. The implication: a program that only optimizes the brand site is optimizing for ~20% of the citation surface.
Amazon, eBay, and resale platforms only get cited directly 4–8% of the time. But marketplaces supply 30% of the supporting ratings AI uses to validate a recommendation. The Amazon-only objection (“we don’t need GEO, we sell on Amazon”) reads backwards: AI uses your marketplace ratings to validate the brand shortlist, then the buyer comes back to Amazon to check out.
AI doesn’t cite the product page that re-described the same spec sheet every other listing in your category did. It cites the page (or thread, or review) that answers a specific buyer’s specific question. Two moves we run that most ecom content programs skip.
Customer-service tickets, return reasons, sizing questions, fitment chats, post-purchase survey responses — every ecom brand has a warehouse of buyer questions that no keyword tool will ever surface, because the buyer asks them privately.
We extract those question-and-answer pairs and turn them into specific buyer-guide content, sizing pages, comparison content, and FAQ sections. The long-tail factual answers AI lifts when it decomposes a shopping prompt into sub-questions.
The gift-buyer asks AI for a thoughtful pick under a budget. The self-buyer asks for the technically best option for their use case. The wholesale buyer asks about minimums and lead times. Same product line, three different prompt sets.
We build a separate prompt map and content track per buyer type, and tie each back to its own attribution path. The buyer with the highest revenue contribution gets the most weekly throughput.
We map your category against every prompt shape and audit the citation source for each. Different shape, different source — the off-site work bends per type.
60–200 actual buyer prompts in your category, pulled from ChatGPT shopping, Perplexity, Reddit, and Google AIO — segmented by buyer type (gift, self, wholesale, B2B). Where you stand on each, scored against competitors.
Reddit citation work in your category subs, listicle placements with Wirecutter-style outlets and niche review sites, creator partnerships where the long-form review ends up cited. The signal AI prefers over your own pages.
ProductGroup, AggregateRating, and attribute markup on your D2C product pages. Review-acquisition work that lifts star count and depth. Sizing content built from CX data. All of it strengthens citations regardless of where the cart closes.
D2C: GA4 + post-purchase surveys with “how did you hear about us”. Amazon: branded-search lift in Helium / Brand Analytics, plus PPC search-term reports. Retail: branded-search + retailer first-party data. Same off-site work, different attribution layer.
Shortlist share, citation count, branded-search lift, channel-revenue contribution — every Monday in one dashboard. Not a quarterly retrospective; not a monthly Looker dump.
When a buyer asks AI “Is [product] worth it?”, the answer pulls from your reviews, your product attributes, your structured data, and the third-party reviews on Trustpilot, Amazon, and category aggregators. AI reads the structured layer first.
Most ecom sites have partial product schema, missing AggregateRating markup, no ProductGroup variants for size / color, and 4-star averages that don’t make it into the citation because the schema isn’t there. We fix the structured layer first — it’s the cheapest unlock and the heaviest cited.
A cause-driven e-commerce brand running on Shopify with a parallel Amazon channel. Strong product, healthy reviews on their own site, negligible AI shopping presence — invisible across the top 14 buyer prompts in their category.
We mapped the prompt set, fixed the product schema, ran a Reddit and listicle program in three category subs, and seeded honest creator reviews. By month three they were in the top-3 AI shortlist on 11 of 14 prompts. Branded search on Amazon lifted 38% in the same window, with PDP conversion up 11% — both measured in Brand Analytics, not modeled.
Read the full case study →Run a Live Audit. We pull your brand against competitors on the top buyer prompts in your category — across ChatGPT, Perplexity, Gemini, and Google AI Overviews — and send the full report to your inbox.
