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GEO for e-commerce
A GEO consultant for e-commerce measures how often AI answer engines name your store when a buyer asks what to buy and who will deliver it — then changes what your site publishes so the engines can reach for you.
I do this as an independent consultant, one store at a time, in engagements of six to eight weeks. It begins with a measured baseline of your own buyers' questions and ends with the same measurement repeated in the identical mode, reporting what moved and what did not.
Everything is delivered in writing. No call is required.
Also called AI search optimization, generative engine optimization or AEO. For a retailer the labels matter less than one distinction, below.
The distinction that decides the work
Facts are executed. Adjectives are ignored.
Across twenty tracked purchase queries on a live store, one split held without a single exception.
Questions of fact — winnable on your own site
Who delivers to this city today? Is it in stock? What does it cost? Answered from your own pages. Publish the checkable number and you get named.
Questions of judgment — decided elsewhere
Which brand is best? Which store is trustworthy? Answered from other people's pages. Your own site barely participates, and no amount of content on it changes that.
Most money spent on AI visibility for retailers goes into writing judgment-question content on the brand's own domain, where it cannot work. Establishing which of your questions sit on which side is week one, because it determines everything after.
Measured
The engine reads your cut-off — and calculates with it
Asked where to buy electronics in a named city with delivery today, ChatGPT wrote:
"I'd check Jumbo first because its published policy specifically says 2-hour delivery for eligible orders before 5 PM. Since it's currently around 8 PM… that cutoff has passed for today, so Sharaf DG's checkout… may be more practical tonight."
The retailer with the best promise in the category was demoted because its window had closed at the hour the question was asked. Reproduced independently on two accounts. Full measurement, method and queries.
For a store this is the cheapest change available and the most direct. A later cut-off captures the evening. A twenty-four-hour window removes the comparison. And a cut-off published without a timezone and a city cannot be evaluated at all — order before 1pm is not computable, same day when ordered before 13:00 GST is.
Publish what happens after the cut-off, too. A buyer asking at 20:00 is a buyer the engine must answer. A page silent on late orders offers it nothing, and it reaches for a competitor whose page is not silent.
Measured
Three more things that are true of stores specifically
Stock status is read, and quoted back
Engines report availability inside the answer and warn the buyer when an item is out of stock. A stale out-of-stock flag does not merely fail to help — it actively argues against you in the text a buyer reads.
Size is not the barrier
In a measured category the answers named several independents materially smaller than the retailers who were absent, alongside the marketplaces. "The marketplaces crowd us out" did not survive the data.
The two engines name different kinds of store
ChatGPT named marketplaces, chains and official brand channels almost exclusively. Perplexity named those and the independents. For an independent retailer the realistic entry is Perplexity, and that should set the order of work.
What not to build
Two formats that were measured and failed
Pages shaped like the query, for purchase intent
Thirty pages of the "where to buy X in [city]" pattern earned zero citations in eleven days on a site that was being cited elsewhere in the same period. It is a dead layer for purchase questions, and it is the format most commonly sold.
The distinction that does hold: guides answering how to choose between products do get cited. How-to-choose works; where-to-buy does not.
An llms.txt file as a mechanism
Across roughly 2,100 verified crawler fetches on two sites, requests to /llms.txt from GPTBot, ChatGPT-User, OAI-SearchBot, PerplexityBot and ClaudeBot numbered zero — only bingbot and YandexBot ever fetched it. Publishing one is harmless. Paying for it as a strategy is not honest, and I removed the claim from this site when my own logs contradicted it.
Live retrieval goes to ordinary pages, and on a measured site the agent that fires on a live question took the homepage on 84% of its visits. That is where a store's facts belong — not three clicks deep.
Reference deployment
Eight weeks, one bootstrapped store, no ad spend
A specialty e-commerce retailer: ten of twenty tracked purchase queries reached the top five in ChatGPT from a baseline of zero, including first place on the trust query for its category, with all four control queries behaving as predicted. The store's own phrasing came back verbatim inside answers.
And the other half, which belongs on the same page: this consultancy's own site was measured against ten of its own buyer questions and scored zero out of ten in both engines. The prediction that it would score zero was written down before the measurement ran. Six of those ten questions return no vendor list to anybody — which is exactly the finding the method exists to produce early, before anyone spends money on them.
Price
Start with the free check
| What | Scope | Price |
|---|---|---|
| Category check | Four of your buyers' questions, two engines, eight runs. Tells you whether your category returns a store list at all — roughly half do not. Two working days. | Free |
| Visibility audit | Ten questions, three runs each, two engines. Sixty recorded answers, source analysis, crawler log check. | $400 |
| Audit & first sprint | Audit, two weeks of implementation, re-measurement in the identical mode. | $1,800 |
| Full deployment | Six to eight weeks, baseline to re-measurement, report including what did not move. | $6,500 |
No ranking is ever promised. Positions do not exist in answer engines — the same question asked in the same minute on two accounts returned a five-name shortlist to one and none at all to the other. What is sold is the share of answers naming you, on a fixed question set, measured identically before and after.
Questions
Frequently asked
What does a GEO consultant do for an e-commerce store?
Measures how often AI answer engines name the store across the questions its buyers actually ask, identifies which competitors are named instead and which sources the engines cite in that category, then changes what the site publishes — delivery windows, stock, prices, assortment — so the facts an answer needs are present and checkable. Finally, re-measures in the identical mode.
Is GEO different from SEO for an online store?
The technical foundations overlap almost entirely. What differs is the target and the measurement: a citation inside an answer rather than a position on a page, reported as a share of repeated runs rather than a rank. Much of the work is product-data hygiene that good SEO would want anyway.
Which engine matters more for a retailer?
It depends on what kind of retailer. In a measured category ChatGPT named marketplaces, chains and official brand channels; Perplexity named those plus independent stores. For an independent the realistic entry point is Perplexity. For a product business overall, ChatGPT carried the great majority of measured arrivals on a reference deployment — which is why it is measured rather than assumed.
How should a delivery promise be written?
With four elements: duration, cut-off time, timezone and city — and a stated consequence for orders placed after the cut-off. Engines compare the cut-off against the buyer's current local time and re-order their recommendation on the result, so a promise without a timezone cannot be used and a page silent about late orders drops out of evening answers.
How long before anything changes?
Weeks, not days. Between publishing and appearing in answers sit crawl, index and retrieval. A measurement taken eleven days after a large publication showed nothing from that layer while other work from the same period was already cited. Every engagement includes a free follow-up measurement four weeks after the final one.
What if nothing moves?
If the questions qualified as winnable at baseline show no increase in presence rate, the next sprint is unbilled. Questions flagged unwinnable at baseline are excluded, which is why they are named in writing before payment.
Find out whether your category is winnable
Send your store and three or four questions your buyers actually ask. The free check comes back in two working days with the eight runs, the stores named instead of yours, and the domains the engines cited.
alex@citedlayer.com