Automate AEO with Letaido: 6 techniques to be cited by AI
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A client calls me. 5,200 sheets. Zero citations on ChatGPT.
Lucas runs a high-end furniture site. 3,200 product sheets. Sheets that perform well on Google. But one morning, he types « best convertible sofa 2026 » into ChatGPT.
His company doesn’t appear. Not even at the end of the list.
He tries Perplexity, Gemini. Nothing.
He calls me on a Thursday afternoon. His question is simple: « Stéphane, how many sales am I losing each day without knowing? »
How many? Hard to say exactly. But 3,200 well-written sheets can remain completely invisible to assistants if no one verifies what they display. And doing it manually for a large catalog is impossible.
I set up the 6 automations I detail here. Result in 6 weeks: 47 citations across ChatGPT, Claude, Gemini, and AI Overviews. Without rewriting a single sheet. Without manual work.
XXL catalog and AI: why manual doesn’t hold up
AI assistants don’t crawl like Google. They don’t rank pages—they assemble trusted sources to answer. Your product sheet can be perfect for Google but miss the format ChatGPT or Gemini expect to recommend a brand.
With 10,000, 5,000, or even 1,500 products, manual tracking becomes a mirage:
- answers change each week, sometimes daily;
- each assistant has its own source preferences;
- a tiny rewording of the question can swing recommendations;
- competition moves—a site that wasn’t ranked next to you two days ago is there today.
With my e-commerce clients, I observe a recurring pattern: brands present on Google but absent from assistants, simply because no system detects the window when it opens. Automation isn’t a luxury—it’s the foundation.
Here’s how Letaido’s automation system works, step by step, to turn a product catalog into an AI-cited source.
The 6-step automation engine for AEO
From prompt identification to continuous monitoring
Technique 1: Identify prompts worth targeting
The first thing I did for Lucas was not aim at every prompt. Impossible. We looked for the ones that truly matter.
Letaido starts with a few product catégories (« convertible sofa », « extending table », « designer lighting »). Its Brand Radar module surfaces real questions people ask assistants, not guesses. Then it cross-references that volume with Google demand (Keywords Explorer) to estimate the actual frequency of each query in an AI environment.
The calculation is smart: if ChatGPT represents roughly 30% of users versus Google, a prompt hitting 1,000 searches/month on Google would mean about 300 inquiries on ChatGPT. Letaido applies this ratio to rank opportunities by commercial potential.
For a 3,200-reference catalog, we isolated 78 priority prompts. Not 1,500. 78. The time savings are enormous.
From there, you know where to focus energy.
Technique 2: Measure your share of voice on each assistant
With the list of 78 prompts, we measure how often Lucas’s brand appears versus competitors. No guesswork.
Letaido queries major assistants (ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, Copilot) simultaneously and counts citations. You get a clear table: for « best budget corner sofa », the brand appeared in 1 out of 6 responses on ChatGPT, but never on Gemini.
Share of voice reveals precise gaps. You immediately know which assistant you’re missing from, and for which prompt.
For Lucas: 12% share of voice across the 78 prompts, all assistants combined. 0% on 31 of them. It’s painful, but it’s a clear starting point.
Technique 3: Monitor citations continuously
Now that you’ve got the snapshot, set up automatic monitoring.
Letaido re-runs the same prompts at regular intervals (daily, weekly, as you choose) and compares results. When a mention drops or an unidentified competitor appears, the tool can send an alert via Slack or email.
Done checking 78 prompts every morning. The system alerts you when something happens.
For Lucas, we caught three events in two weeks: a competitor suddenly monopolized « 8-person extending table » on Gemini, and a product sheet whose price had changed was no longer cited on ChatGPT. Without the alert, it would have taken weeks to spot.
Techniques 4 & 5: Optimize product sheets and structured data at scale
Being cited isn’t just about presence. Format matters too. Assistants pull from well-structured data with clear labels, factual descriptions, and precise attributes.
Letaido can, on demand, take a product sheet and reformat it for an assistant. Not for classic SEO, but for smart scraping. It generates concise titles, descriptions enriched with key specs, and injects Product, FAQ, and Review structured data in JSON-LD on the fly.
For Lucas, this dual effect was the breakthrough. We treated the 500 most important sheets—those tied to the 78 prompts. Titles in « question/answer » language, standardized property fields, correct schema markup.
Result: within days, 32 citations on the optimized sheets that had been invisible before. An automation that runs without manual intervention, just by programming the script once.
Technique 6: Program alerts and regular checks
The last piece of the puzzle is the flight plan. You don’t launch automations and forget.
You set up recurring tasks:
- weekly check of the 78 priority prompts with Slack report;
- monthly expanded scan of 250 prompts to spot new opportunities;
- automatic regeneration of structured data if a sheet is modified.
With this system, Lucas’s team spends zero hours a week on AEO. Reports arrive, they click if an anomaly is flagged. Otherwise, nothing. Silence is the goal.
Automation transforms AEO into lean workflow, like your email campaigns or product feeds.
From 0 to 47 citations. Effortlessly. It’s possible.
Lucas didn’t hire an AEO manager. He didn’t produce extra content. He used automations to make his catalog readable by AI assistants.
In 6 weeks, his site earned 47 citations across 6 major platforms, including 12 on ChatGPT for high-intent commercial queries. Revenue from traffic via these assistants is estimated at $12,000 over two months.
AEO? A monitoring and optimization system with alerts that runs itself. Not a dance with the GPTs of the day.
And for your catalog, how many lucrative prompts are you leaving on the table without realizing it?
AEO audit of your catalog
In 30 minutes on a live call, I’ll show you which 20% of your product sheets can capture 80% of AI citations. No commitment.
Book a strategic call — 45 minFrequently Asked Questions
What exactly is AEO?
Answer Engine Optimization means making content easily exploitable by AI assistants (ChatGPT, Gemini, Perplexity…). The idea: be the source they cite, not the first result on a SERP.
Why automate AEO for e-commerce?
With hundreds or thousands of sheets, manual monitoring of AI responses doesn’t work. Automation spots prompts that matter, measures share of voice continuously, and self-corrects without anyone stepping in.
Does Letaido really suit very large catalogs?
Yes. Letaido can handle batch processing of hundreds of sheets, generate structured data and optimized titles at scale. For a client with 3,200 references, optimizing 500 strategic sheets took one day of configuration, then everything ran automatically.
Which AI assistants does Letaido monitor?
It queries ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, and Copilot. Coverage expands with tool updates.
How long before you see AEO results?
With proper automation, first citations arrive within 48 hours on optimized sheets. In one client case, I counted 47 citations across all assistants in 6 weeks.
