Get your business named by ChatGPT, Perplexity and AI Mode

Half of US shoppers research with AI, and that traffic converts better. Build the feed, review and schema setup that gets your business into those answers.

RunbookJune 9, 20265 min read
~/runbook $ cat semrush.md[briefing]
>_// Writing & SEO
93 lines · writing-seo.md0x2297

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By the end of this build you'll have your business sitting inside the data ChatGPT, Perplexity and Google AI Mode read from when they name a business: a feed they can pull, a Google Business Profile they trust, schema they can parse, and fresh reviews. The stack is free feeds, a schema plugin, and a review habit. Most of it takes an afternoon. Here's why this works differently from blue-link search, then what to wire up.

A growing share of buying now starts with a question to an AI, not a search box. In a 2025 Adobe survey, 53% of US consumers said they had used AI to research a purchase, and Adobe's analysis of more than a trillion retail visits found AI-driven traffic up several times over during the 2025 holiday season, converting roughly a third better than other channels. So when the AI names someone, how does it pick, and how do you get named?

What you'll build

A setup that makes you legible to the assistants and worth quoting:

  • A product or business feed the shopping answers actually read.
  • A Google Business Profile and schema that let the model parse you cleanly.
  • A review and mention habit that gives the model a reason to trust you.
  • A capture layer so the ready buyer it sends doesn't bounce.

Stack

All three big assistants turned recommendation into a core feature in the last eighteen months. Each reads from structured data plus trusted third-party sources.

  • ChatGPT added shopping research in 2025 with sourced product details and comparisons. It briefly tested in-app checkout, then in March 2026 went back to sending people to the merchant's own site to buy. (CNBC reported the pivot.) Discovery stayed. Checkout moved back to you.
  • Perplexity built a shopping flow with in-chat checkout and a merchant program for catalogs, specs, and reviews. It leans heavily on reviews when it answers.
  • Google AI Mode combines Gemini with a Shopping Graph of tens of billions of listings, and in January 2026 added new Merchant Center attributes and a business-chat agent aimed at conversational queries. (Google's announcement has the detail.)

The build sits on free feeds, a schema plugin, and a review habit. Two named tools show up later: Semrush surfaces which queries the assistants pull you into, and Surfer helps you brief the pages they cite.

53%
US consumers using AI to research a purchase
~33%
Better conversion than other channels

On the surfaces and in the stack

Perplexity logoPerplexitymerchant program for catalogs and reviews
Semrush logoSemrushsee which queries the assistants pull you into
Surfer logoSurferbrief the pages they cite

Steps

You don't chase every platform. You build to be clean, fed, and reviewed. In order:

The build, in order

1

Get into the feeds

If you sell products, set up a Google Merchant Center feed and enroll in Perplexity's merchant program. This is the single biggest lever for product recommendations, and it's plumbing, not marketing. No feed, no mention.
2

Fix your Google Business Profile

For anything local, AI surfaces weight a complete, fresh profile: right hours, real photos, current services, recent reviews. Update it like a storefront window, because to the AI it is one.
3

Add the basic schema

LocalBusiness, Product, Review, and FAQ markup help the systems parse and trust your pages. On a mainstream platform, a plugin handles most of it.
4

Make reviews a habit, not a campaign

Ask every happy customer for a Google review, every time. Perplexity references reviews in close to every product recommendation, and a business with fifteen stale reviews is easy to pass over for one with two hundred fresh ones. Wire the ask into whatever CRM you already run so it fires after every job.
5

Build pages the assistants can quote

Use a rank tool like Semrush to find the questions buyers ask the AI, then brief each page with Surfer so the answer sits near the top with real specifics. Recognizable, often-mentioned sources are what the model repeats.

Your move this week

Pick the one feed that matches your business. Merchant Center if you sell products, a fully updated Google Business Profile if you're local. Then send a review request to your last ten happy customers. Those two actions put you into the exact data these assistants read from.

The part that breaks

The second trap is treating AI traffic as too small to bother with. Most analytics setups don't tag AI referrals yet, so a lot of owners can't see it, then assume it's zero. The people who arrive after an AI pointed them your way show up half-sold, which is why they convert better. Build for the channel while it's still quiet.

It's the same legibility problem that decides whether you show up in Google's AI Overviews for a small business, and it pairs with building a name people search for.

Do the free basics first. The feed, the profile, the schema, and the reviews are the build.

Copy this

A review-request message you can drop into your CRM automation, sent the day after a job closes:

Hi [first name], thanks for choosing us.
If we did right by you, a quick Google review helps
more than you'd think: [direct review link]
Takes 30 seconds and it means a lot. Thank you.

One link, no friction. Volume of fresh reviews is the signal the assistants weight.

Upgrade path

Once feeds, profile, schema, and reviews are live:

  • Route AI-sent and ad-sent leads into one inbox with instant follow-up, because the checkout is moving back to your site and a recommendation only counts if it turns into a booking. The wiring for that lives in sending leads straight to your CRM with Make.
  • Get mentioned where the AI reads: an honest comparison listing, a Reddit thread where real people vouch for you. You can't fake this, which is exactly why the model trusts it.

This pairs with the capture logic in the Meta Advantage+ build. The writing and SEO hub tracks the shift as it moves.

Frequently asked questions

Do people really shop through AI assistants now?

Enough to matter. An Adobe survey in 2025 found 53% of US consumers had used AI for shopping research, and Adobe measured AI-driven retail traffic up sharply over the 2025 holiday season, converting around a third better than other channels. It is growing fast and the visitors buy.

How does an AI assistant decide which business to recommend?

It pulls from structured product and business data (Google Merchant Center, schema markup, Google Business Profile) and from third-party sources it trusts (reviews, comparison sites, Reddit, press). Perplexity references reviews in nearly every product answer. Messy or missing data is easy to skip.

Is this different from normal SEO?

It overlaps but is not the same. Classic SEO chases a ranking position. AI recommendation is about being a clean, well-reviewed, frequently-mentioned source the model can quote with confidence. Being known and machine-readable matters more than a single keyword ranking.

What is the fastest thing a small business can do?

Two things. Get a product feed into Google Merchant Center if you sell products, and run a steady habit of asking happy customers for Google reviews. Both feed directly into what AI surfaces show, and neither needs a developer.

About Runbook

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