Who’s Asking?

For most of this industry’s history, the buyer journey was thought of as one person moving through one path: search, browse a few manufacturer sites, call a rep, get a quote. A single line, a single decision-maker at a time.

That was never quite true, and AI has made the gap impossible to ignore. A single product doesn’t get asked about once. It gets asked about seven different ways, by seven different people, often in the same week, and increasingly all of it starts with a prompt instead of a phone call.

What Are They Really Asking?

This is where most of the surprises happen. The prompts buyers actually type are narrow, technical, and specific, nothing like the “best flooring adhesive” searches most brands optimize for. Even the simplest ones carry more than they say: a search like “where to buy [product] today” usually comes with urgency, a need for local supply, a question about availability, and often a crew that’s already scheduled. Every one of these questions is answerable, as long as the information exists somewhere AI can read it. Here are the four types of prompts where that matters most, and what it takes to win each one.

What Else Does AI Need to Know?

Competing for AI search visibility requires more than a general product description.

Identify your closest competitors and the products that compete directly against your own. Then strengthen the information that helps buyers make those comparisons.

Spec vs. Spec

Get your specs visible on your own product pages. Very few distributors do this, even though manufacturers often do. Don’t assume that because the manufacturer already shows the specs, you don’t need to. If your pages don’t show them, put the specs front and center, visible and indexable (readable by search engines and AI).

The Fix

Many AI searches in this industry are about something going wrong: uncertainty about dry time or cure time, why something failed, how to remove it. Teach installation processes and procedures where your product avoids the competitor’s known failure points, and be specific about where theirs falls short.

The Stock Check

Availability, jobsite delivery, service level agreements, and delivery routes. Even without exact inventory numbers, being clear and consistent about your core in-stock brands and your delivery turnaround improves how you perform in AI results.

When several local suppliers carry similar products, AI steers buyers to what it can verify: who has it, where, and how fast.

How Does AI Learn About You?

AI search visibility depends partly on the information available on your website and partly on what other sources say about you.

Your product information should be structured, consistent, and accessible in readable text.

On Your Website

Start with product specifications, searchable pages, technical documentation, structured data, and discoverable URLs.

Product Schema Fields

Structured product information helps describe technical attributes, physical dimensions, and compliance characteristics.

Other Website Discovery Signals

• XML sitemaps: Help search engines discover important website URLs.
• Google Search Console: Submit sitemaps and inspect indexing status.
• Bing Webmaster Tools: Support discovery through Bing’s search ecosystem.
• llms.txt: An emerging convention for describing useful AI-facing resources, without guaranteed citation benefits.

On Your Website

• Structured product data, specs in labeled fields, not paragraphs and PDFs
• Sitemap, submitted to Google Search Console and Bing Webmaster Tools
• llms.txt file, specially crafted for AI crawlers
• Product schema markup in HTML code

None of these sources works in isolation. Consistent information across multiple websites helps reduce confusion about products and brands.

A product name spelled three different ways across three websites may create ambiguity about whether those references describe the same product.