How We Helped a Pet Services Business Get Mentioned by ChatGPT

One of the most common questions we hear from business owners is "How do I get my business mentioned by ChatGPT?" or "Why does ChatGPT recommend my competitor but not me?" This case study walks through the methodology we applied for a pet services business that was completely invisible in AI search results and what happened after we optimized their online presence for AI visibility.

We are keeping the business name anonymous at their request, but the methodology and results are real.

The Starting Point

The business is an established pet services company operating in a major Indian metro city. They offer pet grooming, boarding, veterinary consultations, and pet supplies. They had been in business for over six years with a strong local reputation, good Google reviews (4.6 stars, 200-plus reviews), and a website that ranked decently for local SEO keywords.

Despite all of this, when we ran AI visibility queries across ChatGPT, Perplexity, Google AI Overviews, and Copilot — asking questions like "best pet grooming services in [their city]" and "where to board my dog in [their city]" and "recommended pet services near me" — the business did not appear in any AI responses. Not once, across any platform.

Their competitors, including some with fewer reviews and less online presence, were being mentioned. This was the problem we needed to solve.

Why They Were Invisible to AI

After conducting a thorough AEO audit, we identified several clear reasons why AI models were not citing this business.

Their website had zero structured data. No Organization schema, no LocalBusiness schema, no Service schema, no Review schema. Despite having great content on their site, none of it was structured in a way that AI models could easily parse and understand.

Their content was written in typical marketing language — "We provide world-class pet care" and "Your pet deserves the best." These statements are fine for human visitors but give AI models nothing concrete to cite. AI models need factual, specific statements they can confidently include in a response.

They had no llms.txt file. This meant AI crawlers visiting their site had no clear signal about what the business does, what services it offers, or how to categorize it.

Their knowledge graph presence was minimal. While they had a Google Business Profile, they were not listed in major business directories and knowledge bases that AI models frequently reference.

Their FAQ content was essentially non-existent. No FAQ page, no question-and-answer formatted content anywhere on the site. FAQ content is one of the primary formats that AI models extract answers from.

The AEO Strategy We Applied

We developed a focused AEO optimization plan that could be implemented over eight weeks without requiring a complete website redesign.

Phase 1: Structured Data Implementation (Weeks 1 to 2)

We implemented comprehensive schema markup across the entire website. This included Organization schema with complete business information — name, address, phone number, email, founding date, service area, and social media profiles. LocalBusiness schema with geo-coordinates, opening hours, and accepted payment methods. Service schema for each service they offer — grooming, boarding, veterinary consultations, and pet supplies — with descriptions, pricing ranges, and availability. AggregateRating schema pulling from their Google reviews. FAQPage schema for the FAQ content we created in Phase 2.

The goal was to create a complete, machine-readable picture of the business that any AI model could immediately understand.

Phase 2: Content Restructuring (Weeks 2 to 4)

We restructured their website content with AI comprehension as the primary goal. Their homepage was updated to include clear, factual statements about the business — what they do, where they operate, how long they have been in business, and what makes them distinctive. We replaced vague marketing language with specific, citable information.

We created a comprehensive FAQ page with 25 questions and answers covering their services, pricing, process, and policies. Each answer was written to be a self-contained, accurate response that an AI model could extract and use directly.

Each service page was rewritten to include a clear definition of the service, the process involved, pricing information, and frequently asked questions specific to that service. We also added comparison content — "Pet grooming at home vs salon grooming" and "How to choose a pet boarding facility" — because AI models frequently reference comparison and educational content.

Phase 3: llms.txt Implementation (Week 3)

We created and deployed an llms.txt file for their website. This file clearly stated the business name, category, location, services offered, and key differentiators. It also listed the most important pages on the site and their content focus, giving AI crawlers a clear roadmap of the site.

Phase 4: Citation Building (Weeks 3 to 6)

We built citations for the business in sources that AI models are known to reference. This included major business directories such as Justdial, Sulekha, and niche pet service directories, industry-specific platforms and forums, and local city guides and directories.

We also ensured their Google Business Profile was fully optimized with complete information, regular posts, photo updates, and prompt responses to reviews.

Phase 5: Monitoring and Iteration (Weeks 6 to 8)

Starting in week six, we began systematically querying AI platforms with relevant questions to track whether the business was appearing in responses. We tested dozens of query variations across ChatGPT, Perplexity, Google AI Overviews, and Copilot.

What Happened

We want to be honest about the results because AEO is not magic, and outcomes vary significantly.

By week four, we saw the first appearance — the business was mentioned in a Perplexity response to a query about pet grooming services in their city. Perplexity cited their website directly as a source.

By week six, the business began appearing in Google AI Overviews for local pet services queries. This was likely a combination of the AEO work and the structured data improvements, which also benefited their traditional SEO.

By week eight, the business was appearing in ChatGPT responses for approximately 30 percent of the pet services queries we tested for their city. This is not 100 percent coverage, and we want to be clear about that. AI responses vary based on the specific query, the conversation context, and model updates. But going from zero mentions to appearing in roughly one-third of relevant queries in eight weeks was a meaningful improvement.

Their Google organic traffic also increased by about 15 percent during this period, which we attribute primarily to the structured data and content improvements. The AEO work and SEO improvements are interrelated — the same changes that help AI models understand your business also help Google understand it better.

What We Learned

Several things stand out from this project. First, structured data is foundational. Without comprehensive schema markup, AI models simply do not have enough structured information to cite your business confidently. This was the single highest-impact change we made.

Second, content clarity matters enormously. Replacing marketing fluff with clear, specific, factual statements made the content actually useful to AI models. A sentence like "This company provides professional dog grooming, cat grooming, and pet boarding services in Mumbai, serving over 5,000 pets since 2020" gives an AI model something concrete to work with.

Third, AEO results are not instant. Unlike a Google Ads campaign that can drive traffic immediately, AEO is a cumulative process. AI models update their knowledge periodically, and building enough signals for consistent citation takes time.

Fourth, there are no guarantees. We cannot promise any business that they will appear in ChatGPT responses. What we can promise is that the methodology we apply — structured data, content optimization, llms.txt, citation building — significantly increases the probability of AI visibility and provides lasting benefits even beyond AI search.

Is This Methodology Applicable to Your Business?

The approach we used for this pet services business is applicable to virtually any local or national business that wants to improve AI visibility. The specific schema types and content focus will differ based on your industry, but the core methodology remains the same: make your business information clear, structured, and authoritative so that AI models can understand and cite you confidently.

If your business is not appearing in AI search results and you want to explore what AEO optimization could look like for you, the first step is an AI visibility audit. Understanding where you currently stand is essential before implementing any changes.