SMBs Track Google, Reviews, and Ads. Now Track AI Recommendations.

Small and medium-sized companies already know how to watch the channels that bring customers in.

You check Google rankings. You monitor reviews. You look at ad performance. You compare your website traffic against last month. You know which competitors show up when someone searches your category.

That work still matters.

But there is a new discovery channel most companies cannot see clearly yet: AI recommendations.

When someone asks ChatGPT or Gemini which product to buy, which service provider to choose, or which local business is worth considering, the answer is not a traditional search results page. It is a recommendation, a shortlist, a comparison, or a direct explanation of which brand fits the person asking.

That creates a simple question for every growing company:

When AI assistants recommend brands in your category, do they recommend yours?

SonarLens helps answer that question with structured reports across ChatGPT and Gemini. No guesswork. No subscription required for a one-off study. Just a practical report showing where your brand appears, who else gets recommended, what sources are influencing the answers, and what you can do next.

AI recommendations are not the same as SEO rankings

It is tempting to treat AI visibility like another version of SEO.

That is understandable. Both are about discovery. Both are shaped by online information. Both can influence whether a customer finds you or a competitor.

But the measurement problem is different.

Google search usually gives people a list of links. Your question is often:

• Do we rank?
• Where do we rank?
• Which page is showing?
• Which competitor is above us?
• What search terms are driving traffic?

AI assistants work differently. When someone asks ChatGPT or Gemini for advice, the model may synthesize information from many places and produce a direct answer. The customer may not click through ten pages. They may read the recommendation and use it as a shortlist.

That means the questions change:

• Does AI recommend our brand at all?
• Are we a top recommendation or an occasional mention?
• Which competitors are recommended more often?
• What reasons does AI give for choosing us or not choosing us?
• Which sources are being used to support the answer?
• Do ChatGPT and Gemini agree, or do they favor different brands?
• Does the recommendation change for different types of customers?

A high Google ranking does not automatically mean you will be recommended by AI. A strong review profile does not guarantee that your brand will be framed as the best fit. A well-known competitor may appear more often because the model has more context about them, more third-party sources, or clearer positioning for a specific customer need.

For SMBs, that matters because you do not have unlimited budget to chase every channel. You need to know where the problem actually is.

The blind spot: you cannot measure AI recommendations by asking once

A common first step is manual testing.

You open ChatGPT or Gemini and ask a question like:

• What is the best accounting software for a small business?
• Which agency should I hire for local SEO?
• What running shoes are good for beginners?
• Which skincare brand is good for sensitive skin?
• What restaurant should I try in this area?

If your brand appears, it feels like good news. If it does not, it feels like a warning.

But one answer is not enough.

AI recommendations can vary based on the wording of the question, the model being used, the person being represented, and the type of need described. A general buyer may get one answer. A budget-conscious buyer may get another. A first-time buyer may see different recommendations than an experienced user. A parent, founder, student, homeowner, runner, or regional customer may be pointed toward different options.

That is why SonarLens does not rely on one prompt and one answer.

A SonarLens study runs structured queries across a panel of realistic profiles, then compares the recommendations across ChatGPT and Gemini. The goal is not to see whether your brand appears once. The goal is to understand your AI recommendation position across the kinds of customers you actually care about.

Why audience profiles matter

Most companies do not sell to a generic customer.

Even a small business usually has segments:

• Budget-sensitive buyers
• Premium buyers
• First-time buyers
• Repeat customers
• Local customers
• Customers with specific requirements
• Customers comparing you against a known competitor
• Customers who care about speed, service, quality, price, trust, sustainability, or specialization

AI assistants respond to that context.

If a customer asks for a recommendation and includes their needs, constraints, preferences, or location, the answer may change. The model is not only naming popular brands. It is trying to match a brand to a situation.

That is where many SMBs can either win or lose.

A larger competitor may be recommended in broad category questions because it is better known. But your company may be a stronger fit for a specific segment: a local buyer, a niche use case, a budget range, a service requirement, or a customer who values hands-on support.

You will not see that by asking a generic question once.

With SonarLens, you describe the audience you want to study in plain language. SonarLens generates realistic profiles based on real panel data, each with demographic, psychographic, and lifestyle context. It then queries ChatGPT and Gemini as those profiles, so you can see how recommendations change across different kinds of people.

That gives you a more practical view of AI visibility:

• Where your brand is already a good fit
• Which customer types are being pointed to competitors
• What reasons AI gives for those choices
• Which positioning gaps may be holding you back
• Which sources may be shaping the answer

For an SMB, this is often more useful than a generic visibility score. You need to know who you are winning with, who you are losing with, and why.

What a SonarLens report shows

A SonarLens report is designed to turn AI recommendations into something you can actually inspect.

Instead of manually copying answers from ChatGPT and Gemini into a spreadsheet, you get a structured report that summarizes what happened across the study.

A report can show:

Top recommendations

See which brands or products were recommended most often across the responses.

This helps you understand whether your brand is a frequent recommendation, an occasional mention, or absent from the shortlist. It also shows which competitors are taking the most AI recommendation share in the study.

Audience breakdown

See how recommendations change across different profiles and segments.

This is where the report becomes especially useful for SMBs. You may find that your brand performs better with one audience than another, or that a competitor dominates a segment you expected to win.

ChatGPT vs. Gemini comparison

Different AI models can produce different recommendations.

A SonarLens report shows where ChatGPT and Gemini agree, where they diverge, and whether your brand performs differently across models. That helps you avoid drawing conclusions from one assistant alone.

Brand and product details

The report summarizes how brands are described, including common strengths, concerns, and the types of customers they appear to fit.

For your own brand, this can reveal whether AI understands your positioning. For competitors, it can show what they are being credited for.

Sources

AI recommendations are shaped by information available across the web. SonarLens reports show the websites and articles AI cited, ranked by frequency, with links.

For SMBs, this is one of the most actionable parts of the report. It can help you identify which third-party pages, review sites, articles, comparison pages, or other sources are influencing the category conversation.

Model agreement

If both ChatGPT and Gemini recommend the same competitor, that is different from one model making an isolated choice.

Model agreement helps you understand which recommendations are consistent and which are model-specific.

Key findings and detailed summary

SonarLens also provides auto-generated takeaways and a narrative summary so you can move from raw results to interpretation quickly.

The point is not just to collect AI answers. The point is to see patterns.

What an SMB can do with the findings

A SonarLens report is useful because it points to practical next actions.

Depending on what the study shows, you might decide to:

• Update key website pages so your positioning is clearer
• Strengthen content around specific customer needs
• Improve how your product or service pages explain who you are best for
• Address recurring concerns that AI associates with your brand
• Build or refresh comparison content
• Prioritize third-party sources that appear frequently in AI answers
• Monitor competitors that show up more often than expected
• Test whether different customer segments see different recommendations
• Run a follow-up study after a campaign, content update, or PR push

This is not about chasing AI for the sake of it. It is about finding the specific places where your brand is underrepresented, misunderstood, or being beaten by competitors in a new recommendation channel.

For small and medium-sized companies, that clarity matters. You may not need a large ongoing program on day one. You may just need to know whether there is a problem, where it is, and what to work on first.

Pay per report, no subscription required

Many SMBs do not want another platform subscription just to answer one strategic question.

SonarLens supports pay-per-report studies, so you can run a one-off analysis without committing to a subscription.

You choose the report size based on how broad you want the study to be:

• Small: 50 profiles
• Medium: 100 profiles
• Large: 200 profiles

You can also add brand deep-dives when you want a closer look at specific brands, including your own or key competitors.

For teams that later want recurring monitoring, tracker subscriptions are available. But you do not need to start there.

A single report can already help you answer important questions:

• Are we being recommended by ChatGPT and Gemini?
• Which competitors appear most often?
• What customer segments do we win or lose?
• What reasons does AI give?
• Which sources are shaping the recommendations?
• What should we do next?

That is enough to move from speculation to action.

AI recommendations are now part of brand visibility

Customers still use Google. They still read reviews. They still click ads. None of that is going away.

But AI assistants are becoming another place where purchase decisions begin. For SMBs, the risk is not that every customer suddenly stops searching. The risk is that a growing share of discovery happens in a channel you are not measuring.

If ChatGPT or Gemini recommends your competitor more often than you, you need to know.

If AI describes your brand inaccurately, you need to know.

If your strongest customer segment is not being matched to your brand, you need to know.

And if the sources shaping AI answers are not the ones you are watching today, you need to know that too.

SonarLens gives you a practical way to see it.

Run a study on sonarlens.com and find out whether AI recommends your brand, which competitors it favors, and what actions are worth taking next.