How Javvo gets your business recommended by AI

Javvo measures how you show up in AI answers, audits the five levers that drive AI recommendations, and builds the plan that wins you new customers. This work is called Answer Engine Optimization (AEO), also known as Generative Engine Optimization (GEO).

The Five Levers of AI Visibility

We do a deep audit across the five levers that determine AI recommendations, and produce an action list that shows the strengths worth defending and the gaps to fix. Then we do the work with you and deliver measurable results.

Technical Foundation

Make your site readable to AI.

AI engines read your site through its structure and its schema, the machine-readable data that states your key facts. When schema is missing or crawlers are blocked, engines fall back on what other sites say about you.

Data Integrity

Ensure your data is trustworthy to AI.

AI answers are only as accurate as the sources behind them. If your facts are inconsistent across the web, engines lose confidence in your data and either stop quoting you or repeat the errors.

Content Optimization

Give AI strong content to quote.

AI engines quote specific, direct answers to specific questions. Where you have no AI-optimized content of your own on a question your customers ask, engines skip you and quote a competitor instead.

Brand Reputation

Shape how AI portrays your brand.

Your reputation is built from online reviews, ratings, and how you and others describe you, all of it picked up by AI. Inaccurate or damaging claims spread the same way, and reach your customers if not addressed promptly.

Earned Authority

Build a strong presence where AI looks.

AI engines lean on a small set of trusted directories, publications, and communities. Being present and standing out across them earns you the authority that decides whether you get recommended.

Measurement you can trust

We test the questions your customers actually ask.

User prompts are built from your business data, your competition, and Google search-demand data. We map them to the buyer journey and focus on winning the high-intent questions asked right before a purchase.

We build complete and accurate competitive sets.

Raw AI engine output is messy. We trace every brand competing with you, including ones you may not be aware of, and resolve the different names AI uses for the same company so each one is counted once.

Our multi-scan method delivers a stable read.

AI answers vary between runs. We run every question several times across each engine and report the pattern across the runs. Every query runs through live web search, so each engine answers from the current web rather than its training data.

We track the AI engines your customers use.

We measure your AI visibility across ChatGPT, Gemini, Perplexity, and Google AI Overviews, together covering the large majority of AI search in the US. We add Claude and Microsoft Copilot when it makes sense for your business.

Led by people, accelerated by AI

Our team learns your business, sets the strategy, and reviews everything before it ships. AI agents assist with execution, so we get the work done in days or weeks rather than months, without big-agency overhead.

Book a discovery call and get a free AI Visibility Snapshot

See how AI answers the questions your customers are asking about your business.

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Frequently asked questions about our methodology

How do you decide which questions to test?
We build your question set from your business data, your competitive landscape, and Google search-demand data, then map each question to a stage in the buyer journey. You review and confirm the set before anything runs, and you can add questions you know your customers ask.
Why run the same question more than once?
AI engines do not return the same answer every time. Asking once gives you a single result that may not repeat, so a change between scans can be variance rather than progress. Running every question multiple times on every engine gives you the pattern, which is what you can act on.
How do you know the answers reflect the current web and not the model's training data?
Every query runs with live web search enabled, so each engine retrieves and answers from what is published now. This matters because training data can be months old, and a business that fixed its site last quarter would still be measured on last year's web.
How do you count mentions when AI names a company in different ways?
AI answers refer to the same company by its brand name, its legal name, its products, and its people, often within one answer. Our data-cleansing method traces each of those back to the company behind it and counts that company once, and filters generic phrases that may look like brand mentions. Without this step, share of voice is inflated for some competitors and understated for others.
Can I see the questions and answers behind the numbers?
Yes. Your report includes an appendix listing every question tested, on every engine, with the businesses each answer recommended. The numbers are traceable to the answers that produced them.
Can I compare my results month over month?
Yes. Every re-scan uses the same core question set and competitor set, so movement reflects real change rather than a change in what we measured. We also scan monthly for new customer questions and for competitors entering or leaving your market.
Can you guarantee my business will show up in AI answers?
No, and any vendor promising guaranteed AI visibility is selling something they cannot deliver. What AEO does is raise the probability, by optimizing your whole online presence: your site, your data, your content, and the third-party sources AI reads, which takes real strategy. And because engines update their models, competitors make new moves, and customer sentiment changes, holding a lead takes ongoing work rather than a one-time fix.