AI Visibility Audit
When a buyer asks ChatGPT or Perplexity to recommend a product like yours, the model answers from what it already learned, and you do not get to see that answer unless you go looking. An AI visibility audit goes looking. It tells you whether AI engines mention you, get your facts right, and cite your site, or hand the recommendation to a competitor.
The Challenge Brands Face
AI answer engines do not read your marketing the way you wrote it. They blend whatever they absorbed about your category into a single confident answer, and that answer can be wrong in quiet ways: an outdated price, a feature you dropped, a competitor listed as the safe default, or your brand left out of the shortlist entirely. You rarely find out, because nobody forwards you the chat where you lost the deal.
Even when you suspect a problem, it is hard to act on a hunch. Knowing that ChatGPT once described you wrong does not tell you which topics it misses, how often, at which stage of the buyer journey, or whether fixing your own site would even change the answer. What is missing is measurement: a repeatable way to score how well AI engines know you and turn each gap into a specific thing to fix.
AI engines are forming default recommendations for whole categories right now, and in Indonesia buyers are adopting them fast. The brand a model names today tends to be the brand it keeps naming, because each answer reinforces the pattern. Measuring your AI visibility early gives you time to close coverage and accuracy gaps before a competitor becomes the locked-in default answer.
Our Approach
Set up a Knowledge Profile and truth set
We start by building a Knowledge Profile: your brand name, type, industry, description, products, competitors, and aliases, plus a definition of your target audience. We then crawl your own site to use as the truth set, the reference the evaluator checks AI answers against. This is what lets us tell the difference between an AI engine being wrong and your brand simply being unknown.
Run category prompts across every engine
We run real category prompts grouped by buyer-funnel stage — discovery, consideration, and decision — across Gemini, DeepSeek, Claude, ChatGPT and Perplexity. For each prompt we evaluate four things: information coverage versus missing topics, information accuracy with a verdict of correct, unverifiable, outdated, or incorrect, citation presence including which other domains get cited, and subject visibility including your share of voice against competitors.
Score and convert gaps into action items
We report four metrics — mention rate, citation rate, information completeness, and information accuracy — each with a 95% confidence range and broken down by funnel stage. Every finding becomes an auto-generated action item with an effort level and priority, such as cover a missing topic, correct an outdated claim, or get your site cited in AI answers. Social listening and sentiment signals about your brand and category also feed the picture.
What You Receive
How We Prove Progress
During the optimization period — before conversions fully materialize — these are the metrics we use as proof that the strategy is moving in the right direction.
Who This Is Designed For
This service works best for:
- Brands in competitive categories where AI engines pick a default recommendation
- Founders who have seen AI describe their product with wrong or outdated facts
- Marketing teams that want share of voice inside AI answers, not just rankings
- UMKM new to AI search who want to know if they show up at all
What to Expect
You learn exactly where AI engines misrepresent or ignore you, and what to do about each gap.
Setup of the Knowledge Profile and first scan usually lands within one to two weeks, depending on how many prompts and engines we run. We need your brand details and website to begin.
Questions About AI Visibility Audit
How do I know if AI engines recommend my brand?
An AI visibility audit tells you directly by running real buyer questions through Gemini, DeepSeek, Claude, ChatGPT and Perplexity and recording how each one answers. It measures whether your brand is mentioned at all, your share of voice against competitors, whether your facts are stated correctly, and whether your own site is cited as a source. The result is four metrics (mention rate, citation rate, information completeness, and information accuracy) plus a per-prompt breakdown.
What metrics does an AI visibility audit report?
Four, each scored per answer: mention rate (the share of answers that name you), citation rate (the share whose cited sources include your own domain), information completeness (0 to 100, how many of the facts the answer should contain it covers), and information accuracy (0 to 100, every claim checked against your facts: correct scores 100, outdated 50, wrong 0). There is no single blended score. We also break the results down by buyer-funnel stage — discovery, consideration, and decision — so you can see whether the gaps are at the top or bottom of the journey.
What happens if an AI engine states something wrong about my brand?
The audit flags it with a verdict and a fix. Each questionable claim is marked correct, unverifiable, outdated, or incorrect, with a severity level and the exact correction needed, checked against the truth set we built from your own site. That flag then becomes an action item with an effort level and priority, so a wrong claim turns into a specific task rather than a vague worry.
What do you need from me to run the audit?
We need a brand profile and your website. The Knowledge Profile covers your brand name, type, industry, description, products, competitors, and aliases, and we ask you to define your target audience. We then crawl your site to build the truth set the evaluator uses. With those in place we can run the category prompts and produce your score and action items.
Interested? Let's Talk.
We start with a short conversation — no template pitch, no generic proposal. We want to understand your brand first.
Or WhatsApp us: +62 819-7712-1092