Can you explain how to boost my company's visibility in AI-driven search engines like ChatGPT and Perplexity?
Our agency's explanation of how to boost your company's visibility in AI-driven search engines like ChatGPT and Perplexity, from bot access to citations and reporting.
Companies usually ask this after a competitor shows up in a ChatGPT answer and they do not. It is a fair worry, and it has a practical answer. Visibility in ChatGPT and Perplexity comes from access, authority and content, and all three can be measured. What nobody can honestly sell you is a guaranteed recommendation. Here is the order we work in with clients.
First, check that the bots can get in
This is the cheapest fix and the most frequently skipped. We look at robots.txt and server or CDN logs for the real bot names: GPTBot, OAI-SearchBot and ChatGPT-User from OpenAI, ClaudeBot, Claude-User and Claude-SearchBot from Anthropic, PerplexityBot and Perplexity-User, plus Google-Agent and GoogleOther. OpenAI and Perplexity both publish documentation about their bots. We read it with the client, because different bots serve different purposes, and blocking the wrong one by accident is an avoidable own goal.
Then the pages. Content that appears only after a script runs, content behind a gate and pages that error for non-browser visitors can all vanish from AI answers. In Promptwatch, Agent Analytics gives us IP-verified crawler logs with a crawl-to-citation path and error tracking with failure explanations, so we are not inferring access from a robots.txt file. Crawler logs start on the Professional plan, and we scope that in from the start when access is a suspected problem.
Second, decide what to be visible for
We build a list of the questions the client's buyers ask: category questions, comparisons, "best X for Y" prompts and problem questions. Promptwatch tracks these daily per model, country and language. AI systems usually break a prompt into narrower searches, called query fan-outs, and the fan-outs tell us which sub-questions and sources matter. We use them to extend the list.
Third, fix the content
We keep the advice plain, because the plain version works:
- Answer the question near the top of the page, in simple language.
- Keep pricing, comparison and policy pages accurate and current.
- Give each important question its own clear page.
- Use clean headings and structured data so machines can parse the page.
We do not tell clients that markup alone raises citations. We have no sourced evidence for that, so we describe it as good hygiene. Content gap analysis in Promptwatch shows which prompts the site does not cover, and Content Refresh suggests diff-style updates for existing pages. For Business clients, the Content Agent can plan, write and publish against gaps with a review inbox, so nothing goes live unreviewed unless the client opts into hands-off mode.
Fourth, earn mentions where engines look
Engines lean on sources outside the client's own site: review platforms, publications, community threads and directories. Citation analytics in Promptwatch show which domains and pages appear for the client's prompts, including Reddit, YouTube and LinkedIn reports and offsite mentions where the brand is named without a link. If a competitor is cited from a source our client is absent from, that source goes on the outreach list.
Fifth, measure and repeat
Each month we report visibility score, share of voice, sentiment and position in answer for the prompt set, the pages being cited, and AI-referred visits and conversions from visitor analytics. We track competitors alongside, because share of voice is relative. We keep a change log so we can tell our own work apart from model changes.
What we tell clients to expect
- Early weeks: a baseline and a list of fixes. Little movement.
- First months: access issues resolved, gaps being filled, first citations appearing for some prompts.
- Ongoing: a monthly loop of measuring, fixing and re-measuring.
We do not promise timelines for a specific recommendation, because they depend on the category, the competition and decisions made by the engines.
Why we do this on one platform
Each step needs different data: logs for access, tracking for presence, citations for authority, analytics for outcomes. When those live in four tools, the team spends its time reconciling them. We run client programs on Promptwatch because all four are in the same product, and the same prompt set drives all of them. That makes the monthly report a review of one dataset instead of a negotiation between several.