From Peec or Profound Data to AI Citations: A 5-Step Playbook (2026)

The source/domain gap report, the third-party sites citing your competitors but not you. Because AI engines cite off-domain sources far more often than your own site, that report is effectively your action roadmap: it names the reviews sites, community threads, editorial roundups and reference pages the engines already trust for your category, with the ones citing competitors but not you flagged.

AI-search value is mostly in the mention inside the answer, not the click; click-through from AI summaries is low by design. Judge progress by share of voice on buying-intent prompts and by inbound that references being mentioned in ChatGPT or Perplexity, not by raw sessions. A rising visibility score with flat traffic is normal and isn't a failure. It means you're being seen inside answers.

It means the engine found your page but couldn't confidently extract an attributable answer from it, an extraction problem, not an authority problem, and the cheapest fix on the board. Fix it with content shape: answer-first sections that lead with a one-sentence answer, atomic paragraphs, comparison tables, FAQs, and making sure the content is in the raw HTML rather than rendered only by JavaScript, because most AI crawlers don't execute scripts.

Continuously. Re-run the gap reports on a regular cadence (monthly is common) because answers, competitors and cited sources shift week to week, and citations decay as content ages. Treat AI-search optimisation as a recurring programme that compounds, not a one-off campaign that flattens out.

You can, if you have the content and off-site capacity to sustain it. Most teams find the recurring volume (rewrites, new pages, review profiles, community participation and editorial outreach across dozens of priority prompts every month) is the bottleneck, which is where a done-for-you execution layer like Schmitdy comes in: it works the dashboard's gap list for you, human-reviewed.