How to track your brand in Perplexity

To track your brand in Perplexity, send your buyer questions to Perplexity's sonar models — search is always on, with no ungrounded mode to switch — and check each answer plus its search_results and citations fields for your brand. Perplexity attaches more sources per answer than any other engine, which makes it both the most measurable surface and the fastest place to see whether a content change worked.

Last updated 2026-07-28

Why is Perplexity the easiest engine to measure?

Because it cannot be measured ungrounded. The sonar models are retrieval-first and search is always on, so the single most common source of corrupted AI visibility data — a model answering from memory and inventing citations — simply cannot occur here.

It also returns the richest citation payload of any engine, in both search_results and citations fields. More citations per answer means more chances for your domain to appear and, more usefully, a much denser picture of which competitors own your category: a single Perplexity run over fifteen prompts yields more competitor-domain data than the other engines combined.

What does Perplexity cite?

A notably broad mix: publications, review directories, forums, documentation and video, refreshed aggressively. Where other engines settle on a stable set of trusted domains for a category, Perplexity will surface a two-week-old article if it answers the question better.

That volatility cuts both ways and should shape how you read it. Gains show up fast — often within days of a page being indexed — and so do losses, including losses that reverse themselves for no reason you can act on. Use Perplexity as your fastest feedback loop, not as your most stable number.

Which sonar model should you measure with?

The standard sonar model, unless you specifically want to measure the Pro experience. It is what the consumer Perplexity product runs and it is the cheaper of the two, so it is both more representative and easier to run daily.

The Pro tier searches more deeply and returns roughly twice the citations, which will raise your apparent citation rate simply by giving you more slots to appear in — a real difference in the product, but not a real improvement in your visibility. Whichever you pick, hold it constant, or your trend is measuring your model choice. Same principle as choosing a measurement model generally.

What is Perplexity-specific about reading the results?

• Search is always grounded — there is no ungrounded mode to measure by accident.
• More citations per answer means more chances to appear, so your Perplexity Share of AI Answer will usually read higher than other engines. Compare it to its own history, not to your ChatGPT number.
• Fast index refresh makes it the best early signal that a content change is working — treat it as the canary, then confirm on the slower engines.
• Its breadth surfaces long-tail domains other engines never cite, which makes its competitor-domain list the most useful input to an AEO plan.
• Perplexity calls carry a per-request search fee on top of token costs, so it is often not the cheapest engine per prompt despite using smaller models.