How to track your share-of-voice in Perplexity (and why it's not the same as ChatGPT).

Perplexity is the most-cited "AI search" tool that almost no one tracks correctly. The reason: it works differently from every other LLM. Where ChatGPT and Claude give you an answer and an opinion, Perplexity gives you an answer and a citation list. That citation list completely changes how share-of-voice works — and most teams are measuring the wrong thing entirely.

What makes Perplexity structurally different

When you ask Perplexity "what's the best CRM for small B2B teams," it returns a synthesized answer and a numbered list of source URLs it cited to construct that answer. Your brand can appear in three distinct places:

1. 1In the synthesized answer, as a recommended option (just like ChatGPT).
2. 2In the citation list, as a source URL the model used to construct the answer.
3. 3In an inline citation, where the answer text links directly to your specific URL as the basis for a specific claim.

Most tools track only #1, which significantly underestimates your real influence. A brand that's cited 8 times in the source list and inline-linked 3 times is materially more visible than a brand mentioned once in the prose, but conventional SoV math scores them the same.

The three-layer measurement we use

• Layer 1 — Synthesis SoV: How often you appear in the answer prose. The headline metric. Maps directly to ChatGPT-style SoV.
• Layer 2 — Citation share: % of source URLs that are yours. Reflects how much the model trusts your content as the basis for its answer.
• Layer 3 — Inline-citation rate: % of inline citations that point to your URLs. The strongest signal — and the rarest to earn.

Three gotchas we hit building this

Gotcha 1: Perplexity's web-search vs reasoning models cite differently. Sonar-large cites richer source pools; sonar-small cites fewer but more authoritative ones. Track both — they tell different stories about the same query.

Gotcha 2: Citation URLs are sometimes truncated or canonicalized in ways that break naive string matching. Always normalize before scoring (strip query params, lowercase, resolve redirects).

Gotcha 3: The model's recency window matters. Perplexity heavily prefers recently-published content, so older brand assets often disappear from the citation pool even when they're authoritative. Plan refreshes accordingly.