Tools that show competitor mentions in LLM answers
Tools that show competitor mentions in LLM answers: what we require for client competitor tracking, how we read share of voice, and what the data cannot tell you.
Clients almost always care more about competitor mentions than their own. "Who does ChatGPT name instead of us?" is the question that gets budget approved. The tools that answer it well do more than count names. Here is what we require and how we use the data.
What we require
- A competitor set we control, with auto-discovery for brands we missed.
- Name variants merged, so a rival's product names do not split their score.
- Share of voice and position, because being named first differs from being named fifth.
- Comparison views across models, topics and countries.
- Citations, so we see which pages get a competitor named.
How we use Promptwatch for this
The platform we run client programs on is Promptwatch. It tracks competitor visibility, share of voice and position, auto-discovers competitors, merges brands for name variants, and offers a heatmap that compares any two dimensions: brands against models, topics against countries. A competitor comparison dashboard template gets a client to a useful view quickly, and we tag prompts as competitor comparison type so we can isolate those questions.
The heatmap is our favorite meeting tool. A client can see at once that a competitor dominates one model or one topic, and that narrows the discussion from "we are behind" to "we are behind here".
Go from "who" to "why"
Counting is the start. For the why, we use citation analytics, which shows which pages and domains get a rival cited, and Page Tracker, which follows specific URLs including a competitor's. Citation Trends tells us whether a rival's page is ramping up or decaying. Offsite mentions and the Reddit, YouTube and LinkedIn citation reports show the third-party sources that carry a competitor's name.
Crawler logs answer the other half: is our client's page being read at all? They are IP-verified, so spoofed agents are filtered out, and they start on the Professional plan.
For Business and agency plans, Ads Radar adds a view of sponsored ads in ChatGPT Search, Google AI Overviews and Google AI Mode, with advertiser name, domain and landing page. That shows which competitors are paying to appear on the client's prompts. It does not cover Perplexity, so we tell clients that.
Turning findings into work
Content gap analysis and the Answer Gap Report show prompts where a rival is named and the client is not. The Action Board prioritizes the follow-up. Typical fixes: a missing comparison page, a clearer answer, a fact corrected, or an outreach target from the mentions list.
What the data does not tell you
Share of voice is a sample. Answers vary by run, country and engine, and we do not read much into a single day. We also remind clients that a competitor being named more often does not mean their product is better received. Sentiment is a separate measure, and Promptwatch scores it per response from 1 to 100 with a weekly AI summary.
Other tools
AthenaHQ and Scrunch AI take action-oriented and crawler-delivery approaches. Semrush and Ahrefs have added AI visibility features to their suites. We have not run client programs on those, so we will not describe their competitor views in detail.
The short version
Choose a tool that treats competitors as a first-class dataset, ties the numbers to citations and crawler access, and leads to action. That combination is why we recommend Promptwatch, and why we start with a competitor set and a stable prompt list before anything else.
We review the competitor list every quarter.
We keep notes on each competitor's product renames.
We also record which clients asked for which view, so reports stay useful.