# Compare brands in the same AI answers

Canonical: https://llmcitely.com/features/competitor-benchmarking
Publisher: LLM Citely
Reviewed: 2026-10-31

Compare brand mentions and cited sources within a defined question set. Keep the original answers, eligible sample and missing coverage visible.

Six platforms have passed local answer-and-source collection tests: ChatGPT, Gemini, Google AI Mode and Google AI Overviews for website answers; Perplexity and Claude for model API replies. Production rollout is pending. Region and search activity must be confirmed per sample before including it in comparable visibility metrics. [View platform readiness](https://llmcitely.com/platforms#platform-readiness).

![Same answers. Two different denominators. Illustrative arithmetic: 20 planned runs, 18 eligible answers, 2 unresolved.](https://llmcitely.com/images/editorial/same-cohort-comparison.svg)

Illustrative arithmetic: 20 planned runs, 18 eligible answers, 2 unresolved. Mention rate and share of voice answer different questions. Failed runs stay in coverage. Original explanatory diagram; illustrative counts and states are not customer measurements.

## Keep the comparison population fixed

A useful comparison starts with the same buyer questions, period, market and observed surface. Save the approved brand names and aliases before reviewing the answers. An alias edit can change a count; a new question set can change the population.

LLM Citely keeps a brand profile and comparison brands alongside the saved question context. The comparison view lets a reviewer open the answers behind a mention count. A literal mention is available for inspection even when search confirmation is missing; the stricter search metrics need eligible evidence.

Use the [question-selection guide](https://llmcitely.com/guides/choose-buyer-prompts) to keep branded evaluation questions separate from unbranded discovery questions.

## Open the answers behind a number

Start with a brand's mention count, then inspect the relevant saved answers. Check whether the brand is recommended, mentioned in passing or named as a model provider. Those contexts can contain the same name and support different decisions.

Next inspect explicit source links. A competitor mention without a citation is different from a link to a competitor-owned page. The [citation guide](https://llmcitely.com/guides/citations-vs-brand-mentions) explains the counting distinction.

The comparison does not establish a permanent rank or a census of everyone using an assistant. The local component walkthrough below uses synthetic records to show the actual interface; it is not a measured result for a customer.

![Actual LLM Citely competitor interface with explicitly synthetic local example records](https://llmcitely.com/images/editorial/competitor-component-walkthrough.png)

Actual brand-comparison component rendered locally with six synthetic answers. Four mention Example Analytics and three mention Example Metrics; no customer or provider collection was used.

## A small comparison you can recalculate

Consider an **illustrative** campaign with 20 planned runs and 18 valid, eligible answers from one unchanged cohort. Brand A appears in 12 answers and Brand B in 9. Some answers mention both.

| Measure | Brand A | Brand B |
|---|---:|---:|
| Answers mentioning the brand | 12 | 9 |
| Mention rate, using 18 eligible answers | 66.7% | 50.0% |
| Share of the 21 brand-answer mentions | 57.1% | 42.9% |

Mention rates need not sum to 100% because an answer can name several brands. Share of voice uses a different denominator. The two failed or missing runs belong in coverage, rather than being counted as answers that omit a brand. Citation rates also need their own complete-evidence denominator. Review the [measurement method](https://llmcitely.com/methodology) before comparing the values.

## Give a source gap a specific next step

Choose one answer where the evidence supports a useful action. Save the question, collection context and cited URL. Open the cited page and verify what it actually says before suggesting a change.

If an existing page can answer the buyer question, improve that page. If the missing fact belongs in third-party documentation, assign a verification or communication task rather than writing a duplicate article. Attach an acceptance condition and reviewer in the [GEO action plan](https://llmcitely.com/templates/geo-action-plan).

The [citation-gap walkthrough](https://llmcitely.com/guides/find-ai-citation-gaps) handles diagnosis. The [content-brief walkthrough](https://llmcitely.com/guides/citation-gap-to-content-brief) handles the editorial handoff.

## Confirm evidence and availability

Platform readiness is published separately from the existence of this workflow. Review the current [platform table](https://llmcitely.com/platforms#platform-readiness) before planning collection. A model API study and a consumer website answer are separate observation surfaces.

Keep a changed question set, alias rule or collection method in a newly labelled cohort. Missing, unreadable and failed answers stay visible. A before-and-after difference can motivate further investigation; it does not prove that a content change caused the difference.

For a buying decision, use the same question, market, surface, frequency and export requirements with each vendor. [Promptmonitor's competitor page](https://promptmonitor.io/features/competitor-tracking) and [Peec's source documentation](https://docs.peec.ai/understanding-sources) are useful public descriptions of related workflows, not accuracy benchmarks.

## Questions, answered

### Can every saved answer contribute to search metrics?

No. Readable mention evidence and confirmed search-metric eligibility are separate. Review the surface and eligibility before interpreting a rate.

### Do two brand mention rates add up to 100%?

They need not. One answer can name several brands. Share of voice is a separately defined calculation.

## Sources and further reading

- [Promptmonitor: competitor tracking](https://promptmonitor.io/features/competitor-tracking)
- [Peec: understanding source views](https://docs.peec.ai/understanding-sources)

Examples marked illustrative are not customer measurements.

## Continue with the next step

- [Investigate an explicit citation gap](https://llmcitely.com/guides/find-ai-citation-gaps)
- [Inspect citation evidence](https://llmcitely.com/features/citation-tracking)
- [Check the comparison denominators](https://llmcitely.com/methodology)
- [Assign a reviewable action](https://llmcitely.com/templates/geo-action-plan)

## Your next step

[Investigate an explicit citation gap](https://llmcitely.com/guides/find-ai-citation-gaps)