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MentionHub: Track Whether ChatGPT, Perplexity and Gemini Mention Your Brand

MentionHub: Track Whether ChatGPT, Perplexity and Gemini Mention Your Brand

More and more prospective customers ask ChatGPT, Perplexity and Gemini directly before buying. They no longer type keywords and compare ten links — they ask a question and receive one answer containing two or three recommendations.

That shift makes the old question insufficient. It is no longer “where does my site rank”, it is “does the AI mention my brand at all”. MentionHub was built to answer that new question with numbers rather than guesswork.

Why asking once is not enough

If you have ever asked an AI model the same thing twice, you know the answers can differ. That is exactly why checking brand visibility by asking once and drawing a conclusion is an unreliable method.

MentionHub asks one prompt repeatedly across several AI engines at once, then analyses the answers: is your brand mentioned, in which position, and with what sentiment. Repeated sampling is what makes the result stable rather than one lucky reply.

Share of voice and competitor analysis

You can see your brand's share of mentions against competitors in a single chart, making it clear who the AI actually recommends when customers ask about your product category.

What usually surprises brand owners: The competitor dominating AI answers is often not the largest one, but the one mentioned most across the sources models read — directories, forums, reviews and comparison articles. That is immediately actionable information.

Trends over time

Every check is stored as history, so rises and falls in visibility are visible by day, week or month. For agencies and in-house marketing teams this is the most valuable part: you can prove the impact of optimisation work to a client or a manager with a chart rather than a claim.

White-label PDF reports for agencies

MentionHub produces send-ready reports carrying your agency's own logo, colours and identity. That is what allows the tool to be sold directly as a paid service to clients rather than used only as an internal utility.

Multi-tenant with a credit system

You install the provider API key once as the operator, set your own rates, then sell that capacity to tenants as credits. Each tenant's usage is recorded cleanly and never leaks across accounts.

One installation serves many clients with isolated data.
You set the price per credit above the underlying AI provider cost.
Usage per tenant is recorded so billing never becomes a debate.
Reports go out under the agency's identity, not the tool's.

Technology

Built with Laravel 12, Vue 3 with Inertia, and MySQL — a modern stack that is easy to customise, scale and deploy on your own server. Because you supply your own provider API key, operating cost is transparent and fully under your control.

It costs IDR 700,000 as a one-time source code purchase. For an agency, that figure is usually covered by a single client in the first month.

Who benefits most

ProfileHow they use itMain value
Digital agencySelling monitoring as a monthly serviceWhite-label reports and the credit system
In-house marketing teamMonitoring own brand and competitorsEvidence that optimisation work landed
SEO consultantAdding a service beyond Google rankingsDifferentiation from other consultants
Brand ownerChecking brand position periodicallyEarly warning when visibility drops

Frequently Asked Questions

Does this replace SEO?
No, it complements it. Search rankings still drive direct traffic, while AI mentions determine whether your brand appears when prospects ask instead of search. Both run in parallel, and the sources that strengthen one often strengthen the other.
What does it cost to operate?
Because it uses your own API key, cost follows your AI provider's rates and how much sampling you run. That is precisely why the credit system exists — so you can set your own margin above that cost.
Which prompts should be monitored?
The most useful are questions prospects genuinely ask, such as recommendations for the best provider in a given city or comparisons between solutions. Monitoring your own brand name helps, but monitoring category questions that name nobody is far more important.
Can the results be used to improve position?
Yes, and that is the point. Once you know which sources a model cites when recommending a competitor, you have a concrete work list instead of a guess.
Explore MentionHub

Including how multi-engine sampling works, the tenant credit structure, and an example of the white-label report you can send to clients.

View MentionHub