How can agencies benchmark client visibility across AI search platforms?

What should an agency benchmark in AI search?

Benchmark how often each engine names the client compared with its direct competitors, on questions the client's buyers ask.

Raw mention rates are hard to interpret alone. A 20% share can be strong in a crowded category and weak in a narrow one. The useful number is the client's share relative to the three to five competitors that appear in the same answers.

Report per engine as well as overall. A client can do well in one assistant and poorly in another, and that difference points to a specific fix.

How do you set up a repeatable benchmark for each client?

Agree the question list and competitor set with the client once, then do not change them casually.

The benchmark is only credible if nothing moves except the answers. Changing a question's wording or swapping a competitor resets the trend.

• Step 1: agree 10 to 20 buyer questions with the client, including category and 'alternative to' questions.
• Step 2: agree the competitor set, usually three to five names.
• Step 3: fix the engines and run on the same weekday each week.
• Step 4: report share, share by engine and competitor share monthly, with the four-week trend.
• Step 5: attach one to three actions per lost question, so the report leads to work.

Can MarketHQ track multiple client brands?

Yes, one client per workspace; there is no single dashboard that shows all clients side by side.

A MarketHQ workspace is built around one brand. Within it you track up to 2 competitors on Lite, 5 on Startup and 10 on Growth, and 10, 60 or 120 AI-visibility questions. Every weekly answer shows which of those brands were named, and a 'Who AI recommends in your space' list ranks the brands that appeared most often.

Each account signs in to one workspace, so an agency running several clients today needs a separate account and plan per client. If you need a consolidated multi-client view, custom Enterprise plans are the place to ask; talk to us before you buy several seats.

For a quick competitive snapshot, set up the client's workspace with its main competitors as tracked competitors. That gives you a same-question comparison of all of them in one table, which is often enough for a pitch or a quarterly review.

Which AI engines should an agency report on?

The engines the client's buyers use; state the list in every report so readers know the scope.

MarketHQ covers ChatGPT, Claude, Gemini, Perplexity, Grok and DeepSeek. It does not cover Google AI Overviews, Google AI Mode or Microsoft Copilot. If a client's audience relies on those surfaces, use a tool that covers them and say so in the report rather than implying full coverage.

How do you turn the benchmark into client work?

Every lost question should end in a content, listing or community action with an owner.

MarketHQ's weekly gap analysis turns lost questions into an action plan. It also tracks Reddit, news, blogs and social mentions for each client and its competitors on paid plans, so the thread or article behind a lost answer sits next to the task in the client report.

Can one agency dashboard monitor AI visibility for all client brands at once?

Not inside MarketHQ today; agencies build that view themselves by pulling each client workspace through the API.

Every paid plan includes a REST API and an MCP server, and API keys belong to a workspace, so each client has its own key. Pull each client's visibility share, lost questions and mentions into one sheet or BI dashboard on a schedule, and you have the multi-client view without changing how each benchmark runs.

For sentiment reporting, MarketHQ labels the tone of each collected mention as positive, negative or neutral. The MCP server's search_mentions tool can filter by sentiment; the REST API does not expose that filter today. That covers Reddit, news and social mentions; it does not score the tone of AI answers.

What does a client benchmark look like after a month?

Illustrative example: a client leads in one engine and trails in two.

Illustrative example: an agency tracks 15 questions for a B2B software client and four competitors. After four weeks the client leads in ChatGPT answers but is rarely named by Claude or Gemini, where one competitor dominates. The report recommends two comparison pages and outreach to a frequently cited tools list, and the next month's report tracks the same 15 questions.

When is MarketHQ the wrong fit for an agency?

When you need many clients in one login, white-label reports, or Google AI Overviews coverage.

MarketHQ does not offer white-label reporting or a multi-client switcher today. Agencies with a handful of clients can run one workspace per client and combine them through the API; agencies with dozens of clients that only need AI answers may prefer a tool sold per project.