1) Set the baseline
Add your brand and competitors. A couple of weeks of daily runs give you a visibility rate to compare against.
Generative engine optimization has two halves. You need to know how often the engines name you, and you need to know what to change. CitePrism samples seven engines with your buyer questions on a schedule, then turns the stored answers into a short work list. No tool can see real user conversations, so this is sampling, not a view of what any one buyer sees. The work itself stays yours: no tool changes what an engine says on your behalf.
Most GEO work happens outside the tool: on your site, on review platforms, in comparison articles. A GEO tool earns its place when it shows where to spend that effort, and then shows whether the effort moved the answers.
ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, Google AI Mode and Microsoft Copilot get the same questions, so a gain on one engine does not hide a loss on another.
Gaps lists the prompts where a competitor appears and you do not. Each one points to a page to write or a source to earn.
Opportunities reads the last 30 days of answers and writes a weekly list of actions, each linked to the prompts it should move.
How it works
Add your brand and competitors. A couple of weeks of daily runs give you a visibility rate to compare against.
Start with Gaps and the most cited sources. Publish, update or get listed where the answers come from.
Keep the same prompts running. The trend and the raw answers show whether the engines picked up the change.
Lead with visibility rate: the share of sampled answers that name the brand. Put share of voice and average rank beside it, measured against the same competitors and the same prompt set every period. Add citation share to show whether the client site is a source. Report each engine as well as the overall number, show the sample size, and leave out any metric with fewer than 10 answers behind it. Link the raw answers behind each large change, so the client can read them.
Five things. The same fixed prompts on every engine, so results compare. Competitors scored by those same prompts. Raw answers stored, so you can check any number. A minimum sample size before a metric shows (CitePrism greys out below 10 answers). And the cited sources, because they tell you where to act.
It depends on where the answer comes from. Engines that search the web can pick up a new or updated page once it is indexed. Answers that come from model training change only when the provider ships a new model. Steady daily sampling catches both kinds of change when they happen.
A Free baseline runs on your own keys: 1 brand, 25 prompts, 5 competitors and one run a day. Model keys run the API engines at about $0.046 per prompt across the four API engines (measured August 2026), paid to the model providers, so twenty prompts once a day is roughly $28 a month. Google AI Overviews, AI Mode and Copilot have no API, so on Free they need your own key for reading the answers, which its provider prices per request. Pro is $29 a month or $299 a year and runs on CitePrism keys with a daily included usage amount.