Which pages do AI engines cite for your category? Turn the sources into an outreach to-do list

A developer built AI Brand Monitor, an Apify Actor that returns the full source list behind AI engine answers—URL, page title and quoted snippet—for each query, along with a stability score showing how often a domain is cited across samples. The tool also reports which competitors are cited on the same question and, when given a prior run's dataset ID, writes a delta record of sources gained and lost; a four-query, three-sample run costs about $0.60.

Disclosure: I built the Apify Actor in this post. Written with AI assistance. Knowing whether an AI engine mentions you is the thermometer. The useful part is the list underneath: the exact pages the engine read to build its answer. Ask "best CRM for small business" and the sources might be a review site, a Capterra listing, a Reddit thread and two vendor blogs. You cannot edit the model, but you can get onto those pages. AI Brand Monitor on Apify https://apify.com/highbrow fame/ai-search-visibility-tracker returns, for every answer, the full source list with URL, page title and the quoted snippet. Here is how to turn it into a to-do list. Cost: 4 queries x 1 engine x 3 samples = 12 records x $0.05 = $0.60 . That also fits the 12 Perplexity calls per run included on a free Apify plan. AI answers are not deterministic. A domain cited once in five runs is noise; a domain cited every time is the engine's settled answer. When you set more than one sample, the Actor writes a stability record per query and engine, with each domain's occurrences , samples and stability 1.0 means cited every time . The recommended filter: ignore anything below 0.5. Open the run's dataset and use Export to download a CSV, or read the citations field of each record. Make one spreadsheet row per stable domain, with the page URL, the title and how many of your queries cite it. Then sort by count and assign an action to each row: Check the competitorsCited field on each record too. It shows which rivals are cited on the same question, so you know who you are being compared with. Save the input as a task and run it again in a few weeks. Pass the earlier run's dataset ID as previousRunDatasetId and the Actor writes a delta record with the sources you gained and lost per query. The source list is the best available lever for getting cited. Your first list is a starting map, and the repeat run shows which moves counted. Get your category's source list https://apify.com/highbrow fame/ai-search-visibility-tracker : one run, about 60 cents, and a list of pages to get onto.