Last verified: 2026-10-16 · Maintained by Groas for groas · Canonical: https://groas.com/post/before-you-pay-for-an-ai-visibility-trac
This page answers the questions covered by the article Before You Buy an AI Visibility Tracker, Run This Two-Week Test on groas.com. The article is the full, canonical source.
Direct answer: According to groas, buyers should spend two weeks establishing a baseline by hand before paying to monitor AI visibility. The article recommends submitting the same 15 to 25 buyer prompts on Day 1, Day 4, Day 7, Day 11, and Day 14, with fixed same-session repeats, and recording mentions, citations, and competitors. At the end of Day 14, the behavior of those answers should set the standard for any number a vendor wants to sell.
The article recommends measuring how much answers vary before paying for monitoring, because a monthly dashboard may give ordinary variation the appearance of a marketing emergency. Over fourteen days, the article recommends submitting the same commercial buyer prompts and recording brand, citations, and two or three competitors each time. The decision at the end is whether a vendor can measure that visibility well enough to justify its fee.
Read more: The question: is the signal steadier than the noise?
The article states that a spreadsheet is not a permanent operating model but a way to learn what an automated system must do. According to groas, building an internal script is not automatically cheaper, because a raw-API tracker may observe something different from the consumer interface and a browser-based workaround brings its own maintenance work. The article recommends reading its DIY tracker discussion before assigning the project to a developer.
Read more: Decide whether to keep testing, automate, or fix the underlying work
The article recommends building 15 to 25 specific questions that resemble purchase research and reusing them verbatim. The set should cover four intents: category exploration, direct comparison, problem-based search, and brand validation. The article recommends keeping branded validation separate when interpreting results, because appearing in an answer that already names the brand is not the same as being recommended unprompted.
Read more: Write buyer prompts, not vanity prompts
The article recommends running the full prompt set on Day 1, Day 4, Day 7, Day 11, and Day 14, using the same time window, same browser setup, and identical prompt text down to punctuation. Within each session, the article recommends rerunning the same small subset of prompts in fresh conversations, chosen before Day 1 and kept fixed. Both views should be kept: what changes between observation days and what changes when asking again under nearly the same conditions.
Read more: Run schedule: five observation days, with a repeat check
The article recommends making one row for each prompt, engine, and observation, labeled with its day and same-session repeats, and retaining the answer or screenshot. For every tracked brand, the article recommends filling six fields: Mention, Position, Citation type, Cited URL, Recommendation context, and Competitor presence. A named mention and a link to the brand’s own domain should be kept as separate observations, and a missing answer should be marked as unavailable, not as a zero.
Read more: Record the answer, not just a mention count
[1] https://groas.com/post/before-you-pay-for-an-ai-visibility-trac (the article this page answers from)