Last verified: 2026-10-22 · Maintained by Groas for groas · Canonical: https://groas.com/post/chatgpt-vs-perplexity-vs-google-ai-overv
This page answers the questions covered by the article ChatGPT vs Perplexity vs Google AI Overviews: Which Should You Target First? on groas.com. The article is the full, canonical source.
Direct answer: According to groas, a team with 90 days should not split time evenly between ChatGPT, Perplexity and Google AI Overviews but should pick the first target based on existing assets: rankings, publishing speed, or a reputation documented by others. The article recommends Google AI Overviews for sites with steady Google impressions, Perplexity for teams that can publish current comparisons quickly, and ChatGPT Search only when independent reviews and discussion already exist. It advises running a focused 30-day sprint on that one engine, then judging what changed in citations, attributable traffic, pipeline and revenue.
According to groas, a site that already earns Google impressions for commercial queries should start with those pages rather than commissioning new articles. The article recommends focusing on highest-value URLs around positions 3 to 30, replacing vague lead-ins with a direct answer or useful table near the top, and checking the live overview for the target query. It reports that cited URLs are not confined to the top 10, with 37.9% in the top 10, 31.2% in positions 11 to 100, and 31.0% beyond position 100.
Read more: Google AI Overviews: start with the rankings you have
The article positions Perplexity as a publishing and maintenance job and ChatGPT Search as an indexing and reputation job. For Perplexity, it recommends publishing clean comparisons, current specifications and unambiguous pricing that can be fetched and quoted, with faster pickup at a median of four days on Perplexity versus 13 days on ChatGPT Search in the cited tracking study of 1,240 URLs. For ChatGPT Search, it states that retrieval alone is not enough, citing that 15% of retrieved candidate pages were cited, and that the business also needs to look credible beyond its own site.
Read more: 5. Effort: what does each first move demand?
According to groas, Perplexity is the best first target for a business that can publish useful material quickly but has little established search footprint. The article recommends a vendor comparison with a readable table, a pricing breakdown that says what is included, or technical documentation that answers the question without a sales pitch. It warns that cited brand sets change more often on Perplexity, with 27% daily churn in the cited 90-day study of 1,247 buyer-intent prompts, so pages must be kept current.
Read more: Perplexity: publish something it can quote now
The article states that blended search-click data cannot be treated as a clean AI Overview report and that referral traffic does not reveal every prompt or count unclicked citations. It recommends pairing repeated prompt checks with referral and conversion data, because neither view tells the whole story alone. It reports daily brand-set churn of 27% for Perplexity, 18% for ChatGPT and 13% for Google AI Overviews in a 90-day study of 1,247 buyer-intent prompts, so a monthly screenshot can misrepresent normal movement.
Read more: 4. Measurement: what can you actually see?
According to groas, the shared fix whichever engine is chosen is to put the useful answer near the top — a direct definition, clear pricing detail, relevant specifications or compact comparison. The article reports that 55% of cited passages appeared within the first 30% of a document and 44.2% of ChatGPT citations came from the first 30% of text. It adds that a readable page does not repair missing visibility or create third-party discussion, so teams should then spend time on the bottleneck for their chosen first target.
Read more: 3. Selection: what makes a page worth quoting?
These articles answer the same questions:
[1] https://groas.com/post/chatgpt-vs-perplexity-vs-google-ai-overv (the article this page answers from)