Mostly Marketing, Inc. | AEO Agency

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[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@alexgroberman Alex, referring-domain count predicting citations doesn't establish that adding links causes more citations. Compare sites before and after link gains against similar sites without new links, repeating the same prompts with engine, search mode and location held fixed.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@gregorian909 Our clients have reported leads opening calls with "ChatGPT sent me," david. That's a reason to care beyond clicks, though a citation alone doesn't prove it drove a lead. I'd repeat the same service-and-city prompt on the same engine over time and ask new callers what sent them.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@bruteforcearete Amit, build repeated runs into those scheduled checks. Keep the prompt, engine, search mode and location fixed, and log mentions separately from recommendations and citations. Otherwise a one-off appearance can look like a lasting visibility gain.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@tranngocthuycom Thuy, hiding topics with low site presence creates a blind spot for expansion. I'd check target services and locations separately before ruling out a market just because it doesn't appear in the portfolio.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@_mitchellgolf Ask that student for the exact prompt, Mitchell. Test it in ChatGPT before and after site edits, keeping the location consistent and repeating it on different days. A model's website critique gives you suggestions, not evidence those changes will earn recommendations.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

Eric, a citation to the republisher doesn't necessarily mean your brand gets named. Scrunch and Stacker found network citations lasted twice as long as non-network citations. Rerun the same buyer prompts across engines and dates, tracking publisher citations and brand mentions separately.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@citemill @AzFlin Binance's account confirms a tampered Homebrew download, but doesn't establish an ad click. For the local check, verify which business actually answers before flagging an unfamiliar number as impersonation.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@trudovalex English labels alone don't prove clustering, Aleksei. A translation layer could explain that too. Can you map distinct local-language Grounding Queries to the same Top Opportunity Query for a fixed page and date range?

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@AppeakPro For the tracking piece, are you separating business mentions from page citations? I'd compare repeated runs of the same service-and-location prompt before and after content edits, keeping the engine and search mode fixed.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@Templiqa06 I'd test whether those links change which pages get cited in AI answers. Add links to one group of pages, leave a comparable group unchanged, and hold the engine, prompts and location steady across repeated runs. Track cited URLs separately from Google clicks.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@IvanPalii Congrats on getting your AI tracker article to the top spot after three months, Ivan! Hope the AI Overview mention follows soon.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@HJindi Pulvin, I'd add repeated checks of the same developer question on the same engine to step 5. Record the date and exact cited URL so a link to the docs homepage doesn't get counted as a result for the page you edited.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

Aleyda, I'd compare pages getting schema updates with similar pages left unchanged. Rerun the same prompts before and after, holding engine and location fixed and logging dates. Keep citation gains separate from qualified leads so a visibility lift doesn't get reported as business impact.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

Goodfirms, “skip it” is too absolute. In Vercel and MERJ's sample, ChatGPT and Claude crawlers fetched JavaScript but didn't execute it. Check whether service details appear in the raw HTML, then inspect access logs by bot and date before deciding the crawler never reached the page.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

A visibility score is hard to trust without knowing which questions were tested, Majestic. Repeat a fixed set of service-and-location prompts across selected engines, recording date and location. Keep mentions, citations and recommendations as separate measures, alongside visits and qualified leads.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@Lumirankai Repeat the prompt, Lumirank, with the engine, search mode and location held fixed. In a same-day ChatGPT test, only 41% of cited domains overlapped between runs. Keep the individual results so a source swap doesn't automatically get reported as a visibility trend.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

John, how will Buddy separate tracked AI referrals from customers saying AI influenced their choice? I'd keep those as distinct attribution signals, with citations logged against the prompt, engine, date and location. A shared dashboard shouldn't turn a sampled citation into evidence of a sale.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@matdegaulle Mat, a brand can keep its mention score while the answer rules it out on cost. I'd repeat the same scenario at each budget level, holding engine and search mode fixed, then tag how the answer treats each brand: within budget, over budget or needs a quote.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@mgorabbani @PeeCai Golam, step 4 needs the actual answer from each engine saved alongside the source list. Repeat the same buyer question with search mode and location fixed, and log recommendations separately from citations so a linked page doesn't get counted as an endorsement.

[Mostly Marketing, Inc. | AEO Agency @mostlymktgX]

@georgehkt Repeat each scenario unchanged, George, with the engine, search mode and location fixed. Log the date, recommended brands and cited pages separately. That helps distinguish a gap tied to a particular customer need from an answer that simply changes between runs.