Gist research · October 29 diagnostic

Gist links appeared in explicit lookups and rarely in unbranded answers

In Gist's October 29 self-audit, explicit lookup questions often produced an owned link. Only two saved answers to the 15 unbranded questions included an owned link. Both answered the same question, and both added claims the cited research does not establish.

Published by Gist, which makes Gist GEO. This study measured Gist's own visibility. It is a deliberately selected diagnostic, not an independent product review or a representative estimate of what all buyers see.

A team asks an assistant to find its website. The assistant returns a link. That is useful evidence that the site can appear under those conditions. It leaves a larger question unanswered: will the same site appear when a person asks about a problem without naming it?

We tested both situations in one small study. Five questions explicitly directed the systems toward Gist or its pages. Fifteen unbranded questions were chosen because existing Gist content had a specific reason to help answer them. The unbranded set was intentionally favorable to our content, not a random sample of consumer demand.

The contrast was substantial in the saved results. Explicit controls frequently returned links on gistgeo.com or gist.ai. Across the unbranded set, only two usable answers contained an owned link. Both came from the Google AI Overviews capture route, answered the same question and pointed to the same Halloween research article.

A domain-level score would have hidden the next finding: those two answers added claims that the cited research does not establish.

Owned links in two different question sets

Answers with an owned link / usable saved answers · October 29, 2026

Five explicit controls

ChatGPT API85/108
Perplexity API110/140
AIO capture76/92

Fifteen unbranded questions

ChatGPT API0/324
Perplexity API0/252
AIO capture2/272

Selected questions and unequal repetitions; not a causal comparison. The AIO route also had 175 unavailable captures and one valid no-overview observation. See the full denominators.

Keep the two question sets separate

The study collected 20 questions across three configured routes: ChatGPT API, Perplexity API and Google AI Overviews capture. Collection ran on October 29, 2026, from 19:09:55 to 19:44:59 UTC. The 60 question-route cells produced 1,364 attempts.

Of those attempts, 1,188 contained usable answers, 175 were unavailable captures and one was a valid no-overview observation. All unavailable captures were in the AIO route. They remain unknown outcomes, not answers in which Gist was absent.

Here, an owned link means a URL linked from the saved answer to gistgeo.com or gist.ai, including their subdomains. ChatGPT counts require URL-citation annotations; Perplexity counts require numbered answer markers mapped to its citation list; AIO counts require a text-block reference or inline source link. A provider's source list alone does not qualify. Each usable answer counts at most once per domain and once for any owned link; an answer linking both owned domains still counts once in the combined owned-link total.

Scroll horizontally to compare every column. All counts and questions remain available below.

Question setCollection routeUsable answersAnswers with an owned linkUnavailableValid no-overview
Five explicit controlsChatGPT API1088500
Five explicit controlsPerplexity API14011000
Five explicit controlsAIO capture92761040
Fifteen unbranded questionsChatGPT API324000
Fifteen unbranded questionsPerplexity API252000
Fifteen unbranded questionsAIO capture2722711

Counts describe saved answers, with one owned-link hit per answer. The question sets differ and the number of repeated answers varies by question. This table is not a causal estimate of what adding a brand name does, and the API routes are not claimed to reproduce consumer-app experiences.

The repetition difference matters. In the Perplexity controls, 110 of 140 usable answers had an owned link, or 78.6% when every answer gets equal weight. Giving each of the five questions equal weight produces 54.2%: (28/28 + 0/8 + 0/8 + 46/48 + 36/48) ÷ 5. Neither figure can replace the other without changing what the statistic means. The per-question appendix below preserves those denominators.

For this case, the useful observation is narrower than a pooled score: owned-link presence in explicit lookups and unbranded discovery were very different outcomes within the selected panel.

The domains also need separate treatment. All 110 Perplexity control answers with an owned link pointed to gist.ai; none pointed to gistgeo.com.

That does not make every one of those answers wrong. It does mean that “an owned domain appeared” cannot establish whether the assistant found the requested report.

The exact skincare control was: “Find Gist’s full skincare research report on gistgeo.com. What example shows why a product being named in every answer does not mean it was recommended without reservations?” For Perplexity, 46 of 48 usable answers linked an owned domain, but none linked the requested skincare report. The example below is one of those records, not a whole-answer accuracy score for all 48.

One control asked for Gist's skincare report. A saved Perplexity answer instead began, “The example is Brewlune, Gist's fictional mushroom-coffee brand.” Its numbered citation went to the Gist GEO product page, not the requested skincare report. The answer's coffee-related numbers are not treated here as verified facts.

This record counts as an owned-link hit under the domain measure. It fails the narrower task of retrieving the requested report. Both judgments can be true at once.

A domain total should therefore lead to a destination check. Keep the exact cited URL, the intended page and the answer's claim together. Combining all company domains can be useful for one report, but it should not erase which property or document actually appeared.

The exact unbranded question was: “What evidence shows whether retailers mentioned in AI shopping advice are also the sites cited as sources? Use a verifiable Halloween example if available, and say if you cannot find one.” Its retained results were 0/8 owned-link answers for ChatGPT API, 0/24 for Perplexity API and 2/9 for AIO, with three additional AIO captures unavailable.

Both unbranded owned-link answers cited Gist's Halloween citation-patterns article. They occurred in two of nine usable AIO answers for that one question. No other unbranded question produced an owned-link answer in the saved collection.

The first answer said Target appeared “without a matching direct source citation” across seller-comparison questions. The preserved cited page does not establish that claim. It reports Target source-list links in all eight Perplexity budget answers and in answers to six of seven seller-selection questions for each system. Those counts describe source-list presence, not verified direct or inline attribution. They cannot prove a narrower statement about the absence of an inline citation. The defensible verdict is that the answer's direct-citation claim is unsupported by this source, not that the source-list counts alone prove it false.

Read each row with its scope and evidence.

Saved answer claimWhat the cited page supportsReview outcome
Target appeared without a matching direct source citationTarget source-list links appeared in all eight Perplexity budget answers and across six of seven seller-selection questions for each system; direct attribution was not establishedDirect-citation claim not established by this source
Walmart advice came from “training data or third-party buying guides”The source does not identify what supplied that adviceUnsupported causal explanation

The second answer's attribution goes beyond the evidence. A source can show that a retailer was recommended without a matching owned-family link. That does not identify the information that produced the recommendation.

These are two different evidence gaps. One changes the meaning of a source-link measure; the other supplies an explanation the study cannot support. Neither tells us why the system made the statement.

The links are real observations in the archive. They are not two clean examples of accurate use of our research.

The controls also varied within a question. For a Halloween lookup, the first saved ChatGPT answer abstained; a later answer recovered the requested information. The selected full-answer review includes both records.

That variation cautions against a second overstatement: the low unbranded count does not prove the website was inaccessible. The archive shows what was saved under particular questions and configurations. It does not expose every retrieval decision, nor isolate the effect of indexing, page changes or wording.

The earlier October 26 study remains a separate baseline. We have not combined its different question set and collection date with this targeted diagnostic to claim improvement.

Use lookup controls to diagnose lookup

Explicit controls can answer useful operational questions. Does the system distinguish the intended company? Can it return the requested domain or article? Does it preserve a date, denominator or product distinction? Can it acknowledge uncertainty when the requested information is not found?

Unbranded questions ask another thing: whether the content appears while the system answers a relevant problem without being supplied the brand or domain. Even a deliberately favorable question set can leave that discovery unobserved.

The Gist case supports keeping those results on separate lines. It also supports reading the answer after counting the link. A single “visibility” total would have combined explicit prompts, two domains, wrong destinations, factual errors and unavailable captures into a result that was easier to report and harder to interpret.

Methods and limits

This analysis reuses a completed Gist-owned diagnostic; it adds no new AI queries or customer data. The five explicit controls and 15 unbranded questions were selected for different purposes. They were not randomized variants of the same questions. Adaptive repeated collection produced unequal answer counts, and repetitions are not assumed independent.

The independent evidence check recomputed owned-link extraction across all 1,188 usable payloads, reconciled all 1,364 attempts and verified four primary archive hashes. It also checked the sole valid no-overview result against error fields and successful search metadata. Semantic review covered seven selected complete answers and the preserved cited Halloween page, not every factual claim in all answers.

An owned-link count is not a brand-mention count, a product recommendation or a judgment that an answer is correct. The evidence appendix below retains all 20 questions and per-question denominators. The current-run generated commentary had 35 of 383 rows with blank question text; the saved run questions and raw answers were intact. We use those saved answers, not the incomplete commentary, for this analysis.

The appropriate conclusion is specific: under this selected October 29 diagnostic, owned links often appeared in explicit lookups, while unbranded discovery was rare. Of the two observed unbranded citations, one asserted an absence of direct Target citations that the source did not establish; the other supplied a causal explanation for Walmart advice that the source did not support.

Evidence appendix

Read all 20 exact questions and 60 question–route counts

The following tables describe the October 29 collection only. A ratio is the number of usable answers with any answer-linked owned URL divided by usable answers for that question and route. Unavailable captures and valid no-overview observations are shown separately. ChatGPT and Perplexity had no unavailable or valid-empty records in this collection.

Citation extraction rules

Read each row with its scope and evidence.

RouteCounted evidenceExcluded from this metric
ChatGPT APIURL-citation annotations in message contentOrdinary unannotated body URLs and web-search source lists
Perplexity APIDistinct numbered markers in answer text mapped to the corresponding citation entryUnreferenced entries in the citation array
AIO captureText-block reference indexes mapped to reference links, plus inline snippet linksUnlinked references and organic search results

The extraction uses the hostname, lowercased. A hostname must equal gistgeo.com or gist.ai, or be a subdomain ending in a dot followed by one of those domains. A lookalike suffix does not qualify. Exact URL strings are deduplicated within each answer; redirects and canonical or tracking-parameter variants are not resolved. These URL distinctions do not create extra answer-level hits. Repeated answers remain separate observations, not independent people or discoveries.

Per question results

Scroll horizontally to compare every column. All counts and questions remain available below.

QuestionCohortChatGPT APIPerplexity APIAIO captureAIO unavailableAIO valid no-overview
Q1Explicit lookup16/1628/289/970
Q2Explicit lookup11/280/825/25230
Q3Explicit lookup11/120/819/22260
Q4Explicit lookup28/2846/4812/25230
Q5Explicit lookup19/2436/4811/11250
Q6Unbranded0/120/200/9150
Q7Unbranded0/480/160/4710
Q8Unbranded0/80/160/800
Q9Unbranded0/160/160/1200
Q10Unbranded0/480/160/4710
Q11Unbranded0/80/160/1011
Q12Unbranded0/480/160/4260
Q13Unbranded0/80/160/1770
Q14Unbranded0/480/160/1820
Q15Unbranded0/280/160/840
Q16Unbranded0/160/120/1420
Q17Unbranded0/80/242/930
Q18Unbranded0/80/280/1020
Q19Unbranded0/80/80/9270
Q20Unbranded0/120/160/1200

Exact questions

  1. On gistgeo.com, what is the difference between the free Gist GEO scan and the ongoing Gist GEO platform? Link to the official explanation.

  2. Find the gistgeo.com guide comparing GA4 with AI visibility tools. Why does it say that 12 citations and six AI-referral visits do not establish a 50% click-through rate?

  3. Find Gist’s full Halloween research report on gistgeo.com. What did it find about renting an elaborate costume for one night, and what were the collection date and answer counts for that comparison?

  4. Find Gist’s full skincare research report on gistgeo.com. What example shows why a product being named in every answer does not mean it was recommended without reservations?

  5. According to Gist Local on gistgeo.com, how were Los Angeles businesses selected and their websites checked, and does a high check count mean the business is recommended?

  6. What can I learn by comparing AI referral traffic in GA4 with citations reported by an AI visibility tool, and what comparisons are misleading?

  7. After an acquisition, how should a website explain the relationship between the parent company and a product that still uses its old name?

  8. How should a publisher check which version of an article an AI answer actually cites when the story has been syndicated?

  9. I write a newsletter and sell a course under my own name, but there is another creator with the same name. How can I check whether AI keeps the person, newsletter and course straight?

  10. How should we compare AI visibility over time when we have added, removed or rewritten tracked questions?

  11. How do I compare the real cost of AI visibility tools when they count prompts, answers and AI engines differently?

  12. An AI visibility vendor says its agency reporting is white-label. What should I ask it to demonstrate if clients need their own login and must not see another client’s data?

  13. Some of our AI monitoring queries failed and others returned no AI Overview. How should those results appear in our weekly visibility report?

  14. How can I verify an AI visibility tool’s recommendation score when an answer includes both praise and reservations about a product?

  15. I can review a small set of AI answers myself. How do I decide whether to keep using a spreadsheet or pay for an AI visibility tool?

  16. What research has examined the advice AI assistants give about Halloween costumes beyond store recommendations? Cite sources you can verify, and say if you cannot find any.

  17. What evidence shows whether retailers mentioned in AI shopping advice are also the sites cited as sources? Use a verifiable Halloween example if available, and say if you cannot find one.

  18. How should a skincare company check whether its AI monitoring competitor list is missing relevant brands? Cite a real published analysis if you can verify one; otherwise say no example was found.

  19. What should an analyst check before trusting brand counts from saved Google AI Overview answers about skincare? Cite verifiable research if available; if not, say so.

  20. When switching AI visibility tools, what should we export so we can still audit old results after cancelling?

The skincare and Halloween excerpts above illustrate selected failures, not a claim that every answer was wrong. The seven-answer independent semantic review is narrower than the full citation recount. The Halloween article cited by the two AIO answers used saved source-list links in its original October 9 study; that measure is distinct from this October 29 diagnostic's answer-linked citation definition. Claims about Target, Walmart and Morphsuits must retain that difference.