四大 AI 引擎品牌提及率相差 12.2 个百分点：30 个消费电子与手机品牌实测

We asked 4 AI engines — ChatGPT, Perplexity, Claude, Gemini — the questions buyers actually type, about 30 Consumer electronics & mobile brands, on 2026-10-03. That is 360 answers. The engines did not agree: 12.2 percentage points separate the most and least generous of them.

Every figure below comes from those answers, and the query to re-run them is at the bottom of this page.

Which engine actually names brands?

Not equally. Gemini named a brand in 41.1% of its answers; Perplexity managed 28.9%. That is a 12.2-point gap between two engines asked identical questions on the same day, which is the whole argument for measuring more than one.

{"type":"bar","title":"Share of answers naming a brand, by engine (Consumer electronics & mobile)","unit":"%","data":[{"label":"Gemini","value":41.1},{"label":"Claude","value":37.8},{"label":"ChatGPT","value":36.7},{"label":"Perplexity","value":28.9}],"note":"360 answers measured 2026-10-03."}

Do the engines agree on who exists?

10 of the 30 brands were named by all 4 engines, and 10 were named by none of them (Crest, Divvy, Doing, Duoqin, Finderlock, Looq: Preview Files, Mispher, RepStandard, adsideō, fort). The rest sit in between, visible to some engines and invisible to others.

The widest split was Apple Reminders: Claude named it in 100% of the answers we asked about it, ChatGPT in 0%. That comparison rests on the handful of questions we asked about that one brand, not on the full sample — treat it as a lead to investigate, not a law.

{"type":"bar","title":"How many engines named each brand","data":[{"label":"4 of 4 engines","value":10,"emphasis":false},{"label":"3 of 4 engines","value":4,"emphasis":false},{"label":"2 of 4 engines","value":5,"emphasis":false},{"label":"1 of 4 engines","value":1,"emphasis":false},{"label":"0 of 4 engines","value":10,"emphasis":true}],"note":"Brands, out of 30 measured."}

Brand by brand, the disagreement is easier to see than to describe. These are the 15 brands the engines split hardest on — each cell is how often that engine named that brand.

{"type":"heatmap","title":"Which engine names which brand","unit":"%","cols":["ChatGPT","Claude","Gemini","Perplexity"],"rows":[{"label":"Apple Reminders","cells":[0,100,100,66.7]},{"label":"EveryDollar","cells":[66.7,66.7,66.7,0]},{"label":"Gaming services by IFTTT","cells":[66.7,0,66.7,0]},{"label":"Google Tasks","cells":[0,66.7,0,33.3]},{"label":"Nothing","cells":[0,66.7,66.7,33.3]},{"label":"Realme","cells":[33.3,66.7,0,0]},{"label":"Xiaomi","cells":[33.3,0,66.7,0]},{"label":"OnePlus","cells":[66.7,66.7,66.7,33.3]},{"label":"Apple","cells":[100,66.7,100,100]},{"label":"co/core","cells":[0,33.3,0,0]},{"label":"Google","cells":[100,66.7,100,66.7]},{"label":"Oppo","cells":[33.3,0,33.3,33.3]},{"label":"Samsung","cells":[100,66.7,100,100]},{"label":"Sensodyne","cells":[66.7,66.7,100,66.7]},{"label":"Sony","cells":[100,66.7,66.7,66.7]}],"note":"The 15 brands with the widest spread between engines, out of 30 measured."}

Named is not the same as recommended

A mention is not an endorsement. Of every mention in this study, 55.4% was the engine's first recommendation, while 40.8% was the brand being offered as an alternative to something else. A brand can look visible and still only ever appear as the runner-up.

{"type":"bar","title":"What role the brand played when an engine named it","unit":"%","data":[{"label":"recommended first","value":55.4,"emphasis":false},{"label":"offered as an alternative","value":40.8,"emphasis":true},{"label":"listed in a comparison","value":2.3,"emphasis":false},{"label":"mentioned in passing","value":1.5,"emphasis":false}],"note":"Share of all mentions in this study."}

5 brands were named but never recommended first by any engine: Google Tasks, Nothing, Oppo, Vivo, co/core. For those, visibility work is not the problem — positioning is.

What the engines actually said

Scores are a summary. These are the sentences themselves — one from each engine, about a different brand, exactly as written on 2026-10-03.

ChatGPT, on Adorama: "Adorama: A well-known retailer with a wide selection of photography gear, including cameras, lenses, and accessories."

Claude, on Apple Reminders: "Apple Reminders is the best free option on iOS. It's built-in, syncs with iCloud automatically, and has improved significantly with Smart Lists, Tags, and shared list features."

Gemini, on Apple: "For a premium, portable, and software-rich experience, the Apple iPad Pro is a strong choice."

Perplexity, on B&H Photo Video: "B&H Photo Video — A strong all-around option for cameras, lenses, lighting, support, audio, monitoring, and cinema gear."

The engines are not criticising you. They are omitting you.

Of the 130 mentions in this study, 121 were positive in tone and not one was negative. That is 93.1% positive. Reputation management is not the problem here: when an engine has something to say about a brand it is almost always kind, and when it has nothing to say it simply leaves the brand out. The gap to close is absence, not sentiment.

Which sources are the engines reading?

The engines cited youtube.com more than any other source (80 citations, 2.5% of all citations in this study). But the long tail is the real story: the top 10 domains together account for only 16.5% of citations. There is no short list of sites to get listed on — the engines are reading widely.

{"type":"bar","title":"Most-cited sources across every answer","data":[{"label":"youtube.com","value":80},{"label":"techradar.com","value":71},{"label":"cnet.com","value":65},{"label":"pcmag.com","value":57},{"label":"techadvisor.com","value":50},{"label":"tomsguide.com","value":49},{"label":"reddit.com","value":47},{"label":"androidauthority.com","value":38},{"label":"bgr.com","value":37},{"label":"nytimes.com","value":33}],"note":"Citations counted across 360 answers. \"Engines\" column below shows how many of the 4 cited each source."}

Who do the engines bring up instead?

These names were never in our sample — the engines volunteered them while answering about someone else. Belkin came up against 4 of the 30 brands we measured. If you are in this category, these are the brands you are being compared to whether you like it or not.

{"type":"bar","title":"Names the engines volunteered, by how many of our brands they appeared against","data":[{"label":"Belkin","value":4},{"label":"Baseus","value":4},{"label":"Honor","value":3},{"label":"Samsung Galaxy S26 Ultra","value":3},{"label":"Google Pixel","value":3},{"label":"UGREEN","value":3},{"label":"TickTick","value":2},{"label":"Todoist","value":2},{"label":"Spigen","value":2},{"label":"Google Pixel 9 Pro","value":2}],"note":"Not part of the sample; named by the engines on their own."}

Every brand we measured

Visibility is the share of scored answers in which an engine named the brand. Apple led at 92%; RepStandard came last at 0%.

What to do with this

1. Measure every engine, not one. The spread between the most and least generous engine in this study was 12.2 points. A check against a single engine tells you about that engine.
2. Check the role, not just the mention. 40.8% of mentions here put the brand in the alternative slot. Moving from alternative to first recommendation is a positioning problem, not a visibility one.
3. Follow the citations, not the keyword list. The engines quoted a wide spread of sources here; youtube.com was the single most cited. Earning a place on the pages an engine already reads is what changes an answer.
4. Zero is a starting point, not a verdict. 10 of 30 brands scored zero here. The first mention on any engine is the milestone that proves the sources are being read.
5. Do not budget for reputation defence you do not need. 93.1% of mentions here were positive. Spend on being present, not on being liked.

What this does not show

• Each brand was measured on the questions our generator writes for that brand, not on one shared question set, so this is an average of per-brand measurements and not a like-for-like ranking.
• Per-brand splits between engines rest on the few questions asked about that brand, not on the full sample of 30.
• These are measurements taken on 2026-10-03. AI answers change; a score here is a reading on that date, not a permanent property of the brand.

Reproduce this

The raw answers are stored per brand, per engine, per question. The figures above come from:

select "brandName", "stratum", "visibility", "mentionCount" from "StudyResult" where "studyId" = 'cmuqjbj13000nl904p08yu98d' order by "visibility" desc

Want the same measurement for your own brand? The free check runs this exact pipeline.

Originally published on GeoBuddy Blog.

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