Gemini was audited alongside three other AI assistants across 2,475 US market leaders, finding that 86% of ecommerce category leaders were never recommended in unbranded queries despite the model...

{
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  "signal_type": "reddit-company",
  "signal_subtype": "customerFeedback",
  "detected_at": "2026-08-30T00:23:23+00:00",
  "company": {
    "name": "Gemini",
    "domain": "gemini.com"
  },
  "data": {
    "nsfw": false,
    "stage": "none",
    "awards": 0,
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    "topics": [
      "ai",
      "aeo",
      "search",
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    "post_id": "1w22mjh",
    "summary": "Gemini was audited alongside three other AI assistants across 2,475 US market leaders, finding that 86% of ecommerce category leaders were never recommended in unbranded queries despite the model having extensive knowledge of the brands.",
    "category": "features",
    "comments": [
      {
        "url": "https://www.reddit.com/r/aeo/comments/1w22mjh/comment/p6rgedu/",
        "depth": 0,
        "score": 1,
        "author": "Jason_StickyFrog",
        "excerpt": "Knowing the brand and recommending it are just two different systems though. One's entity knowledge from training, the other's whatever it pulls live for a comparison question. Your citation backtrack is showing you the second one, and not being in it doesn't mean it's not known, just means nothing recent enough puts it next to that framing.\n\n Worth checking if those citations skew toward \"best X",
        "posted_at": "2026-08-30T09:13:03.000Z",
        "author_url": "https://www.reddit.com/user/Jason_StickyFrog/"
      },
      {
        "url": "https://www.reddit.com/r/aeo/comments/1w22mjh/comment/p7id8qn/",
        "depth": 0,
        "score": 1,
        "author": "Banavo",
        "excerpt": "Absolutely spot-on! This is what we call organic mentions (when AI engines surfaces your brand/product without ever being mentioned in the prompt). This is the most critical measure of AI brand voice. But, it doesn't mean we discount the branded mentions (when the prompt includes the brand for comparison or deeper dive). We find it valuable to track both and optimize content, citations, and compet",
        "posted_at": "2026-09-03T03:35:18.000Z",
        "author_url": "https://www.reddit.com/user/Banavo/"
      }
    ],
    "evidence": [
      "[post] I asked ChatGPT, Claude, Gemini and Perplexity who's best in each brand's category, with the brand name nowhere in the question.",
      "[post] 86% of the ecom brands never came up once. Not ranked low. Never mentioned.",
      "[post] So the model isn't ignorant of these brands. It knows them perfectly well. It just never reaches for them when someone describes the problem the brand solves instead of naming it."
    ],
    "virality": "very_low",
    "post_date": "2026-08-30T00:23:23.000Z",
    "post_kind": "text",
    "post_text": "Been doing this since 1995 and this is the result that changed how I pitch.\n\nLast week I used my system and I audited 2,475 US market leaders, local and ecom, picked by review volume so these are category winners rather than strugglers. As part of it I ran a simple probe. I asked ChatGPT, Claude, Gemini and Perplexity who's best in each brand's category, with the brand name nowhere in the question.\n\n86% of the ecom brands never came up once. Not ranked low. Never mentioned.\n\nThen on the ones I went deeper on I asked the same four assistants about the brand by name. All four knew them. Founding year, product line, positioning, reputation, the lot. One of them has over three hundred thousand reviews and the assistants can talk about it all day.\n\nSo the model isn't ignorant of these brands. It knows them perfectly well. It just never reaches for them when someone describes the problem the brand solves instead of naming it. Knows the brand but pulls a competitor.\n\nI then created a system to backtrack each citation they used to base their recommendation on. Ran it multiple times against a large brand base - pulled over 800 citations for just one brand. I studied where the citation ranked on the page, competitors, density of mention, depth on the page, age of material. WOW - I learned a ton.\n\nThe bit I keep chewing on is that everyone is optimizing to be found when someone types...",
    "sentiment": "neutral",
    "subreddit": "aeo",
    "event_date": "2026-08",
    "post_title": "Every AI assistant knows the brand you name. Not one of them recommends it.",
    "prominence": "core",
    "source_url": "https://www.reddit.com/r/aeo/comments/1w22mjh/every_ai_assistant_knows_the_brand_you_name_not/",
    "entity_role": "vendor",
    "post_author": "styleforge-io",
    "upvote_ratio": 0.6,
    "mention_count": 1,
    "mention_surge": false,
    "subreddit_url": "https://www.reddit.com/r/aeo/",
    "total_upvotes": 1,
    "comments_total": 5,
    "total_comments": 2,
    "event_date_text": "Last week",
    "other_companies": [
      {
        "name": "ChatGPT",
        "role": "competitor"
      },
      {
        "name": "Claude",
        "role": "competitor"
      },
      {
        "name": "Perplexity",
        "role": "competitor"
      }
    ],
    "post_author_url": "https://www.reddit.com/user/styleforge-io/",
    "signal_category": "feedback",
    "comments_included": 2,
    "products_mentioned": [
      "Gemini"
    ]
  }
}

curl https://signals.autobound.ai/v1/signals/00115181-e324-5356-a41e-b3abd6f6b991 \
  -H "X-API-KEY: $AUTOBOUND_API_KEY"

curl -X POST https://signals.autobound.ai/v1/companies/enrich \
  -H "X-API-KEY: $AUTOBOUND_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domain":"gemini.com","limit":20}'