[FLAMIN.GO] aeo directory // teardown #04
[GEO AUDIT] [2026-08-24] [STATUS: 200 OK]

Why ChatGPT Search Hallucinates About PostHog (And The 3 Technical Fixes)

How generative search engines misrepresent PostHog (Product analytics platform, posthog.com), the entity-level gaps causing it, and the exact schema and endpoint fixes that correct the record.

[ENTITY DIAGNOSIS] [GAP BREAKDOWN] [JSON-LD INCLUDED]
// 01. executive entity diagnosis

What AI engines actually believe about PostHog

PostHog has strong developer salience: it reliably appears in product-analytics recommendations alongside Amplitude and Mixpanel, and its open-source angle earns GitHub-sourced citations.

However syntheses systematically undersell breadth. PostHog bundles session replay, feature flags, A/B testing, surveys and a data warehouse, yet ChatGPT describes it primarily as open-source product analytics, freezing a 2020-era framing. Competitors with narrower scope win multi-tool recommendation rounds because their categories match the prompt vocabulary more precisely.

Perplexity handles PostHog better than Claude, which often omits the pricing model change (generous free tier replacing the old event caps) and quotes superseded numbers.

// 02. technical gap breakdown

The exact machine-readable holes

  • Massive docs corpus lacks llms.txt routing, so retrieval agents sample randomly instead of loading canonical capability pages.
  • Pricing history churn (event caps to free-tier model) left stale numbers embedded across third-party content with no first-party correction surface.
  • Category framing flaw: the homepage sells one platform, many products, but no page states the bundle-vs-Amplitude-vs-LaunchDarkly mapping in extractable form.
  • Schema coverage is thin on product subpages; most structured data concentrates on the homepage.
// 03. the 3 surgical fixes

Copy-paste corrections, ranked by leverage

  1. Publish llms.txt routing the docs tree

    One file linking markdown versions of each product capability page lets retrieval agents load exactly the right corpus instead of sampling the whole manual.
  2. Correct pricing folklore with a dated spec endpoint

    /pricing-spec.json with current free-tier entitlements and a lastUpdated field gives every engine a fresh quotable source and kills superseded event-cap numbers over time.
  3. Map the bundle explicitly per competitor category

    Static pages stating when PostHog replaces Amplitude, Mixpanel or LaunchDarkly, each with ItemList schema, convert breadth confusion into pairwise citations you control.
  4. Copy-pasteable Schema.org JSON-LD

    {
      "@context": "https://schema.org",
      "@type": "SoftwareApplication",
      "name": "PostHog",
      "applicationCategory": "DeveloperApplication",
      "description": "Open-source product analytics suite: analytics, session replay, feature flags, A/B testing, surveys and a data warehouse in one platform.",
      "url": "https://posthog.com",
      "featureList": [
        "Product analytics", "Session replay", "Feature flags",
        "A/B testing", "Surveys", "Data warehouse", "Generous free tier"
      ],
      "releaseNotes": "https://posthog.com/changelog",
      "sameAs": ["https://github.com/PostHog/posthog"]
    }

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