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Article report sorted by reactions and conversations

Review article performance by negative reactions, conversations triggered, and no-result searches so content work follows actual customer friction.

uncommon tacticfree budget

Why this can grow a startup

Support content gets political when teams argue from anecdotes. Intercom's Articles report shows which articles triggered conversations, which searches had no results, and which pages drew negative reactions. That gives the docs backlog a harder spine. Instead of rewriting the loudest page or the one a stakeholder remembers, the team can start with the answer that already proved it was failing in public.

Company example

Intercom's Articles report surfaces article views, reactions, conversations triggered, search keywords with results, and searches with no results.

Source and metric

Source: Intercom Help: Articles report · Browse Intercom Help: Articles report tactics

Intercom updates the Articles report daily and includes searches with no results, conversations triggered, and negative reactions.

Source discovered: May 30, 2026

SupportSEODocumentationdocs analyticssearch intentcontent prioritizationsupport reporting
GrowthDex operator note

When to use it

Use this when Support, SEO, Documentation is relevant to docs analytics, search intent, content prioritization and you can run a bounded test with a free budget.

When not to use it

Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.

Founder checklist

  1. Read Intercom Help: Articles report and identify what is directly supported.
  2. Choose one channel context: Support, SEO, Documentation.
  3. Define the test around Intercom updates the Articles report daily and includes searches with no results, conversations triggered, and negative reactions..
  4. Set an owner, evidence window, and stop condition before launch.

Explore the context

Advisory bridge

Apply this with an operator

Turn isolated search tactics into a crawlable visibility system tied to demand and proof.

Work with Ian