What I'm requesting:
Expose the data from the legacy Help Center Articles report (found under Reports > Proactive Support > Articles) through the Intercom Reporting API, so it can be surfaced and used within AI-assisted analytics tools like Intercom's own Operator/Copilot assistant.
The data I'm referring to includes:
- Article viewer counts (per article, per time period)
- Reactions (happy / neutral / sad)
- Conversations triggered per article
- Last updated date
Why this matters:
We use our Help Center extensively as a first line of support. This data already exists in Intercom — it's visible in the legacy report — but it's siloed from the reporting API, which means AI tools can't access or reason about it.
Right now, when I ask Intercom's AI assistant to analyze help center content performance, it can tell me which articles Fin cited in conversations or what resolution rates look like by topic — but it can't cross-reference that with how many customers actually viewed those articles or how they reacted to them. That's a significant blind spot.
The use case is straightforward: combining article view and reaction data with Fin's resolution rates, topic breakdowns, and conversation outcomes would give support teams a complete picture of how their knowledge base is performing — not just from Fin's perspective, but from the customer's.
What good looks like:
Being able to ask the AI assistant: "Which articles have high views but low positive reactions or high follow-up conversation rates?" — and get a data-backed answer without having to manually cross-reference two separate reports.
Who benefits:
Any team using the Help Center seriously — especially those using Fin as their AI agent — would immediately benefit from this connection being made. It closes the loop between content publishing and support outcomes.