Intercom

Sync Revo with your Intercom for customer messaging and support.

What It Is

Revo connects to your Intercom workspace to read conversations, customer profiles, messages, and support data, then transforms your customer interactions into searchable, actionable intelligence that powers engagement and support.

What It Unlocks

Search your entire Intercom workspace using natural language across all conversations, customer profiles, messages, tags, and support threads
Auto-sync customer data with Revo's intelligence modules, interaction history, sentiment trends, engagement scores, and response patterns
Cross-reference Intercom conversations with Jira issues, user feedback, product roadmaps, Slack discussions, and CRM records (HubSpot)
Trigger workflows based on Intercom events like new conversations, message replies, tag additions, or customer satisfaction surveys
Auto-generate insights from interaction data, detect support trends, surface feature requests, and track customer sentiment

How to Use It for Emails

When drafting email replies, Revo automatically pulls relevant Intercom context:

"What's the history with Customer X?"
- → Revo searches Intercom for past conversations, unresolved queries, and sentiment
"What issues has User X reported?"
- → Revo lists support threads, tags, and response times for context
Includes source links to Intercom conversations so recipients can see full interaction history

Result: Emails grounded in real customer context, no more missing prior interactions or support details.

How to Use It from Chat

Ask questions directly in Revo:

"What conversations mentioned 'integrations' this week?"
"Show me recent messages from enterprise customers"
"Summarize support threads for Account Y"

Revo searches across Intercom conversations and profiles, delivering answers with message links and tags.

How to Use It in Workflows

Trigger workflows FROM Intercom:

New conversation tagged "feature request"
- → Extract request details
- → Create User Feedback entry
- → Link to product roadmap
- → Notify #product
Customer satisfaction survey scores low
- → Pull conversation history
- → Create escalation task
- → Alert CSM
- → "Customer Z gave 2/10 rating, review last interaction"
Message contains "bug"
- → Auto-tag and prioritize
- → Cross-reference with Jira
- → Notify engineering
- → "Bug reported in live chat, check if duplicate"

Update Intercom FROM other sources:

Jira issue resolved
- → Post update to related conversation
- → Close thread
- → Notify customer
- → "Your reported issue has been fixed in latest release"
User feedback analyzed
- → Add tag and note to customer profile
- → Trigger follow-up message
- → Update engagement score

Generate insights FROM Intercom:

Weekly support trends
- → Query conversation volume and tags
- → Post to #support
- → "42 conversations this week, top tag: 'login issues' (12)"
Sentiment analysis
- → Cluster messages by score
- → Surface patterns
- → Share with product
- → "Negative sentiment up 15%, main theme: mobile app crashes"

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