Intercom + Eru
Connect your support data to see how conversations, tickets, and customer sentiment map to your CRM, billing, and product systems. Support patterns reveal churn risk.
What Eru reads from Intercom
Eru connects to Intercom via OAuth and uses the API to read your support data. It discovers your specific configuration—custom attributes, tags, team assignments—to build accurate mappings.
Users and companies
Intercom user and company records with all attributes. Eru maps these to customer entities in your other systems, linking support context to CRM, billing, and product data.
Conversations
Support conversations with messages, participants, and state. Eru analyzes conversation patterns—frequency, duration, escalations—as health indicators.
Tags and attributes
Tags applied to users, companies, and conversations. Custom attributes that track customer segments, contract tiers, or support priority. All become part of the Truth Map.
Team and routing data
Which team handles which customers. How conversations are routed. Assignment patterns that might indicate account complexity or escalation frequency.
Why support data matters for RevOps
Support interactions are leading indicators of customer health. Problems surface in support before they show up in usage decline or cancellation requests.
Sentiment signals
Frustrated customers write frustrated messages. Sentiment in support conversations—even without formal NPS—indicates satisfaction levels that predict retention.
Volume patterns
Customers with increasing ticket volume are often struggling. They might be hitting product limitations, experiencing bugs, or failing to get value. High support load correlates with churn risk.
Resolution quality
Unresolved issues and repeat contacts signal problems. Customers who keep coming back with the same questions aren't getting what they need.
Engagement type
Are conversations about bugs and complaints? Or feature requests and expansion questions? The nature of support interactions reveals where customers are on their journey.
Common use cases
Churn risk scoring
Combine support ticket frequency and sentiment with usage and billing data to identify accounts showing warning signs across multiple dimensions.
Customer health dashboards
Surface support context alongside CRM and product data. See the complete picture of each customer relationship.
Escalation tracking
Track which accounts escalate frequently. Correlate escalations with contract size, product usage, and renewal timing.
Support-to-product feedback
Link support themes to product features. Understand which features generate the most support load and why.
Example: Support-based churn signal
Setup
1. Connect via OAuth
Eru uses Intercom's OAuth flow. You authorize read access to your workspace data. Credentials are stored encrypted.
2. Eru explores your configuration
The agent discovers your custom attributes, tags, team structure, and conversation patterns. It samples data to understand how you use Intercom.
3. Map to other systems
Eru links Intercom users and companies to entities in your CRM, billing, and product database. It uses email matching, custom attributes, and pattern recognition.
4. Surface support signals
Once mapped, support data becomes part of your unified customer view. Eru can include support patterns in watchlists, checks, and Q&A responses.
Other integrations
Connect Intercom to Eru
Turn support data into actionable customer signals.