KPI Tree

Intercom Metric

Customer Support

Repeat Contact Rate = Customers with Repeat Contacts / Total Customers Contacting Support × 100

Repeat Contact Rate measures the percentage of customers who contact support about the same or a closely related issue within a defined window after their initial conversation was closed. It reveals incomplete resolutions, workarounds masquerading as fixes, and systemic product issues that generate recurring support demand.

Full guide: definition, formula, and benchmarks
IntercomCustomer Support

Repeat Contact Rate

Repeat Contact Rate measures the percentage of customers who contact support about the same or a closely related issue within a defined window after their initial conversation was closed. It reveals incomplete resolutions, workarounds masquerading as fixes, and systemic product issues that generate recurring support demand.

How to calculate repeat contact rate

Repeat Contact Rate = Customers with Repeat Contacts / Total Customers Contacting Support × 100

Why repeat contact rate matters for Intercom users

Repeat contacts are the most expensive kind of support - they consume agent time on issues that should have been resolved, frustrate customers who expected a fix, and inflate volume metrics in misleading ways.

For Intercom teams, a high repeat contact rate signals that agents may be closing conversations prematurely, that solutions are temporary rather than permanent, or that underlying product issues need escalation to engineering. Reducing repeats is one of the highest-leverage improvements a support team can make.

Understand and act on repeat contact rate with KPI Tree

Identify repeat contacts by matching customer and topic data from Intercom in your warehouse. Model repeat contact rate in KPI Tree and link it to conversation resolution rate and customer effort score.

Assign RACI ownership to quality assurance leads and use repeat contact data to identify the top recurring issues for root-cause resolution with product teams.

Get started with your Intercom data

Query using MCP
MCP

Pull metrics from Intercom directly through the Model Context Protocol.

Data Warehouse
SnowflakeBigQueryDatabricksRedshift

Connect your existing warehouse where Intercom data already lands.

Professional Services
FivetranSnowflakedbt

Our professional services team can build you turn-key AI foundations in a matter of weeks. Data warehouse on Snowflake/BigQuery, ELT with Fivetran, all modelled in dbt with a semantic layer.

Related Intercom metrics

Conversation Resolution Rate

Customer Support

Metric Definition

Resolution Rate = Conversations Resolved (Not Re-opened) / Total Conversations × 100

Conversation Resolution Rate measures the percentage of support conversations that are closed and remain closed - without being re-opened by the customer within a defined window. It distinguishes genuine resolutions from premature closures that leave the customer's issue unaddressed.

View metric

Customer Effort Score

Customer Support

Metric Definition

CES = Sum of Effort Ratings / Total Responses

Customer Effort Score (CES) measures how much effort a customer must expend to get their issue resolved through Intercom. It is typically captured via a post-conversation survey asking customers to rate the ease of their experience. Lower effort strongly correlates with higher retention and loyalty.

View metric

Average Resolution Time

Customer Support

Metric Definition

Resolution Time = Conversation Resolved Timestamp − Conversation Created Timestamp

Resolution Time measures the total elapsed time from when a customer opens a conversation in Intercom to when it is marked as resolved. It encompasses first response time, back-and-forth exchanges, internal investigation, and any waiting periods. It is a primary indicator of support efficiency and customer experience.

View metric

Support Ticket Escalation Rate

Customer Support

Metric Definition

Escalation Rate = Escalated Conversations / Total Conversations × 100

Support Ticket Escalation Rate measures the percentage of conversations that require escalation from first-line agents to senior specialists, managers, or other departments. High escalation rates indicate gaps in first-tier training, documentation, or tooling that prevent frontline resolution.

View metric

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