Support Requests

Measure the total number of support requests that have come in.

Support Requests

36 vs. 32 requests per day last period

Total incoming support requests tracked daily over the last period.

Support Requests is a metric that counts the total number of incoming requests your support team receives in a given period.

What is Support Requests?

Support Requests is the total count of customer-submitted requests that arrive in your support queue over a defined time period. It tells you how much work is coming in, so you can staff appropriately and spot demand trends before they become backlogs.

Why Support Requests matters

Volume is the foundation of every other support metric. Without knowing how many requests are coming in, you can't make sense of resolution times, agent utilization, or cost per ticket. A sudden spike in Support Requests can signal a product issue, a confusing process, or a gap in your self-service content. A steady decline might mean your knowledge base is working, or it might mean customers have stopped trying.

Tracking Support Requests daily gives your team the visibility to act early rather than react late.

How to calculate Support Requests

The formula is straightforward:

Total number of requests submitted

Count every request that enters your queue within the reporting period, regardless of channel, status, or outcome.

How to use this metric

Support Requests is most useful when tracked over time and alongside other metrics. A few ways to put it to work:

Spot demand patterns: Rising volume on specific days or after specific events points to where friction lives in your product or process.
Plan staffing: Consistent volume trends help you schedule agents and set realistic response time targets.
Benchmark resolution capacity: Pair Support Requests with First Contact Resolution and Average Resolution Time to see whether your team is keeping pace with demand.
Catch product issues early: A sharp increase in requests often surfaces before a formal bug report does.

If you're pulling this number manually each day or explaining context to a generic AI tool every time you want a trend, a connected dashboard removes that friction. Your volume data stays current, and patterns become visible without digging.