Customer Support KPI

Ticket Resolution Time Formula

Learn what Ticket Resolution Time means, how to calculate it in Excel, and how to recreate the same KPI as a Power BI DAX measure.

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Resources related to this KPI and spreadsheet reporting.

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📚 Step-by-step booksStart with beginner-friendly step-by-step books and learning resources from Create & Learn.📊 KPI dashboard resourcesBooks and templates for building customer support KPI dashboards in spreadsheets.📈 Business metrics booksReferences for understanding customer support metrics, definitions, and reporting habits.📘 Excel reporting guidesGuides for turning spreadsheet calculations into clear reports and dashboards.

Quick answer

Ticket Resolution Time is calculated as:

Total Time to Resolve / Resolved Tickets

Use this Excel version when your inputs are on row 2:

=IFERROR(B2 / C2,0)
Example result10.6 days/hours
FormatNumber with unit such as days, hours, or months
Typical chartLine chart for trend; column chart by queue, team, project, or location.

What is Ticket Resolution Time?

Ticket Resolution Time measures speed, delay, or duration. It helps show whether work is moving quickly enough and whether process changes are improving performance.

Customer support KPIs track service speed, resolution quality, workload, satisfaction, and support cost.

Beginner tip: A KPI is not just a formula. It is a number used to make a decision. Before adding it to a dashboard, write down the definition, time period, owner, target, and data source.

Real-life example

Imagine a support manager reviewing team performance. The team adds the inputs for Ticket Resolution Time to a support operations dashboard, calculates the KPI for the current month, and compares it with the previous month and target. In the sample below, the result is 10.6 days/hours. That number becomes useful when everyone uses the same formula each month.

Excel cellInputWhat it meansSample value
B2Total Time to Resolvethe total time measured using the same unit for every row9,500.0 days/hours
C2Resolved Ticketsthe number of records included in the same reporting period900
ResultTicket Resolution TimeOutput of the KPI formula10.6 days/hours

How to calculate Ticket Resolution Time in Excel

  1. Create one row per reporting period, team, product, campaign, location, or customer segment.
  2. Add one input per column. Do not combine inputs in the same cell.
  3. Paste the Excel formula in the KPI result column.
  4. Format the result as Number with unit such as days, hours, or months.
  5. Copy the formula down the table and compare the result against target, previous period, and trend.
Quality check before publishing:
  • Use the same date range for every input.
  • Confirm that the denominator is not blank or zero.
  • Document whether the KPI is calculated before or after discounts, refunds, taxes, returns, or cancellations.
  • Keep the definition stable so reports remain comparable over time.

Power BI DAX measure

If you also report this KPI in Power BI, create a measure instead of hard-coding the calculation in a visual. Replace the measure names below with the names used in your model.

Ticket Resolution Time = DIVIDE([Total Time to Resolve], [Resolved Tickets], 0)

For best results, build base measures first, such as revenue, cost, customers, orders, or tickets, and then build the KPI measure from those base measures.

How to read the result

Lower is usually better, because this KPI often represents cost, waste, delay, risk, loss, or friction.

Do not read the KPI alone. A single value can be misleading without a target, trend, segment, and business context. For example, the same result may be good for one product line but poor for another.

Useful comparisons

  • Current month versus previous month.
  • Actual result versus target or budget.
  • By channel, product, customer segment, team, or location.
  • Rolling average over several periods to smooth one-off spikes.

Common mistakes

  • Mixing time periods, such as monthly cost with quarterly revenue.
  • Using a total when the KPI should be segmented.
  • Changing the formula definition after the dashboard is already in use.
  • Comparing two teams that collect the inputs differently.
  • Ignoring blanks, zeros, refunds, cancellations, or duplicate records.