First Response Time

What is first response time (FRT)

First Response Time refers to the time elapsed between when a customer first submits a request or inquiry and when they receive the first human or automated reply. It’s a direct reflection of how quickly your support team acknowledges a customer issue.

Impact of first response time in customer support

This is the customer’s first impression of your support experience. A fast First Response Time signals attentiveness and care, even if the issue takes longer to resolve. A delay, on the other hand, can increase customer anxiety, trigger unnecessary follow-ups, and lead to escalations or churn. Internally, first response time reflects the efficiency of your queue management, staffing adequacy, and triaging workflows.

Formula + Example/Use Case

Formula:
Total time to first response for all tickets ÷ Number of tickets
= Σ(FRTs) ÷ N

Example:
If a customer submits a ticket at 10:00 AM and the agent replies at 10:15 AM, the First Response Time is 15 minutes. For 100 tickets, if the combined time to first response is 1,200 minutes, then FRT = 1,200 ÷ 100 = 12 minutes.

What affects first response time

• Agent availability and staffing levels: If there aren't enough agents online, especially during peak hours, FRT naturally increases.
• Ticket routing logic: Poor routing mechanisms can delay assignment to the right agent, causing lag in response.
• Support volume spikes: Unexpected increases in ticket volume, such as after product launches or outages, can overwhelm teams.
• Customer support channel: Channels like live chat often have faster response expectations than email or social media, which can skew averages.

How to improve first response time

• Use intelligent auto-responders: Provide instant acknowledgments with useful links or expected wait times, so customers feel heard immediately.
• Implement smart routing systems: Leverage automation to send tickets to the most suitable agent or team based on issue type, channel, or priority.
• Staff according to real-time demand: Use historical data to predict high-traffic periods and schedule agents accordingly to reduce wait times.

Benefits

• Builds trust early in the interaction: Customers feel that their time and issue matter from the start.
• Reduces unnecessary follow-ups: When customers receive prompt replies, they’re less likely to resend or escalate.
• Boosts perceived service quality: Even if the resolution takes time, a quick acknowledgment sets the right tone.