We all live online, and let's be honest, our patience has worn pretty thin. When you have a question for a company, waiting hours for a reply feels like an eternity. And a slow response doesn't just feel bad, it’s actively bad for business.
According to Sprout Social, a whopping 73% of people will just go buy from a competitor if a brand takes too long to respond. So yeah, speed isn't a bonus feature anymore, it's the price of entry.
The problem is, there’s often a huge gap between what customers expect and what support teams can realistically deliver. This leads to frustrated customers, people canceling their subscriptions, and a support team that feels like they’re always one step behind.
This guide will give you some practical tips for lowering your first reply time. We'll start with the foundational stuff, look at the tech most teams are already using, and then dive into how modern, integrated AI can help close that expectation gap for good.
What is FRT and why does it matter?
First Reply Time, or FRT, is simply the time between a customer sending a support ticket and a real person on your team sending the first reply. Those automated "we got your email" confirmations don't count here. We're talking about the moment an actual human steps in.
But FRT is more than just a number on a dashboard. It's your customer's first real impression of your support. A quick FRT says, "We see you, and we value your time." A slow one... well, it sends the exact opposite message, creating a bad vibe before you've even had a chance to help. It's not surprising that a lower FRT almost always leads to happier customers, better loyalty, and fewer cancellations.
So, what does "good" actually look like? It can vary, but here’s a rough guide to aim for.
| Channel | Good | Better | Best |
|---|---|---|---|
Frequently asked questions
A low First Reply Time (FRT) shows customers you value their time and leads to higher satisfaction and loyalty. Conversely, slow replies can drive customers to competitors, making it a critical metric for business success.
SLAs provide measurable targets for response times, turning vague goals into actionable objectives. They help teams understand expectations and identify areas where processes might be causing delays.
Manual triage creates bottlenecks as agents must sort every ticket, slowing down the initial response. This manual step can significantly delay the first reply, especially during high ticket volumes.
A knowledge base allows customers to self-serve, preventing tickets from being created and thus lowering FRT. However, keeping it updated and easily searchable can be challenging, often forcing agents to leave their helpdesk to find information.
Modern AI agents integrate with all your existing knowledge sources, learning from past tickets and internal docs to provide accurate, helpful first replies. First-generation chatbots were often disconnected, providing generic answers that frustrated customers.
Modern AI platforms like eesel AI are designed for self-service, allowing you to connect helpdesk and knowledge sources and launch an AI agent in minutes. This rapid deployment means you can start seeing improvements almost immediately without extensive setup.
Unifying knowledge sources means AI learns from your public help center, past tickets, and internal documents. This allows the AI to give highly relevant and accurate first replies, often solving issues instantly and significantly reducing FRT.
