Do Traditional Contact Center KPIs Still Matter?
KPIs monitor just about everything that happens in a contact center: workflow, scheduling, attendance, agent performance, and customer satisfaction. Managers review these metrics, looking for trends and patterns to confirm things are going well. Or signals that pinpoint places to improve the customer experience, reduce friction and optimize for efficiency.
KPIs change, but one thing stays the same: customers hate hold time. Offering customers a call-back respects their time and keeps them off hold. Your CSAT scores will light up, too!
Your contact center may run like clockwork, with engaged agents answering calls quickly, solving problems, and creating satisfied customers in record time. But without the contact center KPIs and metrics that managers use to measure the effectiveness of their operations, you’d never know for sure.
KPIs matter. And they’re changing quickly. We asked contact center industry influencers to share their insights into the changing role of KPIs and shine a light on new metrics to watch.
Dennis Wakabayashi, CX Expert, Team Wakabayashi:
“I see new kinds of data that we’ve never seen before plugging into customer care; digital footprint metrics like number of chats, or number of clicks to the website, or other additional steps in the customer journey. I think the more companies focus on customer care analytics over marketing analytics, the better. I think that’s where the insight and the wins can be.”
Popular Contact Center KPIs
There are dozens of call center metrics, but these are some of the most popular ones that businesses rely on.
Customer satisfaction (CSAT)
Just as it sounds, a customer satisfaction score shows how satisfied your customers are with your products or services.
Average handle time (AHT)
Average handle time computes the average duration of an entire customer transaction. AHT includes hold time, call transfers, and after call work, too.
Net promotor score (NPS)
This metric expresses the customer’s perception of your brand and how likely they are to recommend your product or service.
First call resolution (FCR)
First call resolution shows the percentage of customer problems that are resolved on the first call or contact with an agent.
Average speed of answer (ASA)
This metric shows the average amount of time it takes for an agent to pick up an inbound call, including any time the customer spends waiting on hold.
Measuring Customer Satisfaction
The arrival of AI-supported tools is expected to flip the script on some of those traditional metrics and introduce some new ones, too.
For example, AI-powered chatbots and virtual assistants make metrics like AHT less important. Why? With bots answering basic questions, the calls that get routed to humans will be more complex, and resolving them may take longer. Your AHT may go up, but if the goal is to have happy customers, then CSAT is a better metric to watch.
Shep Hyken, CS & CX Expert, NYT Bestselling Author:
“If we’re looking at average handle time as a key ingredient to determining whether our agents are successful, well, guess what our agents are interested in doing? Getting off the phone as quickly as possible! We have clients that say average handle time is important. More important is that when we get finished, they give us a high NPS rating — on a scale of 0 to 10, the likelihood of being recommended — or a high CSAT rating. That’s the number one goal. We want the customer to be happy.”
AI-Assisted Tools Bring New Insights
On top of changing the relevance of some traditional KPIs, AI brings new ways of measuring success. Industry experts are excited about sentiment analysis, which is a score that reflects a customer’s feelings about the customer service they’ve received.
Tom Laird, CEO, Expivia Interaction Marketing Group:
In 2023, we are looking at real-time agent assist and real-time sentiment scoring. This means looking at a dashboard and not just seeing just bubbles of cool keywords but seeing if a call is going south, in real-time, based on sentiment scores.
How does it work? Computer programs with natural language processing abilities monitor customer service calls — some in real-time — and offer sentiment scores, usually expressed as line chart, bar graph or heat map. By listening to what customers say and how they say it, the software can reveal whether the customer is happy with the service, or if they feel neutral, or dissatisfied.
By combining sentiment analysis scores with other KPIs such as CSAT or NPS, managers can have a more comprehensive view of their customer service – and a better shot at success.