Implement These 5 Customer Experience Analytics to Upgrade Your Call Center

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Experts agree: It pays to prioritize the customer experience. So what if we told you that analytics could be the secret ingredient you’re missing?

To help you craft a seamless CX journey from start to finish, we’re taking a look at how to unlock the benefits of customer experience analytics, what this means for your support team, and how you can upgrade it to deliver delightful experiences from every interaction.

What Is Customer Experience Analytics?

Put simply, customer experience analytics is the collection and analysis of customer data from a variety of sources.

Data used in customer experience analytics can be drawn from any interaction between an organization and its customers. That includes reviews of your company’s products or services, customer interactions on social media, customer conversations with contact centers, and much more.

That’s a lot of data! To break it down, in a CX analytics strategy, support teams should consider both direct feedback customer data and indirect feedback customer data.

Direct feedback includes traditional CX metrics and KPIs gained by directly asking the customer questions or sharing surveys such as CSAT, NPS, CES, OR CLV, which we’ll break down below.

1. CSAT: Customer Satisfaction

This is the extent to which a customer feels their needs have been met. It’s usually measured with a one through five rating, ranging from Very Unsatisfied (one) to Very Satisfied (five).

2. NPS: Net Promoter Score

Net Promoter Score is a single number (usually between zero and 10) that shows a customer’s response to the question “How likely are you to recommend a [Brand/Product/Service] to a friend or colleague?”

3. CES: Customer Effort Score

A single number (usually between one and five or one and seven) that shows a customer’s level of agreement with the statement “[Brand/Product/Service] made it easy for me to handle [customer challenge]”.

4. CLV: Customer Lifetime Value

CLV is a metric that shows the total revenue a company is likely to receive from a single client or customer.

For the mathematicians among us, it can be calculated as CLV = Average purchase cost * average number of purchases per year * average customer retention rate in years.

A great support team can increase each of these factors, boosting your business’s CLV.

5. Feedback survey responses

Written responses, not always quantified by a numerical scale, to questionnaires or research surveys your organization has sent directly to customers.

Meanwhile, indirect feedback includes data that hasn’t been received directly from the customer but instead measures how customers interact with your business, for example:

Customer churn rate

Also known as attrition rate, customer churn rate is the rate at which a customer stops purchasing a company’s products or services in a set time period.

Customer renewal rate

A customer renewal rate (sometimes referred to as a customer retention rate) is the percentage of a company’s customers that grow their relationship with the company by purchasing more products or services.

Customer review monitoring

This involves tracking customer reviews from different sources, for example, iOS or Android app stores or online shops.

Data from voice interactions and calls

Data from voice interactions can include transcripts and analysis, as well as additional metrics like missed-call rates, wait time, and more.

Given their central place in the customer experience, call center interactions are a rich data source for customer experience analytics (more on this ahead!).

Why CX-Specific Analytics Metrics Matter

Customer support teams should keep it top of mind that customer-centric companies are 60% more profitable than those that are not. And, in the U.S., 90% of people use customer service as a factor when deciding whether or not to do business with a company.

So given that customer experience is a defining factor in the success of your business, there are clear benefits of CX analytics.

By using customer experience analytics, you can create a best-practice approach to customer experience, as they help you with:

• Identifying where customer needs are not being met and the root causes of customer pain points

• Showing you where the customer journey can be streamlined by removing unnecessary steps. For example, you might discover using an Interactive Voice Response (IVR) system would help your support team rapidly classify callers and route them to the right resource

• Highlighting successful products, services, or interactions so they can be replicated and iterated on

• Revealing trends in how customer touchpoints are impacting your customer’s experience

How Analytics Improve the Customer Experience

Continuous improvement is at the heart of great customer support, and customer experience analytics provide the information you need to do just that.

Let’s look at how you can make those analytics work for your support team.

Personalized customer experiences

When a customer calls customer support, their worst fear is that they’ll become just another ticket number. Creating a great customer experience means ensuring every interaction is human, personal, and streamlined.

Personalization builds meaningful connections with customers, differentiates your approach from your competitors, and forges lasting partnerships.

Customer experience analytics can enable personalization in several ways, including enabling better audience segmentation. By gathering and analyzing customer data, you can create target audience segments and personas. As a result, you can clearly understand different customer needs.

For example, if a senior sales manager gets in touch for support, their concerns will differ from those of an IT security leader. Using customer experience analytics to define those nuances helps you personalize an initial response and fast-track their customer journey.

Improved loyalty, reduced churn, and increased repurchases

CX analytics can show you where your business is delighting customers and where it’s faltering. And you can do this across the dozens of digital touchpoints, including social media and online stores.

After analyzing the customer journey, you might discover you could use IVR to route queries more efficiently or need monitoring and coaching to nip any mistakes in the bud.

In this way, customer experience analytics enable you to attract new customers and, just as importantly—given that current customers are 50% more likely to try new products and spend 31% more on average—retain existing ones.

More knowledgeable teams; better customer relationship management

There’s no question about it: Strong customer experience analytics make for a stronger customer support team.

Take customer reviews for example. By analyzing the latest, CX analytics can provide support teams with knowledge of recurring issues. That means when a customer calls with a question, the support team is ready to respond.

And, by providing up-to-date insights, customer experience analytics enable improved customer relationship management—for both retained support workers and new ones.

For experienced members of the support team, it provides a well of information that helps them up their game. But for new hires, it also offers improved support training experiences. By building training around the latest real-world insights, as well as resources like call recordings, you ensure everyone delivers a consistent, tailored customer experience.

5 Metrics Your Call Center Dashboard Is Missing

Few interactions have the potential to delight customers more than a meaningful conversation with a knowledgeable, empathetic support team.

To maximize the value of your contact center, though, you need to collect data. As we’ve seen, this is the secret ingredient for making the future customer experience even better.

Aircall’s dashboard is designed to make that simple, keeping all the essential stats front and center. It organizes and presents data in a digestible way that makes it simple to sort and find what you need. It means your support team can use their business phone system to see—and act on—customer experience analytics in real-time.

So what are the must-have metrics to analyze in your call center dashboard?

Wait time

Average wait time shows you how long a customer usually has to wait until they interact with your business. Let’s be honest: Nobody likes to be put on hold. The longer a customer is waiting, the more likely they are to have a negative perception of your business.

So knowing how long customers have to wait and taking action to decrease it is a key element of delivering a positive experience.

Missed-call rate

Customers call because they want to interact, solve a problem, and get support. Ultimately, missed calls mean letting the customer down. By tracking your missed-call rate, you can make sure to keep them at an absolute minimum.

Following that analysis, you might realize you need time-based routing to better align your calls with availability in the support team. Or that a ring-on speakers feature could help reduce the risk of accidentally missed calls by ensuring you hear every call loud and clear.

Response time

Response time is how long it takes for a customer to get a callback. This could potentially be a result of when a customer gets in touch via a different method like email.

Long response times are a sign that your customer support processes aren’t joined-up. It could also mean that you’re not communicating effectively with customers to keep them updated.

If your response time becomes too long, customers might think you’ve forgotten about them. In turn, this can mean they raise their original issue again, which restarts the process.

33% of customers state that the most frustrating thing about customer service is repeating themselves to multiple support reps. Bottom line: Keep track and ensure those response times are short and snappy!

Average call time

Your average call time, also known as Average Handle Time (AHT) is the duration of an entire customer call. And it includes everything from when the customer hits the dial button on their phone to when they hang up. It also includes everything in between, including hold time and transfer time.

Average call time shows you how efficient your support operation is. For customers, a low average means they’re more likely to feel respected and prioritized. Depending on your industry, average call times will differ, so it’s worth researching and benchmarking against those in your sector.

Gaining sight of your average call time can help you identify issues. These can range from causing longer calls, reducing “dead air” time, and providing better resources to your support team.

Activity feed

We’re sort of cheating by including this one, as Aircall’s activity feed is more than just one metric. It gives you insight into all call activity and enables you to adjust user availability on the fly. From there, it can help your support team spot problem calls and jump in to coach in real-time—all from within the Aircall dashboard. And with clarity on who’s available and who isn’t, it’s simpler to direct customer support questions.

This means getting customers connected with agents faster. As a result, they’ll be able to spark those meaningful interactions that are the bedrock of a golden customer experience.

Support teams have access to more data than ever before. While that can be overwhelming, embracing customer experience analytics can unlock a new era of wonderful interactions with customers.

And, given voice interactions are at the heart of any human-centric customer support operation, the right data is essential to improving your call center.

Want to gain the insights you need to boost your support team, create fantastic customer experiences, and ultimately improve your business? Reach out to the Aircall team today.

Published on July 6, 2022.