Customer Service Analytics Helps Drive Customer Experience

Recently, I was conversing with some of my peers at an industry event. One thing led to another, and we finally discussed the hugely successful Unified Payment Interface (UPI) payments in India.

As I write this, UPI has close to 10 billion monthly transactions, which is considered mammoth in the digital payment landscape.

However, banks or payment enablers don’t make any money out of this, whereas merchants and customers prefer this as they don’t have to pay any transaction fee.

So, what is the incentive for banks and payment enablers to continue offering UPI payments?

Data is the incentive that banks and payment enablers get. You can derive actionable insights from this data. You get to know the spending pattern of your users – the type of spending and their appetite for spending.

For example, banks can use this data to underwrite lending for individuals and SMEs who do not have a huge financial history to rely on.

Likewise, what do you do with all your customer interactions as an organization?

Often, customer service is misinterpreted as a cost center, which can lead to a huge uptake in new business for you.

You generate huge volumes of customer interaction data. You can do a lot with this data and make it actionable.

This article is about customer service analytics and how it can enhance the customer experience.

What Is Customer Service Analytics?

Customer service analytics is collecting and analyzing all the information generated by your customer service team and deriving actionable insights from it.

What do you do with all your customer interactions?

You collect a lot of information – their challenges, needs, wants, desires, and recommendations to improve.

Customer service analytics can help you put together all the jumbled pieces of information into actionable insights.

Let us look at some of the customer service analytics use cases.

Customer Pain Points

Your customer service is the first place that understands your customer pain points.

What do you do when you have a problem using a product or service you bought or subscribed to?

You reach out to the customer service department and explain the problem.

If your customer is churning, the reason behind that would be a pain point that you failed to resolve for your customer.

With customer service analytics, you could group all of these customer pain points and try to pre-empt by proactively addressing them.

It is reported that about 85% of customer problems are transactional in nature and can be addressed using self-service tools like knowledge base and FAQs.

Customer service analytics can help you address customer pain points and help you create self-service channels to address transactional queries that do not require the intervention of human agents.

What if the bounce rates are high on your website’s knowledge base and FAQ sections? It is a clear indicator that the content there is not helpful.

Customer service analytics pull out such insights and make every customer interaction channel perform optimally.

Customer Feedback and Suggestions

I presented at a conference and asked my audience for a show of hands on how many of them felt comfortable filling up customer feedback surveys.

Only a few hands went up.

This meant that a majority of them did not feel comfortable.

We dug a bit and realized that most of them felt that the organizations did not act upon their feedback, which is why they don’t feel comfortable.

They didn’t want to spend time on an activity that was not appreciated.

According to a Microsoft report, 37% of Americans believe that brands do not take action on the feedback provided to them.

Customer service analytics can make sense of the feedback received and can convert them into meaningful data.

This can lay the roadmap for your product or service.

For example, your support team would know how happy your customers are with the promptness of their service. Similarly, your product team would know what major improvements need to be made to the usability and features of the product.

Performance Indicators

Customer service analytics help you track key performance indicators (KPIs) and measure performance against service level agreements (SLAs).

Here are some indicators that customer service analytics can throw light on:

• How many customer issues are resolved in the first call?
• How many resolutions are provided by an agent?
• How many reported problems are not resolvable and require intervention at a higher level?
• What is the average time taken to resolve queries?
• How easy do the customers find it to interact with your resources?
• How easily do the agents retrieve information across different systems?
• How often do agents misguide or missell to the customers?

This would allow you to understand the training requirement of agents and areas where there needs to be improvement overall as an organization.

You can also use these metrics to reward agents’ performances in your customer service function. 

Informed Decision Making

Customer service analytics can help tremendously in decision-making.

For example, if 80% of your customers reach out to you for quick resolutions, then you have to make it easy for them to reach your agents or man your chats with live agents.

If a majority of your customers are reaching you through social channels, you need to focus on responding faster on your social channels.

If a majority of your customers give you negative feedback, it is time for you to speak to them to understand their real pain points.

Understanding this would allow you to ensure optimal customer service performance besides reducing the cost and efforts of your customer service.

We have spent time understanding the use cases of customer service analytics.

Metrics for Analyzing Customer Service

Let us take a few moments to understand what customer service metrics should be measured.

1. CSAT Score

The customer satisfaction (CSAT) score asks one fundamental question, which is:

How satisfied are you with our product, service, or customer support?

This is typically requested on a scale of 1 to 5 or 1 to 10.

This is a transactional metric used to evaluate a customer’s specific experience. You usually try to get customers to respond to this within 10 to 15 minutes of interacting with you.

2. Customer Effort Score

Customer Effort Score (CES) is a metric used to measure the effort required for customers to complete a task or resolve an issue.

CES surveys typically have one question, which is:

How easy was it for you to complete your task today, on a scale of 1 to 5, with 1 being very easy and 5 being very difficult?

CES is a customer service metric that helps organizations understand and identify how easy or difficult it is for customers to interact with them.

A low CES score indicates that customers are satisfied with the effort required to interact with a company. In contrast, a high CES score suggests customers are dissatisfied with the required effort.

By regularly measuring Customer Effort Score (CES), companies can track progress and identify areas where they are doing well and need improvement. This would allow them to make data-driven decisions on how to improve the customer experience.

3. Net Promoter Score (NPS)

NPS asks this question:

How likely is it that you would recommend this company or product to a friend or a colleague?

This is typically requested on a scale of 1 to 10.

Responses 9 and 10 are promoters, 7 and 8 are passives, and anything lower than that is detractors.

You calculate the NPS by subtracting the percentage of detractors from the percentage of promoters.

NPS is used as an indicator of customer loyalty and brand devotion. Almost all teams within an organization consume NPS.

4. Customer Health Score (CHS)

The customer health score is a metric used to understand customers’ likelihood to grow, stay consistent, or churn.

CHS is the single metric that would allow you to determine if your customers are staying or planning to leave, as it bridges the gap between customer service teams and customers.

This is not a one-question metric.

You must structure the survey based on your objectives and define the scale. For each value in the scale, plan responses that the customer service would take to address those concerns.

Then this can be a compelling metric to measure. This can be done through surveys, customer interviews, or customer feedback to become very powerful.

Most SaaS companies use this metric religiously to reduce their customer churn.

5. Average Response Time

It is the average time taken by your agents to respond to customer complaints or queries.

The goal should be to reduce the average response time, as the customers typically demand quicker resolutions.

6. First Contact Resolution

It is a key metric that reflects your agent’s ability to resolve a customer query on the first attempt.

This means there is no need for customers to keep contacting you repeatedly, and this would certainly make them happier.

7. Ticket Volume

Understanding the total volume of issues and requests coming into your business can help plan the customer service function.

You can use workforce management and optimization to plan the number of agents with specific skills to address customer needs.

Besides, you can identify innovative ways to reduce the number of requests by proactively acting on commonly reported problems.

How About Qualitative Metrics?

While all these metrics are relevant, they are quantitative metrics that don’t tell how your customers feel about your service.

Most of these metrics are scaled. Imagine asking your customers who provide feedback the following question:

Why Did You Choose That Response?

The insight you gain would be invaluable, and your analytics can make it actionable, resulting in excellent customer experiences.

Customer service data hides more than it reveals. Customer service analytics will help you make sense of it.

While the customer service metrics mentioned here will help you assess if your business is on the right track to offer exceptional customer experiences, it is extremely important to assess the qualitative data to understand the depth of customer experience completely. Customer service analytics will help you focus on how your customers perceive your customer service and business and how well your teams perform to meet the rising customer expectations.