Call center

11 Contact Center Analytics that Helped me to Retain 100+ Clients

I started HiredSupport in 2016. We worked with multiple clients ranging from small medium businesses to large corporations. Over the years, with continuous feedback, we made a lot of improvements in call center outsourcing services, operations, and client management. The constant feedback loop helped me to retain 100+ clients over a period of time.

These feedbacks have a fancy name for them – ANALYTICS! And when it comes to call center feedback, it’s called contact center analytics.

Let’s discuss more about it.

What is Contact Center Analytics?

Contact center analytics help to gain valuable insights that set the direction to improve operations, reduce costs, and assure quality. For example, the following are some of the analytical insights that helped us to make the right decision for improvements:

The churn rate is high, so we need to work on client satisfaction.
The client satisfaction score is low, so we need agents to maintain better quality.
Customers are having issues connecting on call, so we need a better landline system to improve the quality.

You should note that I used the words “churn rate” and “client satisfaction”. These are NOT analytics; these are KPIs.

This brings us to the next part if KPIs and Analytics the same?

Difference Between Contact Center Analytics and Contact Center KPIs?

Analytics represents the process of finding insights out of the KPIs (key performance indicators) that one decides for a campaign. KPIs are the subset of analytics.

For example, I measured that the churn rate is high, so we need to work on client satisfaction.

“Churn Rate” would be a metric.

“We Need to Work on Client Satisfaction” is an insight drawn from the analytics.

With this example in mind, you can use the following table to differentiate between them:

Aspect	KPIs	Analytics
Definition	A specific metric	The process of interpreting metrics
Example	Churn Rate – Measures the percentage of clients lost over a specific period.	Analyzing churn rate data as one point to understanding why clients are leaving
Purpose	Tracks performance towards a key goal (e.g., client retention).	Transforms raw data into insights that can inform decision-making.

In short:

KPIs are the key metrics that indicate whether you’re reaching your goals.
Analytics is the process of interpreting those metrics to provide actionable insights.

Why Do Business Owners Need Contact Center Analytics?

Like I said in the beginning, a call center needs constant improvements in its processes like any other business. Contact center analytics help you to gain valuable insights while making the right decisions.

It can help you with the following aspects:

To identify problems
To manage agents’ performance
To manage client satisfaction
To manage customer satisfaction

In addition to the problems listed above, it can help you to analyze every single business problem that you may come across.

11 Types of Call Center Analytics that Helped Me to Retain 100+ Clients

To retain a client, I analyzed that we need to fulfill the following criteria:

The expectations are delivered
The client should feel that it’s ROI positive
The agent should perform in a productive manner
A customer should feel satisfied with our service

Once I analyzed that there were four potential buckets where I needed to produce the quality, I created analytics for each bucket.

Here’s how:

Goals	Analytics Type
The expectations are delivered	Task Urgency Analytics Resource Availability Analytics
The client should feel that it’s ROI positive	Cost per Call Analytics Revenue per Call Analytics Customer Retention Analytics
The agent should perform in a productive manner	Performance Analytics Workload Analytics Quality Assurance Analytics
A customer should feel satisfied with our service	Customer Satisfaction (CSAT) Analytics Net Promoter Score (NPS) Analytics Escalation Analytics

To Do Exercise:

Step 1: Write all of your goals.

Step 2: Quantify your goals.

Step 3: Set KPIs for them.

Boom, you created analytics for your goals!

1. Task Urgency Analytics

Task urgency analytics helps to assess and analyze the tasks based on their level of urgency. This helps to measure the urgent task that needs priority and the tasks that can be scheduled for later.

If a business owner has an expectation from the contact center that specific types of customers should be prioritized when handling customer service, Task Urgency Analytics helps you to prioritize them effectively.

For example, Sentisum is software that automatically prioritizes tickets based on urgency, see below:

To process these analytics, I used to measure the following metrics under it:

Percentage of tasks completed by due Date
Average time to complete tasks
Number of high-priority tasks completed on time
Average priority rating of completed tasks
Task backlog size

2. Resource Availability Analytics

Resource availability analytics again comes under the umbrella of delivering expectations. It analyzes if there were some important chats and your contact center didn’t have an agent to assign.

For example, see below how CloudTalk helps to measure the availability of agents:

The unavailability of any agent while a potential customer is waiting can also lead to the loss of revenue. In such cases, a contact center owner should analyze the frequency of it and if they need any additional resources to add.