There's a significant volume of data being generated from your contact center. Each interaction offers insight into a customer's needs and whether those needs were met. That data ends up on a dashboard most of the time, and for many organizations, that’s where it ends.

Just knowing your average handle times rose last month won't actually move the needle for your operation. What truly drives better outcomes is when an organization identifies a key performance indicator to enhance and then uses that insight to improve their operations.

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Here are 5 ways to utilize that data and establish those improvements. These strategies all build on one another, but you don’t need to implement all five to start seeing results.

1. Connect analytics to specific business goals

Start with the pain point you’re trying to address.

It could be a recurring billing issue customers keep bringing up. It could be that the quality of service your customers experience varies dramatically by agent, or that you're observing an increase in customer churn. Identify the core issue before you look at the numbers.

Once you’ve identified a pain point, map it to measurable goals. Maybe you want to see your agents get better at helping customers with their billing inquiries, or perhaps you’re targeting a 15% decrease in repeat billing-related contacts over the next three months. That’s a clear objective, and it gives your team a target to hit by a certain date.

Then, you'll want to choose metrics that show whether the issue you first identified is actually improving. Analytics that pertain to resolving the customer’s issue will include first contact resolution and repeat contact rate. Analyzing AHT and cost per resolution can help measure your team’s efficiency. Quality is another metric to consider when tying analytics to a business objective.

Here's where a lot of teams go wrong. They laser-focus on efficiency without recognizing other factors. Shorter calls look great on a report, but if a rushed agent leaves a question half-answered, the customer calls back, and you've now paid for two calls instead of one. Always pair an efficiency metric with a customer outcome.

Practical example: Track average handle time for billing calls alongside the repeat contact rate for those same calls. If handle time drops and repeat contacts hold steady or fall, you've found a real improvement. If repeat contacts climb, the faster calls were just pushing work into next week.

2. Analyze conversations across channels for a fuller picture

By looking at both voice and digital, you can learn how your customers look for assistance, and most importantly, where and how they fail.

There will never be enough quality assurance resources to manually review every conversation. Analysis can highlight what your customers are asking about on every call or chat.

Focus on customer friction points. Why are customers switching from one channel to another? Do they have to state their account number multiple times or request an agent? These moments often spark customer frustration.

Group these insights by contact reason or customer profile. As mentioned above, you may not see patterns if you look only at your contact center as a whole. A 4% transfer rate across the contact center could be obscuring one product or specific customer problem that has a 20% transfer rate.

Practical example: Find customers who used chat and then called about the same issue within 48 hours. Review those chat transcripts. If agents or bots are giving incomplete answers, you've found a fixable source of extra call volume.

3. Use root cause analysis to prioritize improvements

Determining that a metric has changed is easy. The value lies in determining why it changed.

The real work of root cause analysis is in scrutinizing the calls that actually produced those outcomes. Find the calls associated with negative surveys, repeats and escalations and see what actually took place during those interactions. Patterns will emerge rather quickly once you’re looking at the right calls.

Validate before acting. Review a sample of relevant customer interactions and cross-reference with other data whenever you identify a trend. That huge increase in complaints may correlate directly with a website outage or a price change that has nothing to do with how your agents are handling calls.

Consider the frequency and customer impact of the issue vs. how much work it will take to resolve it. A high frequency, high pain problem that’s easy to fix moves to the top of the queue.

Practical example: Say delivery-related calls jump 30% in a month. Analytics flags the trend, but the conversations tell you what's behind it. Are shipments actually arriving late? Or are customers confused by tracking updates that say "in transit" for five straight days? The first is a logistics problem. The second is a communication problem, and it needs a different fix and a different owner.

4. Turn quality insights into targeted agent coaching

Contact center analytics can help you provide more specific coaching by identifying the behaviors that consistently appear in your top performers’ calls. Conventional quality monitoring programs review a small fraction of calls. Automated monitoring enables you to analyze every interaction, so you can understand how each agent is truly performing. Have your QA analysts review automated results and validate them for accuracy before acting on that data.

Tailor each agent’s coaching plan to address their demonstrated needs rather than forcing everyone through the same generic coaching session. Consistency is important as well. Normalize your scoring metrics frequently so that two raters would score the same call the same way, because agents lose faith in a quality program when feedback seems subjective.

Practical example: Coach an agent on explaining billing adjustments in plain language, using a couple of their recent calls as examples. Over the next month, check whether repeat contacts about billing adjustments decline among that agent's customers.

5. Build a continuous improvement process

Schedule regular intervals for discussing insights and what you will do about them. Weekly cadence works for some groups, while monthly works for others. Ensure that every meeting results in action items.

Name an owner for each initiative and clearly define how you’ll measure success. Without both, good ideas stall out between meetings, and nobody can say whether the work made a difference.

Share your findings beyond the contact center. Your agents learn about product defects and billing misunderstandings before anyone else in the organization, and product teams and billing operations need to know because they can often eliminate the reason for the contact in the first place.

Test before you scale. Try a change on one team or with one type of contact, measure the results and scale only if it’s successful. Compare against your baseline when you measure, and consider external factors. Seasonal demand or an unexpected increase/decrease in volume can skew how effective a change really was.

Practical example: Rewrite how agents explain your cancellation policy and test the new approach with one team for a month. Compare that team's repeat contacts and customer feedback against the rest of the center. If the numbers improve, roll it out. If they don't, you've lost very little.

Make contact center analytics part of everyday decisions

Contact center analytics doesn’t deliver ROI until an insight drives an improvement and someone measures if that improvement worked. Anything less is simply reporting.

That’s why you shouldn’t try to improve everything at once. Instead, choose one opportunity with the potential to create a big impact. (The repeat contact driver costing you the most is a great place to start.) Work through each of the five strategies. You’ll learn more from one completed improvement than you will from a dozen dashboards that nobody uses.

CallMiner Eureka analyzes every customer interaction across voice and digital channels so you can understand what’s really happening in your contact center. We turn data into actionable insight your leaders can use to make decisions and your agents can use for coaching.

Frequently asked questions

Which contact center analytics metrics should you track?

First measure the metrics associated with the problem you’re trying to fix. That typically means combining a resolution metric such as first contact resolution or repeat contact rate with a customer metric like satisfaction or customer effort. Then, measure efficiency metrics such as average handle time only in conjunction with those outcome metrics, never by themselves.

What is the difference between contact center reporting and analytics?

Reporting shows what happened. Analytics explains why. Reporting indicates that repeat contacts increased 12% last month, while analytics investigates the conversations that contributed to that number and discovers customers were confused by a new billing statement.

How do you measure the ROI of contact center analytics?

Tie every initiative to a baseline and a dollar figure. If analytics allows you to eliminate 10,000 repeat contacts about billing per year, and each contact costs $6, you just saved $60,000 against the price of the program. Improvements in retention and lower compliance risk are harder to quantify, but they still count towards your return.

What are common contact center analytics mistakes?

The most common mistake is collecting insights you never do anything with. Other mistakes include pursuing efficiency metrics in isolation, never setting a baseline, relying too heavily on averages when outliers can point to trouble segments, and holding agents accountable for failures in policy or product.

Can contact center analytics replace manual quality assurance?

No, not entirely, but it will alter the role. Automated contact analysis will instantly score every interaction, not just a sample. Somebody still needs to confirm what the software identifies and make nuanced decisions the automation can't quite master. The strongest programs let analytics find the calls worth reviewing so analysts can spend their time on those.