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Using Data Mining To Improve The Customer Experience In Your Call Center

Using Data Mining To Improve The Customer Experience In Your Call Center

[fa icon="calendar"] Dec 1, 2016 6:55:22 AM / by Jade Longelin

Jade Longelin

 

Businesses today are drowning in a sea of data─call centers produce tens of billions of gigabytes and work-hours per year, almost all of it recorded. For call center managers, this represents an incredible opportunity to fine-tune processes, come up with innovative solutions to problems, and increase profitability. However, it can be difficult to know where to start, let alone identify action points where change is needed.

Mining for data is like panning for gold─you’re looking for something specific, not scooping up stuff at random. Your key performance indicators give you a guide to measure your data against. Use them to organize the information coming at you.

 

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Define a good customer experience

Businesses might think they know how to create a good customer experience, but it’s not always intuitive. You might have hired an award-winning designer to redo your website, but your customers just find it confusing.

 

When using data mining to improve the customer experience in your call center it’s a good idea not to take anything for granted. Look closely at your customer satisfaction surveys for a preconception-free overview of your customers’ real wants and needs.

 

Customer segmentation for personalization

Good data mining lets you really get to know your clientele. You can group them by age, gender, location, income, and interests. You can obtain information relevant to your needs, such as normal calling times for specific groups of customers.

 

New technology, such as behavioral analytics, can even tell you which customers want agents to act breezy and friendly and which customers prefer a more formal interaction style.

 

Your customers might have different definitions of great customer service, but their horror stories probably sound remarkably similar.

 

Improve bad customer experiences

The first step to creating a good customer experience is to look at terrible customer experiences. If you see that 30% of your callers are hanging up on the IVR without completing the call, you know that updating your self-service system will improve the customer experience.

**Is your IVR(Interactive Voice Response) doing more harm than good?**

You can search through the records to see exactly where they hung up or called for agent assistance. Once you’ve identified the problem areas, you can come up with a plan to fix them.

Maybe you need to upgrade your system, or customers have been calling about an old product that is not in the IVR database.

 

A good analysis of your data can show where customers jumped ship. If there is a section of the process that shows up regularly as a problem area, you can drill further down to identify the root causes. Maybe there is a hardware or programming issue that needs to be fixed.

 

Using data mining to improve the customer experience in your call center lets you focus on fixing technical problems, as well as human problems that might come into play with your agents.

 

Take a close look at agent behavior

New software makes it possible to collect more details on customer/agent interactions that ever before. Call center managers can easily see which agents are doing well, with few supervisor assists, a low number of transfers, and short hold times.

 

It’s also easy to see who engages in unprofessional behavior, such as leaving customers on hold for a long time or disconnecting calls. You can quickly identify which agents should be rewarded and those who might need further training.

**4 die-hard coaching tips to hold everyone accountable**

 

Take advantage of new technology

Most call centers record calls, but only a few of them are reviewed. Avaya’s report, Analytics in the Contact Center: The Road to a Better and More Profitable Customer Experience, states that call center supervisors usually review only 1% or 2% of recorded calls, and then only for training purposes.

 

New technology makes it possible to collect highly detailed and complete information, which can be analyzed to help your customers and your bottom line.

  

Speech and interaction analytics

Speech analytics programs have powerful word detection engines that can analyze the spoken word, identifying conversational trends and emotional tone, even specific words and phrases. Real-time speech analytics programs can flag a call where emotions are running high, allowing a supervisor to take over and handle the issue.

**Speech analysis: The future of QA monitoring**

 

The International Customer Management Institute reported on the case of a telecommunications company that found customers phrases such as “still not working” or “I have called multiple times,” as well as competitor names and prices, were highly predictive of lost business.

 

The company was able to identify customers most likely to leave and organized an outbound call campaign. The customers they contacted were 4 times more likely to stay than customers who didn’t receive the special treatment.

 

Use your social media data

Collecting data from the world outside the call center can allow you to predict customer trends before they happen. For instance, you can use low-cost social media listening tools to search Twitter for words or phrases that might indicate rising customer complaints.

 

Samsung phone blew up” was discussed on Twitter when it was still a rare problem. If you know trouble is coming you can have a plan in place to meet it. It’s a good idea to widen your focus so that you’re never caught unprepared.

 


Modern business practices create a complete picture of customers on all stages of their journey. You can custom-tailor your services to suit your customers like never before. Using data mining to improve the customer experience in your call center lets you make everything as easy and stress-free as possible for them. You can anticipate customer needs because you can analyze the data from their previous interactions with you, as well as looking at the data from similar demographics.

 

Excellent customer service is what makes a brand stand out in the modern business landscape, and data analysis is part of what makes that possible.

 

 

Topics: quality management,, call center best practices

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