Big Data

5 Tips for Root Cause Analysis in the Contact Center

The best way to solve a problem is to dig deep and find out where it started in the first place. Often, what you see of a problem is a symptom, not the cause. Here are five steps you can take to improve your contact center’s root cause analysis.

  1. Consider acoustic issues.

Root-cause analysis should take acoustic factors into account. For example, if the call has long periods of silence, this could point to a problem with the system. If the contact center agent can’t access data quickly enough or if there are problems with IVR, a slow system may be the problem.

  1. Flag conversations that are abnormally long.

Speech analytics will let you sort through calls based on parameters like duration and repeated calls. You can also find calls where specific keywords are mentioned, like those that are normally associated with a complaint. This will let you know which calls need the most attention.

  1. Monitor data in real time.

Accessing real time data can help you spot and stop issues early. If a new sales or marketing strategy launches and then phone calls start coming in within an hour or two, you’ll know that there’s a problem with the launch that must be fixed. Real time data lets you identify trends as they emerge, giving you the opportunity to stop a problem in its tracks.

  1. Sort problems into categories.

As you start to uncover the main problems customers are having, you can segment them into categories, such as product defects, customer education and marketing communication. Then, you can meet with specific teams to come up with targeted strategies to solve the problems.

  1. Understand the context of the situation.

Relying on word count frequency isn’t enough – the terms and phrases that are being used have to be understood contextually, too. Knowing the context of a problem instead of just the hard data will allow you to pinpoint the situation that caused or contributed to it.

Knowing the average number of complaints your contact center receives on a weekly basis is just a start. You have to figure out the root cause of the complaints in order to effectively tackle them and prevent them in the future. Root cause analysis is a way to solve prominent issues instead of merely putting a Band Aid on them.

4 Trends that Improve the Customer Experience

When customer service teams want to differentiate themselves from the rest, they focus on improving and optimizing the customer experience. Companies are more than willing to go above and beyond for the sake of meeting and exceeding customer expectations. Here are four trends that will help distinguish your contact center.

Relying on Artificial Intelligence

Artificial intelligence (AI) is everywhere, from video games to the automobile industry. Customer service has been impacted by the increase in AI, too. This technology can be used to chat with customers about easy-to-solve issues, which frees up live agents for more difficult and complex matters. Automation with AI can reduce customer wait time, interact with customers and collect important data for the contact center to later analyze.

Implementing an Omnichannel Strategy

One major gripe that customers have is repeating themselves to various customer support agents in order to get an answer or have a problem solved. Channel integration isn’t the same as omnichannel service. Today’s companies can’t just respond to a customer, they have to know as much as possible about the customer and their problem beforehand in order to provide customized, relevant support. Customer service requires empathy and a human touch in order to connect meaningfully to the customer.

Analyzing Big Data

While much of the customer experience is about interaction and communication, big data still has a pertinent place in understanding customer behavior. Big data can actually help the contact center connect on a more personal level with customers. There’s so much information that can be tracked now, from customer behavior at every point of the journey to customer preferences regarding any number of attributes. Data helps customer support do things like figure out what a customer is going to want before they even ask for it and determine the best way to reach a customer on the channel of their choice.

Providing Real-Time Communication

Using things like AI, which can automate several processes, and ominchannel strategies, which can cut down on the length of time it takes to solve a problem, gives customer support agents the extra time to handle some queries personally. Real-time communication, specifically via mobile and social media, is in demand, especially by younger generations who are used to communicating in these ways. Being able to provide immediate support improves the customer experience and builds trust in customers.