Revolutionizing call centers through AI

The pandemic has had a big effect on call centers and service desks due to an increased need to interact remotely. More sales and customer service issues are being handled over the phone than ever before, and that means that these centers will need to adapt to the new normal. This provides the perfect opportunity to upgrade your operations with the latest machine learning technologies.

Gauss Algorithmic is all about using data and modern machine learning technology to make businesses more efficient, more profitable, and better at satisfying their customers. But a lot of times, businesses don’t know what they don’t know. They’re unaware of exactly what data they have. If they are aware of their data, they may not know how much it’s worth or how to monetize it.

We have helped clients from many different industries, but lately we’ve seen a big uptick in demand from call center operators. As we’ve worked more closely with this industry, it became pretty clear why that is.

AI in call centers

To put it lightly, the pandemic has had an effect on the entire global economy. This means we’re seeing shifts in behavior on both the business and consumer side of things. One result of that is that there has been a growing demand for call center operations.

A group of people wearing headsets in a call center.

The reasoning is pretty clear: more and more interactions between companies and their customers are happening remotely. This means more call center marketing, more customer service calls, and hiring more people to perform these tasks. Any time there is a large shift in an industry, companies look for new technology or services to help with this transition.
And if you’re reading this now, then it probably applies to you as well!

So as we enter 2022, let’s look at how machine learning can help you get a competitive advantage in this quickly evolving market.

A hybrid approach is the new standard

Call centers have been using a combination of interactive voice response (IVR) and live calls for a long time now. However, as AI technology gets more sophisticated, more and more situations can be handled without the need for a human — and without seeing a drop in reported customer satisfaction.

So, the percentage of calls needing a representative will decrease, but the average complexity of those calls will increase due to the more simple tasks already being solved through automation. AI can help with these difficult calls.

A computer with two monitors and a keyboard in the dark.

Conversations can be analyzed in real time and the system can detect the topic of the conversation, the emotional state of the customer, and much more (really — we think you’d be surprised at how good this technology has gotten!). With that information, AI-powered predictive response helps your agents keep difficult conversations on the right track by providing your agents with a list of possible responses for them to choose from.

This also provides tools for management to analyze their performance after the fact. Did your representative lose their cool? Did they stick to the script? Did they solve the customer’s situation? This kind of detailed analysis can really help you build a more effective team which can significantly boost your sales KPIs and customer satisfaction.

Operators will need more training

Implementing this kind of sophisticated AI-powered system is obviously going to require you to also retool your training and management practices. Your agents will need to get used to working alongside the technology, and they will need to be prepared for their average complexity of call to increase.

Luckily this kind of advanced call analysis is also incredibly useful for creating effective training.

A group of people sitting around a table with laptops.

It’s possible to automatically create transcripts of all of your phone calls. That’s not super impressive these days, we know. But we can use those transcripts to build you a powerful machine learning model, which will be trained on both your successful and unsuccessful customer interactions. This allows you to run future calls into this model, and it will be able to tell you if the call was handled correctly, or if your agent may require some more training.

More than that, machine learning can also tell you the most important factors for a call being a success. You can use this information to train your team to be more effective and efficient. You’ll have a perfect blueprint to boost your results and to stay one step ahead of your competition.