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April 14th, 2020

How to Ramp Up Automation in a Call Center Upgrade

This is the third in a series of blogs about improving your call center.

Upgrading your call center in a crisis has a middle phase that’s critical to achieving your long-range goal of implementing an intelligent virtual assistant (IVA) system.

Call centers IVA use advanced learning algorithms that train their attention on the speech patterns of callers. Over time, they analyze enough data to learn how to answer more caller questions correctly and make fewer mistakes.

Learning automation can be a major boon to call center efficiency — if you follow the ideal path to IVA implementation. It’s a delicate choice because it’s so tempting to throw everything at the challenge. That runs the risk of trying too many new things and faring poorly at all of them.

In a previous blog on automating healthcare call centers, we recommended getting off to an easy start that provides rapid relief to your call agents or patient-support staff. Now we move to the middle phase that forms the bridge to your ultimate goal — a fully functional IVA that eases the burden on call center reps while also pleasing your patients.

The Middle Phase: Adding Channels and Verification  

In the first phase of this model, we suggested choosing a single channel like a webchat and targeting a few easy questions whose answers are easy to automate.

That simple bot generates training data about your patients’ most pressing concerns, creating a baseline for the middle phase — automating new channels and verifying identities. There’s plenty to think about here. You might consider boosting the capabilities of the text-messaging channel and queries arriving via email and social media posts. Much of these channel-choice decisions depend on data insights from your initial automation phase.

As you might expect, the middle phase can tackle more difficult questions. For example, one of the most important goals here is identifying exactly who is contacting your patient-support reps.

Consider the patient asking about paying a bill — a financial transaction that’s an excellent candidate for automation. Your challenge is building a transaction bot that confirms their identity correctly every time while protecting their sensitive medical and financial data in accordance with regulatory requirements.

Verification is a big job. Getting it right early will pay dividends throughout your call center upgrade.

The middle phase also is the right time to start training your call center staff on the subtleties of automation. They must understand that bots are there to augment their capabilities, not put them out of a job.

The stickiest IVA challenge is yet to come: Using learning algorithms for sentient analysis and to examine the intent of complex questions in a voice call and supply the right answer without human intervention. You also want to use caller behavior data to predict and project their future needs.

That’s your IVA system’s ultimate goal, which we’ll cover in the final phase of this blog series.

A Partner for Every Stop on Your IVA Journey

It takes a wealth of knowledge, vision and experience to automate a call center with IVAs that combine the latest innovations in data science, analytics and machine learning. Our experts include data scientists, user experience designers, system architects and project managers schooled in the Agile and DevOps principles that ensure speedy solutions to intricate technology challenges.

As a system integrator with clients in health care, finance, government, retail and automotive sectors, DMI has the skills and the track record to help clients succeed with IVAs and many more next-generation digital technologies.

–Niraj Patel, director, artificial intelligence

Tags: call center data healthcare hospital IVA virtual assistant

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