Smart Action for Call Centers: How to Leverage AI to Enhance Customer Service?

As AI makes high-volume recruiting easier than ever, contact centers are running out of excuses to hang on to legacy systems and skirt tech tools that supercharge customer relations.

Call center recruitment is a unique undertaking. High-performing, friendly customer service agents with a real acumen for relationship-building aren’t always easy to find. On top of that, integrating new customer service reps can be quite challenging, especially if you frequently introduce new processes. It can take more than six months for call center staff to become proficient in all aspects of the business, and that’s including the 90-day onboarding period. Then there’s the high turnover rate, averaging roughly 30% across the industry. When you couple that with an average cost per hire hovering at more than $4,000, it comes as no surprise that cementing a good recruitment strategy is so vital to the success of your business.

Enter AI. It sounds almost regurgitated by now to say that AI is transforming customer service delivered by call centers. From machine learning to predictive analytics, call centers are on the brink of major changes occurring in the ways they source and staff the right people for advertised positions. According to Gartner, AI will not only be pervasive in software products and services by 2020, it will also become a positive net job motivator – creating 2.3 million jobs while wiping out only 1.8 million.

So, if you haven’t deployed AI technology in your call center already, here are a few incentives that will cause you to rethink the status quo:

Advanced Candidate Assessment

The way recruitment is carried out at present makes for some pretty miserable recruiters. It also doesn’t harness the pool of high-performing applicants. Employers can receive between 75 and 250 job applications per job post, so combing for good prospects by hand isn’t unlike looking for a needle in a haystack. At call centers, this problem is magnified even further. Assembly-line hiring practices, which are needed to offset high turnover, drive recruiters to implement biased resume-screening criteria and cut back on meaningful rapport with candidates. In turn, this sacrifices the opportunity to adequately gauge the candidates’ ability to perform in the advertised role.

But AI-powered automation tools can handle all the footwork – from sourcing candidates to scheduling interviews, screening and running background checks – so you can spend more time assessing candidates. All the sensation surrounding AI about armies of robots displacing humans may be all the rage now, but can an algorithm detect a bad candidate hiding behind a flawless resume? Exactly.

Better Evaluation of Agents’ Performance

Predictive analytics can help you evaluate your agents’ performance in ways considered impossible only a few years ago. Specifically, AI can expose emotions that lie hidden below the surface by assessing criteria that are elusive to humans: while a recording of the call between the agent and the customer reveals what the agent is saying, the technology looks beyond words to detect what’s really brewing underneath for a more comprehensive picture of the agent’s performance. Are they acting humorless, repetitive and aloof? Or are they optimistic, assertive and ready to help?

With the advent of Internet, customer churn is only a click away while technological disruption is reshaping customer experience as we know it. Such changes are putting pressure on contact centers to act less as mere service providers and more like true brand partners who build customer relationships as a valuable point of differentiation. In the future, we’re going to see AI-powered tools gain more and more credibility as contact centers aim to deliver the best customer service possible.

Precise Candidate Targeting

Predictive analytics are revolutionizing applicant tracking systems in several ways. Whereas employers routinely rely on keywords, verbal sequences and other research points to track and source candidates from the pile of online applications, AI tools can exploit those patterns a step beyond. For example, they can predict which candidates will deliver as suggested by their application. And they enable recruiters to conduct surgically customized, increasingly granular searches by a whole host of criteria such as education, age, household income, job changes, location and job title. The added advantage of AI predictive analytic tools is that they can detect patterns in a matter of hours instead of days than other, time-honored methods.

Accurate candidate targeting with predictive analytics can go a long way in making sure you spend your valuable time where it matters most. Then you will also hire the best customer service reps who will act as true brand ambassadors, build relationships and effectively resolve customer complaints.

Conclusion

The pattern of AI adoption and full absorption might be surprisingly fast – mirroring the high rate of what has been observed with other technologies, according to a McKinsey Global Institute study.

Stop operating in the dark. Contact us to find out what AI strategy is right for your contact center.

Interested in Subscribing to our Blog?

Please enter your information below and we'll be sure to notify you of new posts.