The future is calling

Call centers have leveraged advanced technology for decades. As nascent applications in artificial intelligence gained traction in the 2000s, call centers were more focused on using tech to reduce costs than they were on improving customer experience. It’s no surprise that the market for call-center AI technology is expected to increase from $800 million in 2019 to $2.8 billion by 2024.

First, the mass adoption of smartphones, social media, and consumer-friendly apps changed customers’ expectations forever. Second, the explosive growth of widely-available cloud services and machine-learning tools has put powerful new AI capabilities in the hands of call centers to improve customer service in all forms. Enterprise executives today cite customer experience as their Number 1 reason for investing in AI; cost reduction has now moved to second place.

The role of AI

AI-enabled conversational agents, for example, are expected to handle nearly 20% of all customer service requests by 2022. That alone relieves human agents of huge burdens and time. And when you do talk to a live agent these days, AI tools are bringing many of them up to speed even before they get on the line. They already know who you are, what you need, and, in most cases, how to get it.

AI now has a powerful role in digital marketing, as it is used widely to customize the digital journey to each person. It is quickly becoming apparent that AI also has a significant role in bridging the customer experience between the action of selling to them and responding to customer needs regarding a purchased product or service. The customers that contact the customer support center are the best source of new revenue.

Natural language understanding (NLU) software—using seven language models and two acoustic models—now translates more than 90% of spoken sentences that it “hears” from customers. AI-enabled conversational assistants aren’t just getting customers basic information they need; behind the scenes, they are also feeding human agents intelligent data and analysis to deliver better, faster outcomes, without customers ever being aware.

Using another type of AI application related to NLU, called sentiment analysis, virtual assistants can parse customers’ spoken or written comments to understand what they are trying to accomplish. Then they can recommend a handful of solutions—not to the customer, but rather to the agent, who can use her human skills (such as the ability to gauge and respond to customers’ emotions) to decide on the best option. The end result is reduced call times and a more personalized customer experience.

Similar types of AI applications can help sales teams make smarter decisions and help boost customer satisfaction. A growing number of companies are using machine learning tools to turn dozens of data types into customer risk scores. And when the scores rise to certain benchmarks, the software alerts sales teams and sends recommendations for personalized offers like rebates, discounts or other perks. The business payoff? Lower churn rates and higher customer satisfaction scores.

For all the hype around AI, surprisingly few companies have embraced it in call center operations. But adoption rates are expected to climb rapidly in the coming years, in part because the pandemic has forced many call centers to shift suddenly to a remote-work model, and many won’t be returning to the pre-pandemic status quo. Many contact centers have experienced an explosion in call volume. Contact center agents have really had to change the way that they had been working for the last 30 years, with everyone being forced to work remote, almost overnight.

TMP’s call center

Here at TMP, we provide extended hours, even overnight and during the weekend, to make sure that our clients get the support that they need, 24/7. We fill in tech gaps using customer relationship management tools specific to each client, utilizing knowledgebase software like Adobe RoboHelp. We help our clients progress from being a just cost-neutral center to a profit center by providing cost-effective solutions. We enhance the customer experience through self-service options such as IVR and chatbot.

Our customer service agents are trained extensively on the platform, policies & procedures, response delivery and product before handling calls for our clients. This improves our customer satisfaction scores and helps us exceed our KPIs every time. We focus on technology, analytics, process and people and our customer-centric approach guarantees success and happy clients.

Ultimately, of course, the only increase that matters is the level of customer satisfaction. And this is one area that TMP excels in, with an average customer satisfaction score of 93% for the first quarter this year. Here’s looking forward to more happy clients!