Artificial Intelligence in Contact Centers—How to Know Your Customers

Artificial Intelligence in Contact Centers—How to Know Your Customers

A customer could once walk into a local shop and be personally greeted by the sales assistant who very often had a one-to-one, direct—and therefore highly individualized—relationship with the person. Each customer had a unique need, attitude, budget and purchasing pattern. The sales assistant understood precise individual needs and tailored his approach accordingly—and in doing so, commanded satisfaction and loyalty.

The challenge for modern businesses that interact with hundreds or thousands of customers daily—either digitally or by voice—is how to replicate the authenticity of personalization. Artificial intelligence is key, but we must distinguish between quantitative, qualitative, historic and predictive. Much like an in-store experience, the objective is to understand sentiment to predict needs and deliver what the customer wants. Historical data, which is often attained using NPS surveys and purchasing history, are useful in providing collaborative measures, but they fall short.

The onus is on companies such as Avaya to develop artificial intelligence and analytics platforms that can understand, route and address an immediate customer need. We have achieved such predictive routing. By developing new platforms and working with innovative Partners, we have succeeded in merging historical and real-time customer-related data, derived from any channel of communication, to make an instantaneous real-time understanding of sentiment. How have we done this?

The most important factor is Avaya’s willingness to open its technology to vendors and application providers across the industry. This has helped Avaya and its Partners discover new ways of making API integration seamless and easy. A great example is our new partnership with Afiniti, whose behavioural pairing AI technology is now embedded natively in all Avaya platforms. This partnership follows our 2017 release of Avaya Oceana 3.4 and our recently launched A.I. Connect program. These platforms offer a whole range of measurements that feed into the AI engine, enabling the customer service agent to respond to changing sentiments in real time.

The second factor is Avaya’s progress in customer experience measurement. We have developed several exciting tools that deliver smarter, intelligent and real-time performance measurement indicators. Take for instance the Digital Experience Index (DEI), an index linked to the AI algorithm that allows customer feedback to be automatically routed into the learning algorithm and to then update individual experiences accordingly. Other examples include the CES (Customer Efforts Score) and real-time UGC (user-generated content). When a company can combine and customize these data sources to meet the needs of their customers, it can achieve predictive routing that delivers a truly personalized customer experience. As customers, we all want to be understood, recognised and appreciated by the companies we buy from. In return, we show appreciation and loyalty.

What it boils down to is sentiment—an emotional experience that is best served through direct interaction with another human being. Customers expect to hear empathy, understanding and solutions. Avaya’s self-service channels enable businesses to achieve this human experience through the combination of voice and highly sophisticated AI and data analytics. This is how to get to know your customer.

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