Here’s how AI can catalyse monetisation of modern-day contact centre

Organisations across the Middle East were left reeling, to varying degrees, by the restrictions that Covid-19 placed upon businesses and their employees. Even sectors that managed to do well had to overcome some of the same challenges as those that did not. Customer service functions, for example, continued for technology companies that benefited from cloud migration and the increased adoption of remote-working tools. But the same function suffered for the airlines, travel agents and hotel groups that had fewer options in adapting to the crisis.

The contact centre is changing. The word “explosive” could be aptly used to describe the growth in customer engagement activity in the past 18 months, even as these facilities wrestled with social distancing and how to provide secure remote access to systems for the purposes of business continuity. Enterprises across the region needed to find ways of providing voice, video, and any other channel the digital-native customer desired. This was the only way they could meet the customer wherever they were during the pandemic.

Across the region, boardroom discussions turned to the enhancement of the digital journey, and how it begins with the basics – with customer engagement and the contact centre. This is a time to get creative and shed traditional mindsets in favour of practices that fit the future. The call centre is traditionally a grievance-resolution hub, which is perceived as a cost centre for most companies. But it does not need to remain so. This is the age of “commodity-data”, where every piece of information gathered should be thought of as monetisable. Every call centre is a goldmine of human eccentricities and preferences. So, what if organisations flip the paradigm and begin to think of the call centre as a profit centre?

Enter AI

But how do we do this? Businesses could start by taking random samples and building models from them, but that squanders the potential of the sheer volume of calls we are seeing. Manual analysis would seem to be impractical, therefore inevitably, the topic of AI emerges. Machine-driven analysis of interactions can offer insights that are both predictive and prescriptive and lead directly to improved sales velocity.

Customer satisfaction and the tendency for consumers to become brand ambassadors are now familiar metrics among business stakeholders. So-called CSAT rates simply measure a percentage of customers who leave an engagement with a positive impression, and the net-promoter score (NPS) is the result of asking customers how likely they would be to recommend the brand to others.

Companies can certainly tell their story through a variety of media, such as websites and social pages, but it is the contact centre where the realities of a brand are exposed. Perception of the brand emanates from customer experience; and customer loyalty emanates from brand perception. And because, as every sales executive knows, it costs so much more to acquire a new customer than to retain an existing one, loyalty is precious. Loyal customers will also likely lead to sustained revenue over a longer term. AI-powered analysis of contact- centre interactions tracks these metrics in real time, and empowers agents to be more effective, whether they are tending to a grievance, selling, upselling, or cross-selling. AI can prescribe methods to increase customer loyalty (or achieve a superior NPS), and hence drive revenue growth.

Personal touch

Personalisation is also important. In trying to build the ideal customer experience, regional businesses, and those around the world, should concentrate on a 360-degree view of the customer and their history with the brand. Customers, especially digital natives, now expect a brand to know them at least as well as they know the brand; and they will prioritise this concept even above that of product quality and cost. AI analysis allows these knowledge models to be built for responding to, and anticipating, customer needs. Negative experiences can be turned around and churns avoided. Once that is achieved, upselling and cross-selling opportunities follow. For example, an insurance customer calling to complain about claims being rejected is a candidate for coverage upgrade. Equally, AI’s ability to pick up on speech patterns (emotions, tone, sentiment) and keywords can be leveraged for product reinvention.

Contact centre KPIs are readily attainable through AI and robotic process automation (RPA). Real-time conversation analysis means agents become more effective more quickly, leading to the type of quality that keeps customers engaged and loyal. This, in turn, leads to lower operating costs and higher revenues. And therefore, to higher profits.

The contact centre is the fulcrum of modern customer service and brand perception. AI isn’t just about chatbots, but about analysing the data businesses have, including voice. AI can go beyond real-time interactions, to social media and emails, to further gauge public sentiment. If this is done effectively, companies can predict consumer preferences and reinvent products and services.

It is a fact the modern organisation must face – today’s consumer is neither patient, nor forgiving. There are simply too many choices in every market, and each is accessible with a swipe and a click. Businesses must get it right the first time, every time. AI is fast becoming the technology that makes this possible.

Ravi Saraogi is the co-founder and president – APAC at Uniphore

Read: Majority of UAE consumers open to using AI to enhance video conversations