Engaging the Digital Customer

digital customer

Discover what it means to avoid the “False Choice” Between Linguistic Models and Machine Learning when building a conversational solution.

Some of UK’s major brands came together last month at the Engage Summit to discuss Engaging with The Digital Customer. While pain points varied dramatically, at the heart of the debates on customer engagement there were several problem areas that linked these diverse businesses together.

All agreed that contact with customers is becoming increasing remote, and harder to engage over traditional channels. While people are frequent and keen consumers of content provided by the brands, it is no guarantee of loyalty. Customers will use the business that provides the best experience for their needs.

But those needs are diverse and use up vital company resources such as call centre staff. A clear need is emerging to streamline processes for low value transactions in order to free-up resources to focus on higher value customers. However, most solutions implemented thus far are piecemeal and only focus on the short-term goal.

Ease of use in enabling customer engagement is a top priority, but customer frustration, particularly with repeating information and rigid adherence to call centre scripts, is rife. This escalates especially when customers feel they have provided the information in context, but it has not been noticed, or if the customer is sold to when all they want is some information.

Despite wanting to give a better experience to their customers, the delegates agreed that most companies engage badly with customers, citing a heavy reliance on legacy systems as one of the key reasons.

We’ve discussed in previous posts how customer engagement rises with natural language interaction. NLI overcomes many of the difficulties brands face in building a closer relationship with digital customers and one of the key differentiators from other natural language technology is its conversational ability. The future of AI in customer engagement needs to be much more conversational if enterprises are to meet consumer demands for a sophisticated, intelligent experience. Humanlike understanding including context and sentiment must be combined with back-end data to enable deeper personalisation to pave the way for organisations to reconnect with their digital customers.

While digital employees and other interfaces have come a long way in short time, it’s only with technology such as NLI that organisations can develop AI based applications that will delight customers and deliver a tangible return to the business.

For forward thinking enterprises, the time to take action is now. Develop your strategy, and think big, but work forward in practical steps with clear goals. But remember, whatever the application, it’s the conversational ability that will make the difference to your customer, your brand, and ultimately your sales.

Maximizing the Value of Conversational AI Alongside GDPR Compliance White Paper

While data regulation may be tightening, it is still possible for enterprises using Teneo to derive significant value and benefits from conversational AI, even when complying with the most stringent of data protection legislation.

View this White Paper

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