Generative AI for Customer Experience: Why You Should Prioritize Processes Over Technology

The contact center market of the near future will undergo, perhaps more than any other, the disruptive impact of new technologies, and in particular, of generative artificial intelligence.

The great challenge that every company will have to face is, even now, not to be caught unprepared in the face of this revolution that will change the relationship with their customers and push the customer experience to a new level.

Market analysts have long pointed out that investing in the relationship with customers generates high ROI and multiple growth rates compared to the market average, and this is a trend destined to grow over time.

The end customer increasingly relies on brands that inspire confidence and on which they know they can count, especially when they need it: in choosing a product or service, customer experience matters more and more, even at the expense of price or quality.

This is why no company can overlook these themes and the challenges of the near future related to new customer care technologies.

How to Choose the Right Generative AI Technology

But what is the right technology for implementing generative AI processes related to customer (or employee) experience?

Today, the only plausible answer to this question is: we don’t know.

For this reason, the second biggest mistake a company can make, after not acting, is to move towards the definitive choice of a technology and a vendor and to bind itself to these over a medium/long term.

All major tech players bounce news every day about miraculous LLM (Large Language Model) services promising revolutionary use cases and unprecedented user experiences, and those who have not yet exposed themselves, like Apple, might soon change all the rules. Just think, for example, about Elon Musk's acquisition of Twitter (now X) for the astonishing sum of 44B$: was the CEO of Tesla really interested in the social network, or maybe more in the user data to train his LLM engine?

So what to do? Our vision today is to focus more on processes and less on technology, relying on companies that have a tradition in this area and a history of innovation. At Eudata, we strive to be technology partners who place customers and business at the center, using technology as a driver to achieve the best possible customer experience. For this reason, Convy.AI, our flagship product, designed as a process orchestrator, enables the possibility of integrating present and future LLM engines and using them individually, in combination, or even alongside other tools such as Natural Language Processing. In this way, a company does not run the risk of being caught off guard by the speed of technological innovation and falling behind its competitors, and can instead focus on data and the value to provide to its customers even through a business-oriented development interface to configure prompts and capture the sentiment of interactions.

The Impacts of Generative AI on Customer Experience

But what are the concrete impacts of Generative AI on Customer Experience?

Answering this question is not easy because the technology is brand new and the application prospects seem almost infinite at the moment. It would be a bit like asking Alfred Nobel what the dynamite he invented was for. He would have certainly replied: for construction and mining. But as we know, over time it was also used for all other less noble purposes.

To date, we could identify at least two significant impacts of generative AI in the CX world:

• The level of personalization: Generative AI allows the creation of tailored content, adapting it to the individual preferences of customers, significantly improving engagement and consequently spending capacity;

• The reduction of operating costs: According to some analysts, implementing generative AI can lead to an operational cost reduction of up to 25%, derived from automated and optimized processes. Our experience in the field tells us that this reduction can be even greater considering the vast range of all possible applications, such as voicebots, for example, to manage the telephone channel in self-service or virtual assistants to respond to customer emails or suggest the product or service most suitable for purchase.

But like dynamite, which was very fortunate but soon replaced by more efficient and safe solutions, the future of Generative AI is yet to be written and many of the applications that will be with us every day in the future are probably not yet clear to anyone.