How Artificial Intelligence can improve customer management
AI & Machine learning, Omnichannel Approach

How Artificial Intelligence can improve customer management

How can Artificial Intelligence make a difference in customer management and why is it so important to leverage conversational AI in customer interaction processes? How much has Covid-19 had an impact on the development of omnichannel technologies? What awaits us in the near future?
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What is conversational artificial intelligence?

The very name of conversational AI explains what this technology consists of: a tool that recognizes human language , and is able to answer questions and requests in a way that best imitates conversation between people .
To obtain this type of interaction, technologies that revolve around the sphere of Machine Learning are exploited, such as automatic speech recognition (ASR), natural language understanding (NLU), natural language processing (NPL), and AI for noise cancellation.

By studying and processing human language and dialogue processes, conversational Artificial Intelligence is able to imitate the communicative relationship between human beings in a completely natural way, giving the user the perception of a real conversation with another person.

The learning of AI also allows you to create fluctuations in the discursive form, which take up phrases and emotional expressions typical of the organic way of expression of every human being.
A mutual recognition is therefore established between “the machine” and the user, putting the latter at ease.

What's the difference between chatbot and conversational AI?

In one way or another, each of us has had the opportunity to experience interaction with chatbots or similar tools. Websites, customer services, e-commerce are the main protagonists of this method with which customer care is managed, in addition of course to the more traditional channels. But how does Conversational Artificial Intelligence differ from the more popular chatbot , and why should companies adopt this tool?


When we talk about chatbots, we are referring to a program whose purpose is to communicate with users .
But how often is this communication satisfactory for the user, for the person on the other side of a screen or a telephone handset?

Using chatbots does not necessarily imply the use of conversational AI , which is a tool, not the program itself. With conversational AI we allow a computer to imitate and create real conversations with people, while a chatbot is often confined within predefined limits , which will greatly limit user interaction and satisfaction.

The difference between chatbots (or virtual assistants) and a conversational experience therefore lies in the integration of back-end systems to provide information to customers, in a way that mimics as much as possible that of a natural dialogue between two human beings.

AI Conversational

If we apply Conversational Artificial Intelligence to chatbots, taking advantage of NPL, machine learning and all the tools provided by AI to better understand a user’s request, his questions and needs, we will obtain a natural communication flow, which he will imitate an organic conversation more effectively, and it will pay off more immediate and authentic interaction between customer and chatbot.

The range of possibilities of conversational AI is infinite : banking operations, reservations (plane tickets, holidays, a dinner), questions about products to buy are just some of the most classic requests.
In a world increasingly focused on speed and efficiency , being able to perform these operations independently, through a virtual assistant, without long waits, directly from a mobile phone or a PC, but at the same time obtaining an immersive and familiar experience , without the “coldness” typical of an automatic responder, is it not a guarantee of quality customer management?

What's the difference between chatbot and conversational AI?

The benefits that are obtained by combining machine learning and artificial intelligence with omnichannel solutions

Covid-19 has in a very short time profoundly influenced the markets and user behavior , bringing an evident impact on the ways of purchasing and interaction of the company.
The acceleration of digitization in some sectors, driven by the need to make up for services that are no longer available “in person”, the difficulty of finding goods if not via the internet and in general a world of work increasingly projected towards the future, also force companies to new reflections on the use of technology.

The estimated value of the conversational AI market in 2020 varies between approximately $ 4.7 billion and $ 5.1 billion. The market is expected to grow from approximately $ 18.02 billion in 2027 to $ 46.29 billion by 2028, with a compound annual growth rate (CAGR) of 18.9% to 30.75%.

In the last two years, therefore, we have witnessed an exponential growth of omnichannel services and the adoption of technologies related to machine learning and Artificial Intelligence , with the aim of improving and personalizing customer care more and more.

But what exactly are the most positive aspects of adopting conversational AI combined with omni-channel solutions?


With conversational AI it is easier to get the right answer to a request , or to give exact information, to personalize an order. Machine learning improves AI learning from time to time and provides ever more exact solutions .

Cost reduction

The functions of an AI allow you to manage different tasks, without any kind of interruption, 24 hours a day, 7 days a week, 365 days a year .
Combining traditional customer care with a service with conversational AI leads to a reduction in training and supervision costs , very useful for small and medium-sized companies, but also for those people intensive with complex management or that require special shifts.

Investing in this type of technology allows significant savings, without sacrificing efficiency.

Remote customer management

The trend that had emerged in recent years has seen, with the pandemic, an enormous growth in what concerns the experience of users remotely .
Apps, e-commerce, home banking and customer services in general today increasingly require the ability to independently manage processes , with immediate, omni-channel and responsive help.
What AI aims at is precisely to provide that help, in the simplest and most effective way possible.

Improve sales

Through omnichannel AI it is possible to develop brand recognition, customer loyalty and manage payments, cross and up-selling with tools that exploit consumer preferences, interaction methods and their habits to create the most suitable option . engaging and convincing to propose .

Quality customer service

Machine learning and conversational AI are the best tools to track and memorize customer satisfaction , providing specific analyzes on the perception of your customer service by users. With 24-hour assistance the satisfaction rate grows, because the consumer feels listened to and supported when he really needs it , without having to submit to the logic of hours or waiting times, while maintaining the quality of response given by human interaction. .

Xenialab and the practical use of Artificial Intelligence

Xenialab products, first of all XCALLY , allow you to make the most of Conversational AI to interact naturally with users, with an omni channel solution for voice , chat , email , sms , fax and other channels (social networks such as Facebook, messaging app like Whatsapp …) through standard API.

Thanks to AI , speed and efficiency of processes are combined with quality of interaction and performance monitoring .

Discover our solutions
Implement Conversational AI to improve contact management with XCALLY and Dialogflow
AI & Machine learning, Omnichannel Approach, Software AAS

Implement Conversational AI to improve contact management with XCALLY and Dialogflow

In this Case Study we see how Inicia Soluciones, XCALLY certified partner in Spain, designed a Voice Bot for one of her clients, using XCALLY IVR Designer and Google Dialogflow.
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The XCALLY Case Study - AnswerNet for Contact Centers