Machine Learning, the engine of intelligent Customer Service

Today Machine Learning must be considered as a fundamental component of modern Customer Service and therefore based on Artificial Intelligence mechanisms.

Customer Service has, in fact, entered the new era of digitalization: it has evolved, taking on innovative forms and approaches, adopting new models to bring real added value to companies and their customers. The Customer Service, following the new behavior trends and the emerging needs of "digital" users, today adopts Artificial Intelligence technologies, automatisms and natural language processes (Machine Learning), through the spread of virtual agents and chatbots, with the aim of improving its assistance performance.

The recent and difficult period, linked to the pandemic, has highlighted even more how the Contact Centers and the Customer Service are fundamental for the relationship with the customer and for their experience. 80% of managers think so and this is confirmed by customers for whom Customer Service is the second most important purchase criterion (after product reliability).

What is Machine Learning?

Machine Learning is an application of Artificial Intelligence (AI) that provides to a system the ability to learn and improve from experience.

The learning process begins with the observation of the data and with the attempt to identify within them the sequences on which to base future choices.
Textual data, often at the center of the customer-brand relationship and increasingly frequently managed by chatbot, are processed by artificial intelligence algorithms that produce an approach based on semantic analysis.

Machine Learning, the new engine of Customer Service

Customer Service is increasingly hired by online customers, for repetitive requests and which give rise to similar flows of problem management (for example: generation of new password, reordering of a spare part, or passage of the case to a more specialized level).

This first level assistance can be delegated, in its most basic meanings, to virtual assistants based on Artificial Intelligence algorithms who, by means of automated and intelligent chats, can manage requests and possibly scale to the next level for more assistance.
These are just a few examples of how Machine Learning can be applied to the daily assistance processes of a company. Within a business digitization process, it is therefore recommended to evaluate the integration of machine learning logic as well, in order to make your working environment increasingly smart and resilient.

Among the consequent advantages that these systems bring to the company, there is also the possibility of relieving the assistance teams from unproductive routine activities and specializing them in other tasks, commercial or technical, with greater value.

Machine Learning applied to Pat's solutions

Artificial Intelligence has always been the application core of Pat's Virtual Assistance platforms.
A vision that our company has pursued since the birth of these new technologies, identifying new models of interaction between brands and customers in automated and AI-driven processes.

The CX Studio multichannel framework and the Engagent chatbot are based precisely on Machine Learning, or rather on the semantic recognition process, which allows you to understand natural language and recognize the best available response. In addition, thanks to the application of artificial intelligence algorithms, Pat's systems are able to automatically classify content, allowing to improve the process of managing user or customer reports.

This is why Pat's solutions can bring added value to the company business, effectively guiding the relationship with the customer, from the multi-channel contact and engagement phase, up to after-sales assistance.