Advanced chatbots: much more than a conversational interface

In the last article we saw how RPA (Robotic Process Automation) technologies help automate business processes, making them faster and more efficient. We saw how introducing a chatbot into the after-sales service pipeline can help customers resolve problems without requiring a human operator. In most situations, with well-trained wizards, calls can be handled and resolved before a ticket is opened.

The chatbot saves the human employee from having to perform many repetitive tasks, directing his resource towards more strategic business activities. Companies gain several advantages because they can use robotic systems that are active 24/7 and can perform most tasks. Exclusive human competences remain reserved for general supervision and resolution of critical situations.

Today we will see how conversational interfaces can be made increasingly intelligent, taking a chatbot far beyond its original function.

The age of cognitive computing

One technology that increasingly accompanies RPA is undoubtedly hyper automation, which uses machine learning techniques to progressively learn from process data to make them more intelligent. If our chatbot were to dialogue with a properly trained ML system, it could receive suggestions to improve the quality of its questions. The strength of hyper automation is that it becomes increasingly efficient over time, thanks to the continuous knowledge that the machine learning system acquires from usage data.

When the CX provider is defining the customer service hotspot of the customer journey, they should always be aware of the contribution they can make from cognitive computing. Cognitive computing is very similar to artificial intelligence in general, with which it shares the same basic techniques (machine learning, natural language processing, speech recognition, etc.). Both automate procedures by learning from data, processing it to provide recommendations, with the difference that cognitive computing seeks the solution in the reasoning that humans would do if they were in the same circumstance. This characteristic generates an affinity that goes beyond the understanding of language and voice, bringing the relationship to the level of feelings.

A system equipped with these technologies goes beyond the usual definition of a chatbot, equipping itself with the initiative of virtual assistants and smart advisers. In addition to obtaining information, an intelligent conversational interface becomes capable of suggesting solutions based on information obtained in real time. The system can also translate decisions into actions that not only solve the original problem, but also improve the customer's experience with the brand across the board.

When a problem is solved, an intelligent conversational interface can propose new solutions to the customer, with a very high probability that they will meet their expectations, making them more profitable and loyal to the brand. This is possible thanks to a high level of knowledge of the customer, which can be obtained through the data of their relationships with the brand's channels.

CRM is the lifeblood of intelligent conversations

Intelligent conversational interfaces build the relationship based on the data the customer generates through their digital experience with the brand. The key tool for collecting this information and making it accessible to machine learning systems is CRM (Customer Relationship Management). Modern CRMs can intercept every relational aspect that the customer establishes in his interactions with the website, e-commerce, social networks, customer care, going into detail about his orders and all the aspects that allow him to be profiled in an extremely precise manner.

User profiling allows the machine learning system to have a very detailed data history and to analyze it to generate very accurate predictions. This information allows the conversational interfaces to interact with the customer in the same way as someone who knows them personally, in the same spirit as the bartender who already knows what they want for breakfast every morning.

This level of confidence offers significant benefits throughout the customer journey. A trustworthy relationship is built by consistently working through the details to build trust and engagement step by step. Start a conversation by calling the customer by name, ask them how they found it after their last purchase, automatically create a personalized microcopy when loading a web page on the website. Today all this is possible, thanks to technologies that make the work of the CX provider increasingly oriented towards automation and performance.?