Quite certainly many executives at the heart of sales operations within software providers around the world are facing questions regarding this year´s plans for developing solutions that involve artificial intelligence, process automation and chatbots. These inquiries will not stop as months pass. In fact, they will only become more complex, more frequent and would require a much more urgent answer.
The debate over whether artificial intelligence and robots will replace humans is already more than solved, since it is evident that at least it will not happen in the near future (and perhaps not even in a distant one). Nor should we get carried away by all the expectations generated by the market about the capabilities that these technologies can offer. The important thing now is to start analyzing the best way to coexist with each other: humans, robots and automation technologies
Self-learning and data mining
The main attribute that artificial intelligence imprints in customer experience is “teaching” systems and applications within companies to make decisions independently based on the study and analysis of information. This allows users to self-manage simple requirements without the need of escalation to an agent, while these interactions feed the knowledge base of artificial intelligence that will be used later in self-service management and even to anticipate future needs. In the event that live agent intervention is needed, the latter would also have first-hand information from the knowledge base to maintain the context of the interaction, provide a solution to the requested need and, above all, to allow transition between bot and agent to be completely transparent to users.
Since customers nowadays interact with companies through a variety of communication channels, they generate massive data records relevant to their customer experience from chat conversations, comments on web pages, survey results and posts in social networks. This information is constantly studied in detail by the areas of data mining in order to extract information that facilitates and expedites future decision making within the contact center. However, the enormous amount of information often does not allow us to measure the quality of the client’s trip through professionals or experts dedicated to their analysis in a manual way. This is where the analysis of text data powered by artificial intelligence and natural language processing technologies (Natural Language Processing) play a decisive role, allowing to make a thorough sweep and study of information quickly and accurately and use algorithms to identify patterns of behaviors, relate information and anticipate business opportunities.
Agent assistance in real time
In order for artificial intelligence to have a positive impact on the client’s experience, the relevant information extracted from the interactions that take place in the contact center must be analyzed on the fly. In the same way that a coach directs a football team during a match, analyzing previously programmed tactics, studying the opponent and making changes according to the outcome of the match, bots can fulfill functions of “personal assistants” for the agents and support them during the conversation. For each client’s interaction, bots can review its knowledge base and offer the agent suggestions for responses that can be sent to the user through a single click, making communication more effective and reducing service times.
On the other hand, some solutions use artificial intelligence with much more advanced algorithms, which even allow to identify the moods of the agents and how tired they are, alerting them to possible failures in their management. This prevents service levels from falling during peak calls or even in the minutes immediately before the service agent ends his/her turn, at which point he/she will most likely be exhausted.
Authentication mechanisms
An optimal strategy focused on maximizing the value of interactions between companies and their customers by combining artificial intelligence with human touch must consider offering conversations with high levels of security. Of course any self-service interaction requires users to identify themselves, especially if it involves transactions subject to loss or theft of information, such as purchase confirmations or bank transactions. These verifications can be done through SMS, email or through voice biometrics, which will increase the speed of service by preventing the self-service session from failing because the user does not remember their password or PIN.
Authentication mechanisms add a much friendlier method to users and raise their level of confidence when interacting with a company. Here it is essential that the knowledge base of artificial intelligence is constantly updated, in order that both bot and service agent are aware of which authentication method is preferred by the client and there is no need to ask for it again. By offering different authentication methods through several points of contact with the customer (mobile devices, conversations with service agents or self-service sessions), companies can alleviate the concern of their customers to provide their personal data, which generates greater loyalty.
Gartner predicts that by 2020, customers will manage 85% of their relationships with companies without human intervention. However, there are many people who prefer and demand to speak with a service agent, either for lack of confidence or simply because they have always done so. Moreover, no matter how strong the artificial intelligence knowledge base is, it can never achieve what a human knows how to do best when it comes to offering customer service: empathy. After all, the capabilities of machines and those of humans are totally different. Machines are excellent at handling and analyzing large amounts of data at very high speed, while the latter are crucial in understanding the emotions and feelings that are linked to interactions and their context.
Here, the most important thing of all is to have a very clear objective: it is not a matter of replacing human intervention, but of facilitating it and, above all, achieving a totally transparent transition between service assisted by artificial intelligence and that which is managed by a human being, only this way the customer journey will be uninterrupted and with a greater chance of being satisfactory.
