The way in which users communicate with companies has quickly evolved, moving from traditional channels like email or the telephone to real-time conversational message platforms.
This phenomenon is linked to the fact that consumers nowadays spend more time on message applications than on the social network. Therefore not only has Artificial Intelligence revolutionised our personal life, but it has also changed our work environment and the way in which we communicate.
As we had already explained when talking about the use of the chatbot for B2B e-commerce, chatbots or conversational interfaces are softwares featuring Artificial Intelligence, which interact with people by means of desktop or mobile message applications. Having started as a phenomenon related to the consumer world, chatbots are increasingly integrating into the business context.
There are virtual assistants in mobile banking apps which help perform banking activities, from monitoring accounts and transactions to paying bills, from doing transfers to controlling expenses. There are chatbots ready to train customers on certain products and services of their assurance company. There are travelling assistants helping users to book flights and tickets, warning them about potential delays or cancellations, “shopping assistants” which support customers when purchasing items, guaranteeing immediate response 24 hours a day, 7 days a week, and simultaneously managing several conversations. In a digital context like the one we live on nowadays, surpassing customers’ expectancies has become a must for companies.
But how can IT assistance to stores in the Retail world benefit from Artificial Intelligence? Can a chatbot on its own guarantee efficient and quality service to users?
The greatest developments in terms of efficiency come from technologies able to take advantage from users’ historical data in order to provide more intelligent and automated services. This is why current service management solutions use the power of automatic learning, utilizing these data to offer a more intelligent Service Desk experience. Thanks to machine automatic learning functionalities (machine learning), it is possible to automatically suggest responses to given issues, improving service to customers. As we have already seen when analysing pros and cons of conversational interfaces, AI cannot yet manage “any” conversation, but only answer within certain parameters or key words. The human factor is therefore essential for support services to customers.
The solution is uniting a multilingual Service Desk’s expertise and empathy to a multichannel application which allows shop-assistants to:
We are facing a real revolution in the world of assistance to points of sale, in which “human intelligence” and artificial intelligence are united to achieve the same objective: improve service to operators, so they can concentrate on sales.