AI/ML based Digital Empathy: the missing point of digital channels & chatbots.

Remembering the 60s, 70s, 80s, the pre-digital whatever banking operation, insurance claim or question and buying a flight ticket were done visiting bank branches, insurance company local agents and travel agents.

The in-person interaction combined with the memory of the persons attending the business produced empathy, being understood beyond the language and most of times before the language was used.

A lot of this personal b2c communications started with a “hi, are you coming because…? Don’t worry”. Big Data already existed but was stored and processed in the human brains. The magic thing happened when all the customer knowledge day by day accumulated by the persons at the other side of the desks were transformed in a very personal, focused and quickly directed to the “mattering point” of the customers using the intuition.

The ability of making customers “feel understood” in advance and avoid a lot of preamble each time that customer visited the bank, insurance company or travel agent was a valuable asset to increase loyalty and reduce churn.

Today “physical office” based customer service is declining as customer care becoming digital with a myriad of digital channels available as IVR, web, app and recently the emerging chatbot space. Customer care become ubiquitous and 24/7 but in the other hand it become more impersonal and colder. In some way the “understanding of each customer mindset” has been lost and with that loss a powerful customer retention tool has been lost too.

Obviously, in conversational digital channels as IVR and chatbots the very first priority was “understanding the language” and producing adequate language based responses. The progress of NLP/NLU/NLG in the last years was incredible and one of the main use cases for Artificial Intelligence & Machine Learning (AI/ML) and for that reason the “customer mindset understanding” have been postponed.

Once language for digital channels is achieving a nice quality and user experience it comes the right moment to balance the efforts and push the AI/ML for “customer mindset / customer behavior” understanding to produce “digital empathy” as outcome and use the outcome as loyalty and retention tool.

Anbotux is pioneering this area. How are we doing this? Well, we are collecting customer journey information, especially in the chatbot channel and combining with customer segmentation data and a myriad of external events to understand customer drivers, motivations, concerns. Anbotux implemented a flexible method to normalize how external events from very different nature (economic figures, weather, sport results, stock exchange evolution) are rated and processed in a unique way to compare with customer actions and customer care needs.

Is it so simple as measuring correlation between external phenomena and user actions? Unfortunately it’s not. Correlation does not mean causality and it is needed the use of AI & ML techniques to profile the “customer mindset” accurately and help to personalize the customer care interactions.

Last but not less…could the digital empathy engine be a separated element of customer care architecture and API accessible?

Yes! Anbotux did not want to reinvent the wheel; we tried to provide a value added new element complementing the current tech pieces of the customer care and chatbot puzzle. Anbotux database is fed with APIs and the customer profiles are provided using an API call that the chatbot engine (or IVR, web or app) can use to personalize and add empathy. Easy integration was a design must.

Cooperation is key to make feasible a better digital customer service and it would be needed that chatbot platforms made available via partnerships the “empathy engine”. It is just the beginning of this new field and it is expected to show results soon from first deployments and AI/ML & B2B focused VCs could see this new field as investment opportunity as well.