For example, Acme Motorcycles (a hypothetical electric motorcycle manufacturer) discovered via AI that if it could get a prospective customer into a showroom and get them on a test drive then there was strong chance they would purchase the bike. Velocity data sent from the motorcycle test-drive experience in real time to the dealer and then pushed into the CEP engine indicated that if a customer drove the bike at over 50 MPH then the likelihood of purchase increased 10%. When the customer returns from the test drive, if the dealer's analysis dashboard shows that the customer is in "neutral" state, then the dealer would be provided with a recommendation to advise the customer to go back on the road and try the bike on the highway.

Measurement of true customer satisfaction has always been the Holy Grail of customer experience. Sure, there are several methods currently in use, including net promoter scores (NPS), customer effort scores, and customer satisfaction scores (CSAT). Typically these approaches are fed by customer surveys--quite often the results are too little and too late. But what would happen if we disrupted customer satisfaction measurement using the Internet of Things (IoT) and artificial intelligence (AI)? The first step to this new disruptive approach is to have customers opt in and provide the data streams that could be fed into an IoT Complex Event Processor (CEP engine), which is a collection of technology components that can process millions of events from mobile devices, connected products, website clicks, social media posts, and pretty much any type of message that can be generated by computers.