Ai for call centres proved successful.

Successful,Customer, Service, Artificial, Intelligence, Analytics, Predictive, Prescriptive, Business, Core, Drivers, MIS, Dashboards, BPO, Cape, Town, Intelligent, Quality, Assessment, Top, BPO, CEX, CX, Data, Script, insights, functional, innovation, machine learning, ML, BI, Learning, Company

Genii Ai successfully deployed our first Ai solution at a large global mobile company, predicting customer intent, with great results! Thanks to a great team, we have a clear case study of a successful Ai model deployment, predicting customer service demand cycles. With a high margin of accuracy, we successfully predicted Who, Why and When customer are going to contact the company for service support. We overlaid the prediction with the actuals for an initial 3 months’ period, with amazing accuracy. The algorithms are working well, and the machine learning model will now become more and more accurate over the next few months, as we add more and more data.

As a first campaign, the mobile company will launch a proactive communication campaign to the identified customers, thus reducing the call volumes. The target is to reduce customer effort by reducing contacts between 20% and 30% over the next three years. This would improve CX as customers receive communication that their queries would be fixed, before having to call the call centre. The next wave of improvements would shift customers to self-service digital channels, as well as improving the call centre resourcing requirements. Knowing who, why and when customers are going to contact you for service queries/requests enable the companies to proact, rather that react.