Customers today expect much more from the brands and companies they work with, and increasingly that expectation includes a desire for personalized service. Per research by McKinsey, 71% of customers want a personalized experience and 76% become frustrated by a lack of such interactions.  

A McKinsey study found that while 77 percent of customer service leaders say their companies have developed digital platforms, only 20 percent of their digital contacts are done unassisted—even as contact center volume continues to grow. That’s a clear indication of the tremendous opportunity to leverage evolving technologies to drive higher return on investment (ROI) at the contact center, especially at a time of agent staff shortages.    

The phrase “predictive analytics” holds a lot of promises—about solving problems before they occur, better service outcomes, targeting scarce resources, supporting decisions and improving responses in time critical situations.

With so much opportunity available, how can government start to consider the risks and benefits associated with this technology?

Project Deep Blue is a Mastek initiative that encourages engineering graduates to create innovative technology solutions for non-profits to address challenges faced by them in solving real-life social problems. Currently, in its fifth season, this unique programme acts as a bridge between the industry and academia and has amassed tremendous popularity in the engineering community for offering students the opportunity to design, develop and build solutions in a project-like environment. Over a period of three months, students are guided by their assigned mentors to successfully develop solutions to address various social problems in the field of education, healthcare, and citizen services – facilitated and identified by Mastek Foundation.

In FMCG, F = Fast. Retailers need to adapt to rapid changes in consumer attitudes and the marketplace. Every aspect of retail operations has the potential to make or break the customer experience. AI technologies are breaking down barriers and making it imperative for retailers to adopt a globally competitive retail business model. The power of machine learning has made it possible for businesses to continuously scrutinize customer behaviour data and generate alerts when the time is right for the next best action.