At the intersection of mobility and analytics lies radical change. Organizations are using a combination of mobility and analytics to address consumer pain points, make life easier, control costs and ensure consumer delight.
Retailers have been studying consumer-buying patterns for a while now to provide a rich shopping experience over mobile devices. Once a consumer makes a choice, analytics and AI-driven chatbots take over. These bots are consistent, available 24X7 and can go everywhere on a mobile device, replacing human effort. With the likes of Microsoft and Amazon pioneering even more advanced chatbots such as Zo and Alexa, the bots are being used for diverse tasks like looking up troubleshooting steps for a malfunctioning device, setting up meetings and assisting with shopping. And, all this is happening at a fraction of the cost it would take humans to do. However, the appeal for users is not the cost factor. The real appeal lies in the fact that bots are humanizing these apps by using smart and near-human attributes.
Chatbots achieve these complex tasks by analyzing the flood of data they are exposed to. Business rules and algorithms are then used to extract knowledge and machine learning is deployed to improve the ability to reach accurate decisions.
In the world of medicine, for example, analytics and mobility are creating nothing short of what may have appeared to be miracles until a few decades ago. Take the use of smartphone cameras for diabetic retinopathy screening. Early detection and treatment of the condition can prevent visual impairment. Factors such as the availability of retinal specialists and trained technicians, as well as the high cost of photographic equipment, had limited the detection of this widespread health issue. However, using a smartphone and analytics, patients can be screened anywhere in the world, including remote locations, without doctors having to travel. A US-based managed care consortium reports that diabetes patients visited emergency rooms 29 times less after their electronic health records were made accessible. These are example of a dramatic increase in efficiency using analytics and mobile technology.
These mobile applications are built on a strong foundation of readily available, and often real-time, data. The problem is that organizations are too closely focused on acquiring data. They need to quickly move to placing equal emphasis on analyzing their data, with the help of bots, just so their mobile applications combine contextual intelligence with the data to bring rich experiences to customers.
Every industry, from hospitality to transport, from manufacturing to insurance, can use mobility and analytics in an affordable Backend-as-a-Service model to smoothen customer-facing processes and improve experience. Organizations are realizing just how indispensable the two are to solving customer pain points, providing differentiated value, ensuring customer loyalty and controlling costs.