I just spent several days in Las Vegas at TechWave, and was fortunate to be able to spend some time with some of our early adopter mobility customers. The fact that they are on the leading edge of mobility adoption means these are customers who have already show the foresight to be thinking strategically. One of the areas that came up consistently was how to find new and more effective ways to accumulate data that profiles customers, buying patterns, and up-selling/cross-selling opportunities, particularly for enterprises that have a B2C emphasis. Many savvy marketing thinkers are already at work developing best practices for mobile marketing and associated metrics. However, what may be missing from many enterprise plans for developing tactical and strategic business intelligence based on mobile device data is an appreciation of the subtle opportunities implicit in mobile user diversity.
Customer facing mobile apps are more than just a way to reach consumers in the right place and at the right time with buying incentives. They are also a tool for finding out what is happening in a given brand’s community right now.
Think of it in these terms; there will never be an opportunity to see a fresher view of customer sentiment and motivation than the one harvested from mobile device users engaged with your brand, because unlike desktop and laptop users, mobile device users have an implicit context in location and time. The immediacy of this context goes a long way toward bridging the gap between marketing data and business intelligence. The distinction is significant, because while data is useful, intelligence is something I can use to make decisions.
However, because it is based on dynamic data, business intelligence that is location or temporally driven tends to have a very short shelf-life. This is why it is crucial to architect mobile solutions that integrate well with existing business intelligence infrastructure. As an example, if an IT architect is trying to build out mobile business process support, what they absolutely don’t want to see in their enterprise mobile solution portfolio is a collection of standalone mobile apps that are captive in line-of-business silos. Mobile apps should be able to readily move their data to backend systems that aggregate and propagate information to additional business areas that could or should respond to changing conditions. Like mobility, analytics is endemic to an enterprise ecosystem and should be leveraged across all functions and processes.
An enterprise ready mobile strategy should integrate cleanly and securely with existing data management infrastructure, be able to operate across traditional lines of responsibility and enhance customer engagement opportunities. In essence, this is one of the defining qualities of a mobile enterprise application platform. Like enterprise apps and devices, developing and managing business intelligence is a job that demands holistic business process architectures.
This also begs the broader question, how expansive a definition of mobility and associated analytics should be factored into your planning? There are over 6 billion mobile devices in play globally, which is a pretty big number by any standards, but there are over 1 trillion wireless devices out there, all gathering data on a continuous basis. If you can stick a chip in it, you can give it an IP address, so this is not just about the consumer, it is about everything the consumer interacts with, all of which ties into gaining a more nuanced and actionable perspective of how to anticipate customer requirements. While the confluence of mobility and analytics offers a vast confluence of opportunity, we are barely seeing the tip of the iceberg.