Recording and analyzing details of transactions with customers is nothing new. In fact, traders 3,000 years ago did just that. When silicon became the new papyrus, it became possible to gain new insights into transactional patterns. In the 1990s, relational databases allowed enterprises—the new “traders”—to interrogate transaction data and report on customers, purchases, variability in product sales and the like. This first-generation marriage of data warehousing and business intelligence tools allowed enterprises to track performance against goals and adjust strategy to meet market demand.
These tools were dependent on the capture of highly structured transactional data from online transactional processing (OLTP) systems for relational database solutions, with data batch-processed, usually overnight, to create reports.
But there has been an explosion in customer touchpoints and data collection opportunities in the last few years—mobile usage, social media, even sensor- and telemetry-driven data—that offer unprecedented analytical horizons. It’s possible to deliver the right offer to the right customer at exactly the right time and place—if you can pull all this data together.
Unfortunately, this data—collected from online, mobile and social sources—doesn’t fit neatly into the data fields of a relational database model. This “unstructured” data—locational, opinionated, drawn from e-mail and chat and social sources, as well as point-of-sale and other transactional sources—is not the kind that the relational database was designed to deal with. Solutions that incorporate unstructured or semi-structured data into their decision-making process can involve a high degree of complexity. Add to that the necessity to deliver that intelligence to customer transaction points as varied as a cash register to a call centre to an online retail solution, and you’ve created a complex informational web that can cost as much, or more, to administer as the upsell benefits you draw.
But what if you could incorporate the benefits of unstructured data analytics without the complexity?
Read IBM Corp.’s technical whitepaper Simple is STILL better: Embrace Speed & Simplicity for a Competitive Edge, and learn how the much-vaunted speed of new data warehousing solutions isn’t enough alone to drive competitive advantage. Simplicity in a complex environment—simplicity that delivers the benefits of data-driven decision-making to everyone on the customer process, right out to the POS cashier and the call centre operator, rather than holding it within IT and the executive suite—can make a real bottom-line difference in terms of delivering performance and revenue. Learn how the equation of speed, simplicity and performance can transform your organization.