Smart Data - Not Big Data
Conversely, some people became more afraid—often with good reasons. But even more often, people react based on pure fear that their personal information is being actively exploited without their consent. While data geeks are rejoicing in the age of open source and cloud computing, many more are looking at this hype with deep suspicions, and they boldly reject storing any personal data in those obscure "clouds." There are some people who don't even sign up for EZ Pass and voluntarily stay on the long lane to pay tolls in the old, but untraceable way.
Nevertheless, not all is lost in this hype. The data got really big, and types of data that were previously unavailable, such as mobile and social data, became available to many marketers. Focus groups are now the size of Twitter followers of the company or a subject matter. The collection rate of POS (point of service) data has been increasingly steady, and some data players became virtuosi in using such fresh and abundant data to impress their customers (though some crossed that "creepy" line inadvertently). Different types of data are being used together now, and such merging activities will compound the predictive power even further. Analysts are dealing with less missing data, though no dataset would ever be totally complete. Developers in open source environments are now able to move really fast with new toolsets that would just run on any device. Simply, things that our forefathers of direct marketing used to take six months to complete can be done in few hours, and in the near future, maybe within a few seconds.
And that may be a good thing and a bad thing. If we do this right, without creating too many angry consumers and without burning holes in our budgets, we are currently in a position to achieve great many things in terms of predicting the future and making everyone's lives a little more convenient. If we screw it up badly, we will end up creating lots of angry customers by abusing sensitive data and, at the same time, wasting a whole lot of investors' money. Then this Big Data thing will go down in history as a great money-eating hype.
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.