Lessons From the Facebook Fiasco
Mindless hoarding often gets the collector in trouble like we are seeing here. Sometimes “more” data increase only trouble, not the targeting accuracy. Yes, the databases must be broad, accurate, recent and consistent to be useful. But too many data players became too greedy, and there are consequences of being greedy.
Maybe the notion of Big Data gave a wrong impression that big is always good. There are costs involved in dealing with really large data, and another lesson that we must learn here is that a collector can make people mad if “they” think that he is going after too much data.
If the goal is to obtain a “reasonable” level of accuracy in targeting, no, you don’t have to have every piece of data about the target. No analyst likes missing values, but there will be no complete database now or in the future, anyway. A job of analysts is to make the most of what they get, not asking for the entire universe. So, always consider the cost of hoarding too much information, including the social cost.
If all Cambridge Analytica wanted was to predict who was more likely to vote for Trump last year, there were many safer and simpler ways to go about doing that.
Facebook Is Too Powerful?
The ironic part of it all is that Facebook, thanks to its vast coverage, doesn’t require pinpoint targeting precision, anyway. It’s not like it’s going to spend over $1 per piece in direct mailing. Targeted messages are cheap on that platform, and the risk of being wrong is not that high (relatively speaking).
And it seems like Facebook knows it, too. Based on numerous articles that I read about this incident, its analytics is more about maintaining a captive audience by creating a very addictive platform. If the number of eyeballs and time spent on the page are what they are really pursuing, they seem to be doing a fine job there.
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.