Pitfalls to avoid when using Big Data in marketing

Posted by Justin Hesser on January 6, 2014

Marketing, at its core, is about two things: figuring out what exactly people want, and then positioning your product as the one that can deliver that most effectively. For a long time, before the ready proliferation of information, marketers were forced to do that via instinct — they had to quickly size up consumers and then hope that their impressions were correct. It was difficult, if not impossible, to determine how effective their techniques were.

Big Data changed that process. Instead of making choices blindly, marketers were able to use data to effectively identify the needs of their customers and figure out how best to target those needs. However, despite that obvious value, there are some pitfalls that are important to avoid in order to get the most out of the process.

Identify your core brand. It's critical to be able to adapt, but it's also crucial to provide a sense of continuity. Even companies with histories as long as Coca-Cola aren't immune to this trap: In 1985, the soft drink giant introduced "New Coke", a brand that tasted similar to top competitor Pepsi. Management thought it was a slam dunk. Pepsi had been winning in blind taste tests, so people clearly would gravitate towards this novel drink, right?


It became one of the biggest disasters in marketing history. Eventually, Coca Cola brass came to a conclusion that they should have started with — instead of using data analysis to copy your rivals, you should use it to enhance what is positive about your own brand. Once they went back to that, they retained their market dominance, and are still the leader in the industry, nearly two decades later.

Another potential mistake that marketers make is becoming complacent. They set up their custom database software, and expect it to do all of the work, while they blindly implement whatever it says to do. The oversight here is two fold. Not only is it important to have systems in place for properly evaluating the results and being able to separate signal from noise, it's critical to continue to improve the way in which you input data. Getting help with FileMaker isn't just a good idea, it's one that could save your core business.

Like any powerful tool, Big Data is incredibly helpful with the right insight and guidance. To properly wield it, make sure you have a firm understanding of the implications.