How Bad Data Can Blindside Your Marketing Analytics

Big data, in and of itself, is nothing special. Everyone and anyone can collect and aggregate data. But that doesn’t mean it’s providing value. The challenge is twofold: first, ensuring sufficient data integrity and second, successfully gleaning the insights to fuel smarter marketing.

The truth is it’s harder than ever to keep track of the modern consumer. Brands need to manage a seemingly endless number of touchpoints across different devices and marketing channels, from digital and social content to real-world interactions and purchases. It can be daunting to stay apace of where consumers are interacting with you, much less understand what drives and influences their behavior. For example, if you’re using a digital attribution model, you might not be able to account for the impact of traditional media. And if you can’t tell if that TV ad influenced a customer to visit your website, for instance, how can you have a true picture of performance and return on ad spend?

Then there’s the issue of data quality. “Garbage-in, garbage-out” applies here. If you’re putting bad information into your system, then no matter how precise your data model, you’re getting bad analytics in return....