“Big data” blossomed into one of the most used marketing buzzwords of 2012. From the Obama campaign’s use of data to drive donations and volunteering to concerns about “do not track” standards, it’s been the year of big data.
Most of the focus has been on how to use data to improve your marketing or learn more about your potential clients. However, it’s just as important to think about all of the things that you shouldn’t do with your marketing and customer data.
Don’t approach your data like it’s nothing more than numbers.
When you analyze your customer base and find that 60% are female and 25% have purchased both in-store and online in the last year, it’s easy to think of all of your customers as nothing more than part of a larger list. However, there is a very real person behind every email address, every birth date, every purchase, every email open, etc.
Big data is big because it’s a set that’s so complex and large that it can’t be housed and handled with standard tools. That volume of data is useful for finding interesting and important correlations (like the correlation between buying unscented lotions and pregnancy that Target found when it analyzed its baby registry data). But that doesn’t mean that the people behind that data can be reduced down into those numbers.
Testing and data analysis can help you more efficiently drive and measure behaviors. It’s considering the motives and emotions that go into the behaviors that’s going to help you generate hypotheses to test and develop creative that moves potential customers to become customers.
Don’t house data in multiple places with no master list.
Lots of people in your company need to use and collect information about customers and prospective customers. Customer service reps can contribute information about past purchase satisfaction, and the marketing team can map in data about website browsing and buying.
When everyone is maintaining information in multiple places, the ability to find meaningful patterns is limited. Imagine, for instance, that the majority of people who bought an item from your website after clicking on a PPC ad later called to complain and request a refund. That type of data could point to a misleading ad or keyword that changes the expectations of a buyer.
Target, while it has raised some privacy concerns over how it uses data, is a good example of a company that ensures that all information about a customer is fed into a single database. Purchases online and in-store, registry information, customer helpline questions, email opens, and more all feed back to a single customer ID.
One caveat: If you are extremely sophisticated in your data collection, make sure customers understand the information you collect, how it’s collected, and how it’s used. Lack of clarity here can create legal concerns and can leave customers feeling like your knowledge of them is “creepy” rather than helpful.
Don’t take the responsibility of storing customer data lightly.
Just as you need to respect your subscribers in email marketing, you need to respect your customers when handling their personally identifying information.
Respecting your customers’ data includes:
What other data don’ts do you think are important when dealing with big data?
Image courtesy of Ravenelle.
Eric Didier CEO & Co-Founder Eric Didier is a successful serial entrepreneur with a broad background in enterprise software sales management, complex software development and product management for web technologies. He was the founder and CEO of Soamai in 2000, a metadata applications company which was acquired by Allen Systems Group in April 2004. He can be reached at email@example.com.