Big Data Hurdles to Overcome in Direct Mail: Accuracy

Big Data has emerged to tame the volume, velocity and variability of the massive data sets that are used in today’s direct marketing world. So what is Big Data? Simply put, it is conventionally structured data combined with unstructured data from mobile devices, social media channels, the cloud, and various other sources. This is what we’ve always wanted as marketers, right? We need more customer information to create personalized, relevant messages! But now that the data is piling up, how do we organize and analyze it in a meaningful way?

This series of three blog posts will review three Big Data hurdles that could affect your direct mail program and give you suggestions on how to overcome them.

Let’s begin with maintaining Accuracy.
When you decide to utilize the data you’ve collected from every customer interaction, it can be a risky business. You’re trying to connect on a personal level with the consumer, but nothing spells mass advertising like a misspelled name or outdated information. Inaccuracies can be a result of key entered data, duplicate data, and outdated databases to name a few. Companies that utilize key entered data must constantly comb through this data to ensure its accuracy.

Because data can be generated from virtually every interaction, there’s a high risk of data duplication or conflicts. Your customer Robert Lewis might have used the name Bob Lewis when he downloaded a recent white paper from your website. Imagine his frustration if your next marketing touch uses the wrong version of his name. Incomplete or incorrect data has led to millions of dollars wasted each year in company strategies.

How does this impact direct mail?
Data from third parties should be reviewed for accuracy and sourcing.

• It is important to ask how the data has been collected. If it is compiled data rather than data that is self-reported, you want to have a high level of confidence your provider has done due diligence on its quality. It’s a best practice to use data that has been verified at multiple sources.
• Check the data for completeness, especially for areas of information that will be used to personalize your direct mail.
• Let your vendor know what your threshold is for missing fields in the database and provide a default value that can be used in place of the missing data, such as “friend” for full name.
• Check how often the data is updated. National Change of Address (NCOA) corrections must be made every 90 days for USPS discounts.

More to come on the next Big Data hurdle - ensuring Consistency.