Overcoming Dirty Data and Other Roadblocks to Data Activation
Authored by ActionIQ Team
By now, every relevant corporation in the world has emphasized data as a keystone of their marketing, sales and lead generation strategy.
But data, of course, is not an end goal in itself. Data is a means to an end. Information and customer insights are what corporations need to launch personalized, relevant, insightful sales and marketing campaigns — the true end goal.
Too much emphasis on data for data’s sake, and not enough focus on the end result, can hamstring a company with the best of intentions. Harvard Business Review analyzed industry studies that showed that, on average, less than half of an organization’s structured data is actively used in making decisions — and less than 1% of its unstructured data is analyzed or used at all.
So how do you avoid becoming one of those many enterprises that spends massive amounts of time collecting data, but struggles to put that data into use? How can you convert data to customer insights, and then leverage those insights to create the most targeted, relevant marketing campaigns possible?
A lot of roadblocks stand between raw data and the perfect marketing campaign. Here are three things to look for to remove those roadblocks.
- Beware of Dirty Data
Keeping a clean contact database and reconciling different names for the same person is one of the most maddening exercises in managing data. Despite a data scientist’s best efforts, there are so many ways data gets dirty and fouls up an otherwise straightforward data activation process. Make sure the structure of your database sets you up for success, allowing for easy sorting and identification of duplications. Organize consistently by naming convention and watch for multiple emails, online profiles, and nicknames connected to the same person. Finally, screen for human error. Don’t let dirty data reduce the impact of your marketing efforts.
- Interpret Data, Don’t Just React to Customer Actions
Data interpretation is the key to unlock true value out of huge data sets. It is easy to see customer actions and enact rules-based responses. If a customer clicks, downloads or fills out a contact form, it is easy to follow up with an automated email or offer. What is harder is to interpret what those actions mean and predict the customer’s next move. This is the sales and marketing teams’ never-ending challenge — to be predictive and not reactive. Powerful data teams combine the efficiency of automation and predictive analytics with the power of human data interpretation to generate sales and marketing responses that see future customer actions and pick out ways to influence consumer behavior — not just react to the last action a customer took.
- Seek Uniformity in Reporting and Formatting
This might seem like boring, back-end housekeeping, but it is critical to your data activation success. Corporations still struggle with integration and clear reporting across platforms.
Make your data formatting and reporting are as uniform as possible, allowing you to easily combine and pull apart data sets, and get a clear and accurate picture of campaign performance across platforms.
If these seemingly tedious details are not taken care of, you may find yourself allocating more resources to seemingly effective marketing platforms whose true performance is being inflated by inaccurate reporting. Or you may get lost in the jungle of spreadsheets and disparate marketing data sets that require Herculean efforts to integrate and analyze.