The old adage “making lemonade out of the lemons” is never more true than when you are working to create insights from customer data. Here is the hard truth — your customer data will NEVER be completely accurate. There will always be inaccurate records, incomplete addresses, invalid emails. In our “No Excuses Marketing” approach, we tell our clients (nicely of course) to “get over it.” Customer records are not clean and never will be.
However, your data can be used RIGHT NOW to help you build relationships, increase profitability and grow your business — if you can take this one step: Use What You Have.
You would be surprised how many people I meet who tell me that they are waiting for the great Data Warehouse In the Sky. You and I know that waiting for the data warehouse to solve your problems is like Waiting for Godot — you wait for something that never arrives. No disparagement to IT people building data warehouses, by the way; I mean that even when the warehouse comes, customer data will still have inaccuracies and marketers must be ready to work in that environment.
So if the data is always somewhat inaccurate, how do you market effectively to customers?
Here are three keys to driving insight from incomplete customer data:
- Set rules for valid information. For example, use only records that have completed address fields, emails that have a valid .com, .net, or .edu tag. A large number of records may be excluded, but often the majority will make the cut.
- Focus on a subset to drive learnings. For example, in a retail business, analyze customer data from the top 20% of stores with the most accurate data. In a direct sales business, analyze customer data from the most accurate 20% of salespeople, or markets. No matter what, you can find pockets where data completeness is higher than the average. Analyze that subset, and your conclusions will be more valid than looking at the whole.
- Show the value of complete data. Several of our clients will only do database marketing around stores that meet a threshold of data completeness. By showing how those stores perform better than other stores due to the extra traffic from the marketing, the team can now make the case for all stores to work harder to complete customer records.
These three keys are strategies, not tactics. They lay out the basic framework for how to identify valuable data, how to conduct analysis on that customer data to drive insights and how to drive the importance of data completeness to the organization in “black and white terms.”
How to take these strategies to action in your company must be based on the dynamics of your industry, the types of data available and the speed at which you can bring data-driven marketing efforts to bear.
What barriers do you see to implementing these strategies in your organization?
