Databases allow sales and marketing to reach customers and nurture relationships more effectively (and efficiently). If they're designed properly and used correctly, they are the marketing “secret sauce.” Unfortunately, this is not always the case.
If you don't know what the problem is, you won't be able to fix it. So, here are some of the most common mistakes made by marketers:
Monitoring relevant statistics like retention, reactivation, conversion and percent new-to-file allows marketers to more easily determine the success of various marketing strategies.
By not having standards in place, you could run into mailing inefficiencies and customer service problems. (Avoid this and scrub that data!)
Response models very greatly. Each business needs to dig into their data (and their goals) to determine what model works best for them. Many people even recommend that 75% of analysts’ time should be spent digging in to customer data.
Without basic database knowledge, a marketer is not able to establish marketing specifications for database development to maximize effectiveness.
All tests need a control and a measurable variable. If there are multiple variables, they should be clearly stated and clearly measurable. Knowing and applying basic testing rules will ensure results are readable, reliable and projectable. It's also key that you understand how you'll read the final test results before you run the test.
Ok, one more:
It's recommended that you keep key data – including all promotional data – for inactive customers for at least 4 years for future analysis purposes.
These mistakes are easy to make. But being aware of them can help you ensure that you don’t face the same problems. Take steps to evaluate your strategy and resolve these issues to improve your data-driven marketing efforts.
We recommend that you start by reading What Data-Driven Marketing Is and Why It's So Effective. And then share it with your entire team!
After that, to learn more about how other companies are using and viewing their data, read The 2022 State of Data and Technology: A Year of Herding Cats and Black Holes.