Addressing Data Quality

Data Quality is one of the biggest challenges sales and marketing leaders face in their CRM. In our CRM & Sales Impact Report, we found that one third of respondents reported that their CRM data was incomplete, out of date, or inaccurate. The impact of inaccurate and incomplete data stretches far beyond the CRM itself, presenting challenges for automated marketing campaigns, Voice of the Customer programs, and any other initiatives that rely on targeting the right message to the right contact at the right time - something we all know is more effective than generic, blast communications. Not to mention the toll it can take on providing stellar experiences for your customers. 

In this post I'll be sharing my top 3 tips that can help keep your data in tip top shape, but I'd love to hear in the comments below methods that others employ to help keep their data clean. 

  1. Field Standardization - One easy fix that can help alleviate data discrepancies is standardization of common fields (states, countries, industries, etc.) through drop-downs or multi-select fields. This will prevent data discrepancies such as US vs. USA vs. United States. This makes it easier to automate processes because like data will be consistent.
  2. Required Fields - While forcing users to enter lots of required fields can be burdensome, using them judiciously can help ensure important, needed information is entered. This is a key area where people, process, and technology alignment is required. If you simply make the field entry required in the technology, but don't education your users on the process, you'll get A LOT of fake entries just to get around the requirement. look familiar to anyone? You'll want to make sure users understand WHY the field is required and that it is important for the data entered to be accurate. If they know the marketing team is using it to automate nurture campaigns to better qualify that lead, they will be more inclined to enter correct information.
  3. Data Augmentation - It can be hard work to complete a contact card, but now more than ever there are technologies available to give us a helping hand. With tools like Hint, you can easily add enhanced data from external sources to your contacts with the click of a button. Not only will you alleviate friction with your leads and contacts by asking for less information from them, but you can reduce time and effort for your users as well. 

These are some of the top ways I've seen companies tackle the data quality challenge. You can find more great tips from our services team here. What are some of the tactics and methods you've employed to keep your data clean and tidy?