Whether you are implementing a new CRM system, migrating from one to another or even doing a data integration project, special consideration should be give to your data. The importance of good data quality should not be underestimated since poor or incomplete data can lead to a low acceptance of the CRM application.

One of the first and most important steps in any data processing task is to verify that your data values are correct or, at the very least, conform to some a set of rules. The remainder of this articles is designed to give you some best practices around cleansing data.

Pain Points

We know that preparing your data can be a source of pain. Cleaning data for migration into the CRM system is not always an easy process and can be quite time consuming. Most of the time, this requires a resource that is familiar with the data and has the fortitude to “fixing” it.

Key Questions

Before handing off your data to be migrated, you should ask yourself the following questions:

  • Have all the duplicates been removed?
  • Are naming conventions consistent?
  • Is the data complete?
  • What defines a winning record in the case of duplication?
  • Has the owner for each record been identified?

Solutions

Don’t stress out! While data cleansing is an important and potentially time consuming job, it has to be done and is manageable. We have tips on how to make it easier:

  • Develop and agree on rules that determine what stays and what goes
  • The people that are closest to the data should be working on it.
  • Conduct data quality analysis (Pivot Tables)
  • Check for missing data and fill in where possible
  • Find out “rules” for specific fields in your CRM application. For example:
    • Salesforce is very sensitive to bad email addresses. Spend the time to validate that they are formatted correctly or they will error out upon loading
    • Salesforce wants a person’s name to be formatted in First Name (“Cathy”) and Last Name (“Boudreau”)… not as one name field (“Cathy Boudreau”)
    • Salesforce has no Suffix name field. Add the suffix to the end of the last name
  • Build reports and test summaries
  • Work with others that understand the data. It’s important to have a firm understanding on the data and how it’s related. Sometimes the person working closest to the data may not be the one with the “structural” knowledge of the data.
  • Make sure key stakeholders sign off
  • Save backup copies of data

See? That’s all there is to it! Now get to work! On a more serious note, if you find the data overwhelming and still are having a tough time on figuring out where to start, call your CRM consultant (like LiquidHub!). They will know where to start and can help guide you.

Have you undergone a major data migration project? How did it go? Do you have any advice or things that worked/didn’t work? Things you wish you did differently? Let us know in the comments below!

Launching a CRM implementation? Be sure to read this to learn the do's and don'ts to ensure it runs smoothly.