- This playbook is designed for beginner CRM administrators.
The objectives of this playbook are to:
- Identify and scope missing data problems
- Populate missing data or add a missing identifier
- Read our data management strategy playbook for help with creating a data management strategy.
- The DemandTools modules referenced in this playbook are for versions 5.X.X. Please be sure to update your software.
- We recommend standardizing your data first as it can fix many malformed data problems.
- We recommend setting up a sandbox environment to test data manipulations prior to implementing them in a production environment. You don’t want to make changes that adversely affect your CRM data quality.
- If you are trying to solve a specific data problem, review the product training documentation in the Validity Help center or get answers to your questions from Validity’s data experts during office hours.
- For technical issues regarding your software, please contact Validity support.
A clear data management strategy will help to improve your CRM data quality and support achieving your desired business outcomes. With a clean CRM database, many businesses achieve better:
- Accuracy in sales forecasts and reporting
- Data privacy compliance
- Targeting for marketing
- Operational efficiency
- Assess missing data
- Missing data methodology
- Selecting a frequency
- Assessing missing data
- Addressing missing data
- Automating missing scenarios
- What to do next
- Data governance: Developing and implementing data policies and procedures to support business goals.
- Data quality: Accurate, complete, reliable, and actionable data.
- Data standardization: Applying a common and consistent data format.
- Data hygiene: The process of cleaning data to reduce errors and improve data quality.
Preventing missing data
Proactive data management is a key strategy for maintaining a clean database. Talk with the data governance team to determine what data is important and required, so you don’t ask for data that is irrelevant, unactionable, and meaningless. If you fill your CRM with data fields that will never be populated, then you waste time trying to find and populate data that isn’t needed for effective communication and informing business decisions.
Another effective way to prevent missing data is to reduce manual data entry by implementing configurable data types and business rules along in your CRM or web form.
- Configurable data types include picklists, using check boxes to affirm a selection, or to provide multiple choice options and radio buttons to limit a selection.
- Business rules may be an email address syntax check and validation on a web form or populating the state/province and country based on the entered zip/postal code.
- Recognizing and addressing missing data upon import can help prevent some missing data problems.
Required fields in your CRM or web form are also effective at preventing missing data. However, requiring too many fields may cause some people to enter incorrect data to bypass the field requirement. So, it’s important to keep required fields to a minimum.
Before you start addressing your missing data, ensure you have a plan in place to help you manage activities. A plan can help you split up the amount of work you do into manageable sizes and help ensure you identify and address missing records.
Decide on the frequency you need to address missing data. How frequently you address missing data depends on the rate at which you are introducing new records into your organization as well as the overall size of your database. Determine the frequency based on your needs. No matter what frequency is required, you can automate your activities using DemandTools.
- Daily: If you have hundreds of new records coming in daily from different channels, you probably need to run missing jobs daily.
- Weekly or monthly: If you have records that trickle in each week or come in less frequently, then you probably need to run missing jobs weekly or monthly.
- Quarterly: Each quarter, schedule a comprehensive data review and cleanse to ensure all records are addressed as expected.
- Address missing data upon import: DemandTools allows you to analyze and populate data during import. Be sure to train staff responsible for importing on any requirements and procedures.
Data may be input manually in your CRM by staff in your sales, marketing, customer success, and finance teams, so you may need to adjust frequency even if your data intake rate is low.
Assess missing data
Assess your missing data problems using Assess and Tune or Export modules to understand the scope of work and potential sources of missing data.
- Review your Assess results within my.validity.com to get a high-level view of missing data by object and prioritize work based on severity. The Assess feature breaks down missing data by object and categorizes it as:
- Missing engagement (e.g., email address, billing and shipping address, phone number)
- Missing business segmentation (e.g., role, industry, company size)
- Incomplete decision support (e.g., currency, sales region)
- For each object, perform additional analysis to identify specific missing data types or data fields.
- With your data governance team, determine what data is most important to your business and create a prioritized list based on the object and/or data type. Some data may be populated at different times in the sales or customer lifecycle, so it’s important to understand what the data is and if it needs to have a value for its place in the lifecycle.
- For example, you don’t need to look for and address a missing product user ID for a lead because they are not a customer yet. If the lead is missing a phone number and email address, then it’s a higher priority to get the information.
Below is a list of commonly missed data to look for during your assessment.
- Account type
- Employee count
- Phone number
- Mailing, shipping or billing address
- Website address
Lead or Contact
- First or last name
- Phone number
- Email address
- Mailing address
- Lead source
- Record type
- Forecasted value
Address missing data
Now you have a prioritized list of missing data to search for and address. Use DemandTools to populate a correct value or to populate a missing data field identifier that the sales, marketing, customer success, or finance teams can use to identify and fill in missing data.
Automate your missing data scenarios
Schedule your standardization scenarios to run automatically at a frequency you define. We recommend testing scenario automations in a sandbox prior to implementing the automations in a production environment.
Data governance team alignment
As you work through addressing missing data, talk to your data governance team about sources of missing data and recommend improvements such as employee training or system enhancements to proactively reduce data errors.
- Continue cleaning your data using our other data playbooks.