Data stored in your CRM can be universally valuable across your organization. Accurate data points return ROI indicators, sales forecasts, engagement activity, and other insights that can be utilized to increase sales and improve targeting and customer service. But what happens when that data becomes unorganized, incorrect, or outdated? Now you’re swimming in a sea of misinformation. We asked our CRM experts for some tips to clean and maintain CRM account data. Here’s what they had to say:
When a customer comes to us and says they want to clean up their CRM Accounts, they are typically referring to a few different aspects of their data:
- Identifying and merging duplicate accounts, aka duplicate detection
- Removing accounts that no longer have business value, i.e. prospects from 5 years ago that never became customers
- Having more complete data on accounts in CRM
- Having more accurate data on accounts in CRM
To get started with duplicate detection, we suggest first asking your CRM consultant for recommendations. Odds are, they probably have some trusted partners they’ve worked with before who they know can perform an accurate duplicate data scan.
For example, at TAI, we’ve partnered with a company out of the UK called DQ Global. We work with them to do one-time data cleaning for our customers or periodic scans through their subscription product that runs on a regular (i.e. daily, weekly, etc.) basis via StarfishETL. DQ Global’s service/product allows customers to match on a variety of criteria (i.e. name and city) and set parameters for how ‘close’ of a match the values must be. The service also gives us the authority to decide whether to mark the duplicates for a user to review or merge automatically.
Removing Old Accounts
For older data that no longer has business value, we recommend putting together a data governance policy and then building processes to automate that policy. A data governance policy defines the rules and regulations for how your CRM users can work with and share your data. Proper data governance streamlines processes and creates consistencies to keep everyone on the same page. As you start creating a data governance policy, keep these tips in mind:
- Define a clear purpose and scope for your data policy. Who or what does it apply to? What doesn’t it apply to?
- Define policies for all aspects of your data: data access, data usage, data integration, data integrity, etc.
- Clearly define the roles and responsibilities of each person and/or department being asked to comply with your policy
- If you use any specific terminology in your business, compile those terms and provide clear definitions for each in your data policy
- Put a data governance team in place to lead the adoption of the new policy and uphold the parameters you set for governance
Once your data governance policy is set, find a tool to automate as much as possible. This frees up your teams and helps prevent errors and misplaced data. Our sister company, StarfishETL, is one example of a useful tool for automating your data governance. StarfishETL allows users to set up an automated job to run at the intervals they choose. Ask your consultant for recommendations on automating a data governance plan to be sure you’re using the right tools and executing it in the right way for your systems.
Creating Complete CRM Account Data
For better data completion, consider the following two options:
- Look at which fields are required: Make sure the most important data fields are required where feasible. This will ensure that users cannot forget to complete these fields.
- Build mechanisms to identify less complete accounts: This could be accomplished by building reports to show the records' missing key values. Or, you could set up a data score via a calculated field in your CRM. On top of that, consider incentivizing data completeness and/or gamifying it in some way (i.e. a data completeness leaderboard showing which division(s) and which user(s) have the best data completion scores).
Maintaining Accurate CRM Account Data
For better data accuracy, consider partnering with a data enrichment service. Many CRM companies are making data enrichment capabilities a priority for their products. One example of this is the Hint feature in SugarCRM. Hint is built into Sugar and can provide an additional source of account and contact data for users to easily add information to an account.
If your CRM doesn’t offer innate data enrichment, consider partnering with a company that specializes in the type of enrichment you need. For example, if having accurate addresses is important, consider integrating with an address verification and National Change of Address program – we’ve partnered with SmartSoft and used their AccuMail product for this need with our own customers and have received positive feedback on their experiences.