Your CRM doesn’t stay clean just because you cleaned it once.
CRM cleanup is often treated like a project.
RevOps identifies the problem, exports records, works through duplicates and missing fields, standardizes values, fixes ownership issues, and gets the CRM back into shape.
Then the data starts changing again.
New leads and contacts enter the CRM. Reps update records differently. Accounts change. Integrations write new information into fields. Required data gets missed. Duplicate records appear.
A few months later, RevOps is staring at another cleanup project.
The problem isn’t getting your CRM clean once. It’s keeping it clean as the data changes.
The play: Define what clean data looks like. Ballet maintains it.
You already know the rules your CRM data should follow. Instead of repeatedly finding and fixing the same problems, describe those rules to Ballet in plain English.
What you hand Ballet
Continuously check our Salesforce account, contact, and opportunity records for duplicates, missing required fields, inconsistent values, and data that no longer matches our CRM rules. Fix issues automatically when there is a clear rule for what the value should be. If a record is ambiguous or requires a RevOps decision, flag it for review instead of changing it.
Ballet builds the integrations and workflow needed to inspect the relevant records, apply your cleanup logic, make defined fixes, and surface exceptions.
Once built, the workflow runs as deterministic, reviewable code, so your team can see what was changed and what still needs attention.
You define what clean looks like. Ballet builds the workflow that keeps it that way.
Here’s how the workflow runs
1. Ballet checks your CRM continuously
Instead of waiting for the next quarterly cleanup, Ballet checks your CRM for the data issues your team has defined.
Depending on the workflow, that could mean checking new or updated records as they enter Salesforce, running scheduled checks across existing records, or both.
2. Ballet identifies records that don’t meet your rules
Ballet evaluates your CRM data against the rules your team has defined, pulling in information from other systems when the workflow needs it.
Your team defines which systems, fields, and rules matter to your CRM hygiene process.
3. Ballet fixes what has a clear answer
Not every data issue needs to become a RevOps task.
When the correct action can be determined from the rules and information available, Ballet can make the defined change automatically.
That might mean filling a required field from an approved source, standardizing a field value, correcting a record that violates a defined rule, or updating ownership based on current routing logic.
Each fix follows the logic your team has established rather than relying on someone to work through records one by one.
4. Ballet flags the exceptions
Some records don’t have an obvious answer.
Two accounts may look like duplicates but require a decision before they’re merged. An opportunity may be missing a close date with no reliable source for the correct value. Ownership might be unclear because a record matches more than one territory rule.
Instead of guessing, Ballet surfaces those records for review.
Needs review: Possible duplicate accounts have conflicting account owners.
Needs review: Opportunity is missing a close date and no reliable value could be determined.
Needs review: Record matches multiple ownership rules.
RevOps spends its time on the exceptions that actually require judgment instead of manually reviewing every record.
5. CRM hygiene becomes an ongoing process
Fixing today’s issues doesn’t prevent tomorrow’s.
As new records enter the CRM and existing records change, the workflow continues applying the rules your team has defined. Routine issues can be addressed as they appear, while exceptions continue to flow to RevOps for review.
That’s what turns CRM hygiene from a recurring cleanup project into a maintained state.
From messy CRM to maintained CRM hygiene
Your CRM keeps changing. Ballet continuously checks the data, fixes what follows a clear rule, and surfaces what needs your team’s attention.
Less cleanup. More confidence in your CRM.
When routine data issues are identified and fixed continuously, RevOps doesn’t have to wait for another large cleanup project to get the CRM back into shape.
Defined fixes happen as part of the workflow. Ambiguous records are separated out for review. And the team can see what was fixed, what was flagged, and where recurring data-quality problems are coming from.
The result is a CRM that’s easier for Sales, Marketing, and RevOps to rely on without requiring someone to constantly clean it by hand.
Take this play and make it yours
Every company has a different definition of clean CRM data. Start with the rules your RevOps team already uses:
- Which CRM objects and fields need to stay clean?
- What makes a record incomplete or incorrect?
- How do you identify duplicates?
- Which fields should follow standardized values?
- What sources can be trusted to fill or correct missing information?
- Which changes can happen automatically?
- Which changes should always require human review?
- How often should each check run?
You don’t need to turn those rules into scripts or build the integrations yourself. Start with what clean data means to your team and what you currently do when a record doesn’t meet that standard.
