Data Quality Use Cases
Use these workflows to connect a specific CRM symptom with the fields, checks, review steps, and deliverables needed to address it.
Which use case do you need?
Pick the symptom, and the use case follows. Each page below covers one specific job that clean, enriched data makes possible. The categories are how we organize them, but nobody wakes up wanting "master data management." They wake up to a rep complaining that half their territory list is companies that went out of business.
Here's a quick map from common symptoms to the page that covers the fix:
| What you're seeing | Where to start |
|---|---|
| Reps ignore lead scores because "hot" leads keep being interns | Lead Scoring |
| Email bounce rate rising above your documented sending threshold | Email Marketing Cleanup |
| Two CRMs after an acquisition, one messy plan to combine them | Database Merge |
| ABM ads spending against accounts that don't fit | ABM Targeting |
| Board asked for a TAM number and you don't trust the one you have | TAM SAM SOM Analysis |
| Duplicate accounts, dead contacts, blank industry fields | CRM Hygiene |
If none of those sound like your situation, browse the full list below. And if you're still not sure what to call your problem, that's normal. Send us a sample export and we'll name it for you.
Sales & Revenue Operations
Accurate, complete prospect and customer data is the difference between a sales motion that's efficient and one that's just busy. Measure change against a dated baseline, then set the review cadence from the changes observed in your own system.
The use cases in this group share one goal: make sure the records your sales team touches are worth touching. Lead scoring and routing depend on filled-in firmographic fields. Territory planning falls apart when employee counts are two funding rounds old. Pipeline reviews run on whatever the CRM says, accurate or otherwise. A dated exception file keeps disputed values visible instead of silently forcing them into a segment.
Marketing & ABM
Marketing campaigns are only as good as the audience data underneath them. Measure change against a dated baseline instead of applying a general decay benchmark, then set the review cadence from the changes observed in your own system. Segmentation built on blank industry fields produces segments like "Other" that somehow contain a third of the database.
These use cases fix the data before the campaign runs. ICP development and lookalike modeling need enriched firmographics to find patterns. Email cleanup protects sender reputation, which is cheaper to keep than to rebuild. Customer profiling turns a flat contact list into something you can segment on purpose.
Data Management & Operations
The unglamorous work of keeping a CRM clean, accurate, and synced across systems. This is where most projects start, whether or not anyone planned it that way. You can't score leads, target accounts, or size markets on top of duplicates and dead records.
Migrations and merges deserve special mention. Moving to a new CRM with dirty data means paying to import garbage, then paying again to clean it inside a system you barely know yet. The right order is clean, then move.
Market Analysis & Strategy
Market sizing and expansion planning fall apart on bad inputs. A TAM model is a multiplication problem, and multiplying a wrong company count by a wrong average deal size produces a confidently wrong slide. The fix is building the market list from verified firmographic data instead of a purchased list nobody has audited.
SMB and local business data is its own challenge. Small companies close, rename, and relocate at rates that make enterprise data look stable. If your expansion plan depends on franchise operators or local businesses, plan on verifying the list, and plan on re-verifying it before launch.
What does a use case project look like?
The same shape regardless of which page brought you here. You send a file, or a CRM export, or read-only access.
There's no platform to learn and no annual license. That's the practical difference between hiring a use case out and buying a tool subscription: a tool gives you the ability to do the work, and you still have to do it. The project plan instead assigns file preparation, exception review, acceptance, and return import so ownership is clear before work begins.
Two use cases often collapse into one project: cleaning before a migration, enriching while deduping, or profiling customers as part of an ICP build. When the same source file and review rules support both outcomes, we can define one staged delivery instead of creating disconnected handoffs. The acceptance sheet still separates the output fields and review decisions for each use case, making the returned file easier to validate and import. If you want to understand the underlying work first, start with what data enrichment is, or see how we handle CRM hygiene and data validation specifically.
Don't see your use case?
Each business has unique data challenges. Tell us what you're trying to accomplish and we'll show you how clean, enriched data can help.
Get a Free AssessmentFrequently Asked Questions
What use cases does Verum support?
Verum supports a wide range of B2B data use cases including lead scoring, ABM targeting, CRM migration, data integration, sales prospecting, territory planning, ICP development, customer segmentation, market sizing, and more. We clean, enrich, and analyze data to support any revenue operations objective.
How do I know which use case applies to me?
Start with the business problem rather than the use case. Leads that aren't converting point to lead scoring or qualification. A CRM switch points to migration cleanup. A new ABM motion points to ABM targeting data. If the mapping isn't obvious, send us a sample export and we'll tell you where the real gap is.
Can Verum handle multiple use cases at once?
Yes, and most projects combine at least two. Cleaning before a CRM migration usually pairs with enrichment for lead scoring, since the file is already open. We scope by what your data needs rather than by a service menu.
Should I clean my data before enriching it, or enrich first?
Clean first. Enriching duplicate or dead records means paying to append fields to rows you'll delete later. We dedupe and validate before any enrichment runs, which is why the two get scoped together in most projects.
How long does a use case project take?
Larger jobs, like a two-CRM merge or a full TAM build, run one to two weeks depending on record count and how many sources we need to check.
What does this cost compared to a data tool subscription?
Projects use a written scope rather than a software seat. Compare the included workflow, internal operating effort, data rights, acceptance criteria, delivery, usage terms, and current proposal for each option.
Sources and references
Background references: BLS employee-tenure data and Salesforce's State of Sales research.