Data Hygiene Services for B2B Teams

Verum is a managed data hygiene service. You send us a file or a CRM export, and we send back records that are verified, deduplicated, standardized, and filled in. There is no platform to learn and no license to buy. Most projects start at $2,000 and come back within 24 to 48 hours.

We run five services, and most engagements combine two or three of them. Pick the one that matches your problem, or send us a sample and we'll tell you which combination your data needs.

What Is Data Cleaning?

Data cleaning is the process of finding and fixing errors in a dataset: duplicate records, outdated contact information, inconsistent formats, and fields that contradict each other. In a B2B context, that usually means a CRM full of contacts who changed jobs, companies that got acquired, phone numbers that ring nowhere, and the same account entered four different ways by four different reps.

A typical cleaning pass on a Salesforce or HubSpot export covers deduplication, email and phone verification, job title normalization (mapping "VP Mktg," "Vice President, Marketing," and "Marketing VP" to one value), address standardization, and flagging records for companies that no longer exist. If you want the detail on how we normalize titles specifically, our guide to Salesforce job title standardization walks through the mapping logic.

Cleaning fixes what you have. It doesn't add what's missing. That second job is enrichment, which we cover in what is data enrichment.

Data Cleaning vs. Data Cleansing vs. Data Hygiene

People search for all three, and vendors use them interchangeably. The honest answer: data cleaning and data cleansing are the same activity. "Cleansing" is the term enterprise software vendors and UK teams tend to use, "cleaning" is more common in the US and in data science. Same duplicates, same fixes.

Data hygiene is the wider discipline. A one-time cleanup is cleaning. The set of habits, checks, and scheduled maintenance that keeps a database from degrading again is hygiene. One is an event, the other is a practice. Our CRM hygiene page covers what an ongoing program looks like inside Salesforce and HubSpot.

Why Data Cleaning Is Important

B2B contact data decays at roughly 30% per year. People change jobs, companies merge, phone systems get replaced. A database that was accurate in January is measurably wrong by December even if nobody touches it.

The cost shows up in specific places. Reps dial numbers that don't connect. Email campaigns bounce hard enough to damage your sender reputation. Duplicate accounts split activity history, so nobody sees the full picture of a relationship. Territory plans get built on employee counts that are two years stale.

The problem is old and well documented. Anaconda's State of Data Science survey found data professionals spend about 39% of their time on data preparation and cleansing rather than analysis. Sales teams don't track it as carefully, but the pattern is the same: skilled people doing janitorial work on spreadsheets because nobody owns the pipeline.

How Much Do Data Cleaning Services Cost?

Verum prices per project, and most projects start at $2,000. The final number depends on record count and how many services you stack. Cleaning 10,000 records costs less than cleaning, enriching, and verifying 100,000.

For comparison, the alternatives price differently:

• Data platforms (ZoomInfo, Clearbit). Annual licenses typically run $15,000 to $50,000+, and you still do the cleaning work yourself. The license also expires; per our comparison of People Data Labs vs ZoomInfo, most platforms require you to delete their data when you cancel.
• Traditional data agencies. Quoted per project like us, but built on offshore manual labor, so timelines stretch to weeks and per-record costs run higher.
• Doing it in-house. Free on paper. In practice it's your ops hire spending a quarter of their week in spreadsheets.

One more difference worth naming: the cleaned file is yours. No subscription, no deletion clause, no renewal conversation.

What Are Data Hygiene Best Practices?

A cleanup without a maintenance plan buys you about six months. If you want the database to stay clean, five habits do most of the work:

• Validate at the point of entry. Verify emails and standardize fields when a record is created, before bad data spreads into workflows and reports.
• Dedupe on a schedule. Quarterly for most teams. Monthly if you're importing lists or running events.
• Normalize titles and picklists. Free-text fields drift. Controlled values keep segmentation and routing working.
• Re-verify before big sends. Bounce rates above 2% start hurting deliverability, so check any list that's been sitting for more than a quarter.
• Assign an owner. Databases without a named owner degrade fastest. Someone has to be accountable for the standard.

Teams that don't want to staff this internally hand it to our ongoing maintenance service: weekly validation, new prospect alerts, quarterly deep cleans.

Where Data Cleaning Meets Data Analysis

Every analysis inherits the quality of the data underneath it. Win-rate reports, territory models, and ICP studies all fall apart when a third of the input records are duplicated or stale. So we treat cleaning as step one of analysis, and for clients who want the second step we run it too: our ICP analysis takes a cleaned customer list and tells you which segments close fastest and where your next accounts look like your best ones.

Do you need both? If the question you're trying to answer is "who should we sell to next," yes. If you only need the CRM to stop embarrassing your reps, cleaning alone gets you there.

Do You Work With Teams Outside the US?

Yes. Delivery is a file exchange, so geography barely matters. We work with US companies primarily, plus teams in the UK, Canada, and Australia. UK and Australian clients usually find us searching for "data cleansing services." Same service, different spelling. The one practical difference is source coverage: our contact and firmographic sources are deepest for North American companies, and we'll tell you upfront if your target market thins out our match rates.

Common Questions About Data Hygiene Services