Services
Marketing
Marketing Database Cleanup
Clean and organize your CRM data to improve segmentation, automation, and campaign performance.
Foundation
The teams we work with before a database cleanup aren't negligent. They know the data is messy. What they don't know is how bad it actually is, which fields are causing the most damage, or whether a cleanup will hold. Most have tried fixing it before, usually during a tool migration or a rebranding push, and watched it degrade back to its original state within a year. By the time they come to us, the database has become something the marketing team works around rather than works with.
Most CRM databases grow faster than the teams managing them. Duplicates accumulate with every import. Fields that were filled in three different ways during onboarding never get standardized. Contacts from campaigns two years ago are still active in workflows they should have exited. By the time someone tries to segment for a real campaign, the data fights back.
The downstream effects are predictable: email deliverability drops because 15% of your list is bad addresses. Automation fires on the wrong contacts because lifecycle stages are inconsistent. Reporting numbers look different depending on who pulls the report. Sales ignores CRM data because they don't trust it.
The root cause is almost never negligence. It's that nobody was assigned the job of keeping the database clean, and cleaning it after the fact is expensive enough that it keeps getting postponed.
What we do
We extract your full contact and company database and run it through a structured audit. That means checking field fill rates, identifying duplicate records and the rules that create them, mapping which properties are actually used in reporting versus which were created and abandoned, and flagging import practices that keep introducing noise.
The output is a prioritized cleanup plan: what to fix now because it's actively hurting performance, what to fix in the next 90 days, and what governance rules to put in place so the database doesn't degrade again.
For context on what this type of analysis typically surfaces, read what dirty data actually costs.
Deliverable
You receive a database health assessment with specific findings, not a generic checklist. It includes a duplicate audit with merge recommendations, a property-by-property fill rate and usage analysis, a list of risky import sources and how to handle them, and a set of governance standards your team can actually maintain.
Outcome
A database your team trusts. Segmentation that works. Automation that fires on the right contacts. Reports that match across teams.
The less obvious outcome: your team stops adding workarounds to compensate for bad data, which is where a surprising amount of time goes in most marketing operations roles.
How Veloxa Stopped a Leaky Funnel and Grew Conversions by 22% — recovered $1.2M in pipeline, cut CPL by 40%, and grew conversions by 22%.
Best Fit
This is for teams where the CRM has been running for at least a year and nobody has done a structured cleanup. You probably already know there are problems. You're here because you want to understand exactly what they are and get a plan to fix them, not a list of best practices you already know.