Send us the data
Share a sample spreadsheet, CSV or describe the project. For many projects, a representative sample is enough to begin scoping.
How it works
Send us the data.
We’ll take it from there.
Salesbroom cleans business data for RevOps, marketing and sales operations teams. Every project starts with a human project manager who learns what you have, what needs to change, and what the finished dataset should look like.
Get an EstimateExperience
A process built from years of data work.
Over thousands of projects, one thing has remained consistent: the quality of the finished data depends on getting the rules right before the work begins. That is why every Salesbroom project starts with a human project manager. Your project manager learns the data, defines the rules with you, oversees the work and stays accountable through delivery.
Rules first
A project manager starts with the rules.
Data cleaning is not just running software against a file. What counts as a duplicate? Which record survives? How should company names be structured? What belongs in the address field? How should phone numbers, names, titles and email fields be formatted? Your Salesbroom project manager works through those decisions with you before the project begins.
Define the rules once.
Apply them consistently.
Apply them consistently.
The process
Four clear steps.
Talk with your project manager
We review the data, scope the work, identify exceptions, and define the dedupe or standardization rules.
We clean the dataset
The Salesbroom team applies the agreed rules using the right combination of human review, processing logic, software tools and AI-assisted workflows. AI stays in the background.
Get the finished file
Your project manager oversees quality control and delivery. We return the cleaned dataset in the agreed structure.
Project call
What we define together.
What constitutes a duplicate
Which fields drive matching
Which record survives
How conflicting values are handled
Company-name and legal-entity structure
Address formatting
Phone-number formatting
Contact name and title structure
Business vs. personal email treatment
Output format and timing
Quality control
Finished means it follows the rules.
Cleaning data is only useful if the finished file follows the rules we agreed on. Salesbroom reviews the work against the project requirements before delivery. Where ambiguous records require judgment, they are handled according to the agreed process rather than silently forced into a format that may be wrong.
Tools and process
The tools have changed. The process still matters.
Salesbroom has used software and automation as part of data work for years. Today, that toolkit includes AI. But software does not decide what your data should mean. Your project manager works with you to establish the rules. Technology helps us execute them efficiently.
Human project managers. AI in the background.
A service, not software
Nothing for you to install.
Salesbroom is a service, not a software product. There is nothing for your team to learn, configure or integrate before we can begin working on a file-based data project. Send us the data. Define the rules with your project manager. We do the work.
Have a data problem?
Clean it up. Make it work.
Tell us what you are working with and talk with a Salesbroom project manager.