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Datauntangler

No card required. The browser demo is free to use.

CRM data cleansing before the import, with an audit trail

CRM data cleansing is easiest on the export, not inside the CRM. Pull the contacts and accounts out as a CSV, merge the duplicates, standardize the fields, and import a file you can vouch for. That way nothing changes in the live system until you approve it.

In-browser your file never leaves your computer

Every row proposed to you before it is applied

CSV log of what you approved and rejected

Clean a file
01 Try it on this page

Load a messy sample and watch it work

The same engine described below, running on your own machine. Nothing is uploaded and nothing is applied until you approve it.

1. Load a file

Your file is read on your own machine. Nothing is uploaded, so nothing can leak.

Or start from a messy sample

Status

Loading the sample file.

File: CRM contact export

Rows

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Columns

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Changes

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Duplicate rows

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Date formats

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Blank emails

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Load a file to see the diff

Drop a CSV or pick one of the messy samples. Every proposed change appears here as a line you approve or reject.

02 About crm data cleansing

Why the export is the right place to work

Cleaning inside a CRM means editing live records that other people are looking at, with automation and workflows firing on every change. A mistake there is visible immediately and hard to unwind.

On an export you can be careful. You see every proposed change at once, compare rows side by side, and produce a list of what will happen before it happens. That list is also what makes the change acceptable to the account owners whose records you are merging.

A migration checklist

Export contacts and accounts separately

Keep the relationship column so you can rejoin them afterwards.

Clean the fields before matching

Trimming and case folding alone will collapse a surprising number of duplicates.

Review the close matches by hand

Same email is safe to accept quickly. Close name and company matches deserve a look.

Keep the audit log

Attach it to the migration ticket. It is the answer to the first question anyone asks after go live.

Import into a sandbox first

Then compare counts before touching production.

The conversation with the sales team

Merging accounts touches ownership, quota and commission, which is why sales teams resist a cleanup they cannot see. Handing them a list of the exact merges, with the row that was kept and the reason for the match, turns an argument into a review. The matching that produces that list is fuzzy matching, grouped into records by entity resolution, and the Salesforce specific walkthrough is Salesforce deduplication.

03 Cleaning inside the CRM

Why cleaning it in place is the harder way to do it

Working inside the system feels direct. It is also where the changes become permanent before anyone else has seen them.

Salesforce deduplication

The merge happens on the click

Inside the CRM the merge is applied as you confirm it, and the record it overwrote is not somewhere the ops team can go and read afterwards.

Objects are cleaned separately

Contacts and accounts get their own runs under their own rules, so the two never quite agree about which company a person belongs to.

The sales team hears about it later

The first anyone knows of a bad merge is an account missing from a pipeline review, weeks after the run that removed it.

What working on the export gives you

Every merge is a proposal you can circulate before it is applied, the audit log goes with it, and the import lands in a sandbox first.

04 Before you run it

Questions about crm data cleansing

Do you connect to my CRM directly?
Not in the browser demo, which works on the file you export. CRM connectors for Salesforce and HubSpot are part of the Team plan and above.
Can I clean accounts and contacts together?
Clean them as separate files and rejoin on your relationship column. Matching works better when each file has one kind of entity in it.
05 What it costs

Plans for when the file is bigger than the demo

Yearly billing is two months free. There is no free plan, and no card is needed to use the browser demo above.

Yearly billing is two months free.

Switch to yearly and two months are free.

Analyst

One ops person or analyst with files to clean.

$49$59/mo

Billed $590 a year Billed monthly

  • 50,000 rows a month
  • Files up to 25MB
  • 1 seat
  • Fuzzy matching and entity resolution
  • Reviewable diff and audit log export
  • 3 saved cleaning recipes
  • Email support

Team

Recommended

A RevOps or marketing ops team sharing the work.

$166$199/mo

Billed $1,990 a year Billed monthly

  • 250,000 rows a month
  • Files up to 100MB
  • 5 seats
  • Everything in Analyst
  • Unlimited saved recipes
  • Scheduled recurring cleans
  • CRM connectors (Salesforce, HubSpot)
  • Priority email support

Business

A data team cleaning for several departments.

$499$599/mo

Billed $5,990 a year Billed monthly

  • 1,500,000 rows a month
  • Files up to 500MB
  • 20 seats
  • Everything in Team
  • API access
  • Roles and permissions
  • Priority email support

Enterprise

A head of data who needs it defensible across the company.

Talk to sales

Custom terms, invoicing and PO

  • Unlimited rows and custom file sizes
  • Unlimited seats
  • Everything in Business
  • SSO (SAML / Okta)
  • Custom data retention
  • DPA on request
  • Named support contact
  • Invoicing and PO
  • Named onboarding

A row is one data line in a file you process, not counting the header. The browser demo is free to use and is not a plan: it reads CSV and TSV files up to 5MB on your own machine.

Related pages

Clean the file, and be able to show what you changed

Try the demo on your own CSV first. It runs in your browser, it costs nothing, and no card is required.

No card required. Your file never leaves your computer.

Clean a file