Data Cleanser
Stratus Cloud Solutions Stratus Cloud Solutions
Role

Data Cleanser for revenue operations

Duplicates quietly corrupt the numbers RevOps is accountable for — pipeline, forecast, routing, and attribution. Data Cleanser collapses them into one record per customer so every report and rule reads from the same truth, natively and without an export.

RevOps lives in the reports. When the same account or lead exists two or three times, open pipeline scatters across the copies, the forecast double-counts or under-counts, leads route to the wrong owner, and attribution credits the wrong touch. You cannot tune routing or trust a forecast built on duplicated data. Data Cleanser consolidates those records on-platform — on rules you set — so the system of record matches reality before you report on it.

The counts the app surfaces as you work — duplicate groups waiting on review, records merged, and scans running and scheduled — so the cleanup behind your reporting is itself measurable.
The challenge

What duplicates do to the numbers

Pipeline split across copies

When one account exists twice, open opportunities and ARR scatter across both records — so the forecast double-counts, under-counts, or simply cannot be trusted.

Routing and assignment misfire

Lead-to-account matching, territory rules, and round-robin all key on a clean record. Duplicates send the same buyer to two reps — or to the wrong one entirely.

Reporting no one believes

Dashboards built on duplicated records inflate counts and split history, so every number invites a "but is that real?" — and the data gets worked around instead of trusted.

How Data Cleanser helps

One record per customer, numbers you can forecast on

One record per customer, by rules you set

Per-object scenarios match on normalized email, company, and domain so the duplicates that split your pipeline collapse into a single account, contact, or lead — and tiebreaker fields keep genuinely different records apart.

Merge without losing the history

Field-level survivorship keeps the right owner, stage, and source, and native Salesforce merge re-parents opportunities, activities, and related records to the survivor — so pipeline and attribution consolidate instead of disappearing.

A baseline you can forecast on

With one record per customer, rollups, routing, and dashboards read from the same truth — and mass merge clears the historical backlog in controlled passes so the reporting baseline is clean before you tune anything on top of it.

Outcomes

What clean data gives revenue operations

  • Pipeline and ARR that roll up to one record per customer
  • Forecasts that are not split or double-counted
  • Lead routing and territory rules that fire on clean data
  • Attribution credited to the right record
  • Dashboards the revenue team actually trusts
  • Historical backlogs cleared with mass merge in controlled passes
FAQ

Common questions

Duplicate accounts are splitting our pipeline and forecast. Can this fix it?

Yes. Match accounts on normalized name, domain, or billing fields, then merge so open opportunities and ARR consolidate onto one record. Native Salesforce merge re-parents the opportunities automatically, so the rollup reflects reality.

Will merging duplicates break lead routing or territory assignment?

It fixes it. Routing, lead-to-account matching, and territory rules all depend on a clean record — consolidating duplicates means a buyer maps to one account and one owner instead of scattering across copies. You set field-level survivorship so the right owner and territory win.

What happens to opportunity and activity history when records merge?

Merges use native Salesforce merge, so opportunities, activities, and related lists re-parent to the surviving record. History consolidates rather than disappears, which keeps attribution and pipeline reporting intact.

Can we clean the historical backlog, not just new duplicates?

Yes. Set master rules — oldest record, record owner, most related records — and mass-merge large backlogs in controlled passes, so your reporting baseline is clean before you tune routing or forecasting on top of it.

Does any of our pipeline data leave Salesforce?

No. Data Cleanser is 100% native — no export, no middleware, no third-party data processor. Matching and merging run inside your org and inherit your sharing and field-level security.

Which records can it consolidate?

Leads, Contacts, Accounts — including Person Accounts. Cross-object matching also spots a Lead that already exists as a Contact and supports convert-or-merge so the relationship stays together.

See it on your own data

Start a free limited trial in your own Salesforce org, or book a live demo with someone who builds the app.

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See it in your own org

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