Data cleaning for CRM imports
Comparison
Looking for an easier alternative to OpenRefine?
OpenRefine is a genuinely great tool, free, powerful, and, like Sift, it runs locally on your own machine so your data never leaves it. It is the Swiss Army knife of messy-data cleanup. But if your actual job is narrower, get a contact list ready for a CRM import, OpenRefine can be more than you need: it wants a Java install and a real learning curve first. Sift is the scalpel: nothing to install, and built for that one job. Here is an honest split of when each one wins.
Clean your list in Sift, free →
What OpenRefine is great at
Credit where it is due. OpenRefine is a powerful, general-purpose data-wrangling workbench, and for open-ended cleanup it is hard to beat. It has faceting to slice a column and see every distinct value, clustering to group near-identical entries, reconciliation to match your rows against external databases like Wikidata, and GREL scripting for arbitrary transforms you write yourself. If you do not know in advance what shape your data will need, that flexibility is exactly the point.
The cost of that power is setup and a learning curve. OpenRefine needs a Java runtime and a download before you can open your first file, and its faceting, clustering, and expression language take time to learn. For a one-off contact list headed into a CRM, that can be a lot of tool for the task.
Where Sift is simpler
Sift does not try to be a general-purpose workbench. It is opinionated for one job: getting a contact list import-ready. There is nothing to install, you drop a CSV or Excel file into a browser tab and start, and every step is aimed at the specific problems a CRM import throws:
- Dedupe with a golden record. Exact and fuzzy matching on email, phone, or a name-and-company fingerprint, merging duplicates into one record with survivorship rules instead of just deleting rows.
- Normalize the fields a CRM cares about. Phones to E.164 style, countries to a consistent form, US, UK, and Canadian postcodes, plus trim, name-safe casing, email repair, mojibake, and dates.
- Map to a CRM template and pre-flight the import. HubSpot, Salesforce, Pipedrive, Dynamics 365, Zoho, or Mailchimp, with required fields, types, and allowed values checked before you import.
Every change is shown as a before/after diff you approve, and you can save the whole sequence as a reusable pipeline for next time.
The same job in Sift
- Drop the file in. Sift profiles every column in your browser; nothing is uploaded, no install.
- Approve the cleanups with a before/after diff: trim, name-safe casing, email repair, mojibake and date fixes, phone normalization to E.164, countries and postcodes standardized.
- Dedupe fuzzily, matching on email, phone, or a name-and-company fingerprint, and merge duplicates into one golden record with survivorship rules.
- Map to your CRM's template (HubSpot, Salesforce, Pipedrive, Dynamics 365, Zoho, Mailchimp) and run the import pre-flight: required fields, types, and allowed values, flagged before you import.
- Export a clean file, an accounts file, a change log, and a hygiene report, plus a "needs your eyes" list for the rows only you can decide.
When OpenRefine is the better tool
- You need arbitrary, complex transforms written as expressions; Sift is deterministic and has no scripting language.
- You want to reconcile against external data like Wikidata or another database; Sift does no external-data reconciliation.
- You are doing large-scale faceting or clustering to explore an unfamiliar dataset, not preparing a known contact list.
- The work is scripted or repeated with GREL in ways that go beyond a fixed clean-dedupe-map-check pipeline.
The honest read: OpenRefine is the better general-purpose tool, and Sift is the faster route for the specific job of getting a contact list import-ready.