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Data Cleansing - Company Names and Emails

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    Data Cleansing - Company Names and Emails

    Recently we found out that there we're merge rules in our crm that were incorrectly pairing data on mismatched accounts. An example is that one of the merge functions merged companies based on street address. For example: if an account existed in salesforce "xyz logistics" and who's office was located at 123 main st., when importing a new piece of data like information for "abc printing" it would take the owner of "abc printing" and merge them to "xyz logistics" meaning that the owner of "abc printing" now is 1 of 2 owner contacts on the "xyz logistics" account. We have been working to clean this in excel by comparing original data to the exported lists from salesforce.

    We're looking for a way to decouple the data in a streamlined process by comparing the Account name column with the company name column, and further (if possible) the email and domain with the name of the owner/company but again the biggest issue is just matching the company and account name at scale and being able to see the results either highlighted or in a way that can filter all of the ones without fuzzy/75% matches. It's complicated because there are some that are close matches and you can tell are the same companies because it's something like "xyz warehousing and logistics services" "xyz logistics" and others (which we're trying to find) that are completely mismatched.

    Would a pivot table be best? Vlookup? or some very long formula?

    Any and all help is greatly appreciated!!

    -Sean
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  2. #2
    Forum Moderator Glenn Kennedy's Avatar
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    Re: Data Cleansing - Company Names and Emails

    Please repost your sheet showing some expected results, manually calculated (as indicated in the yellow banner - top of page).
    Glenn



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