“Garbage in, garbage out” is a saying used to describe the need to ensure clean data goes into a system so that clean data can be reported out. It even has its own wikipedia page.

The reality though is that its hard to ensure that everything going into a CRM is clean, especially when potentially dozens of people are adding data to it regularly.  Things like adding contacts and companies often leads to having duplicate records, which adds to data sprawl and difficulty in reporting fully or accurately.

Users of generic CRMs like Salesforce have the option of leveraging 3rd party tools to help with this problem. You might think: “this is great!, look at all the solutions I can use.” The vast majority of these options though are at an additional license charge, and even requires you know technical specifics like the version of Salesforce you firm uses to be able to find a compatible product.

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Generic CRMs like Salesforce require 3rd party tools to help tackle the problem of duplicate records. Sorting through the options can be overwhelming – including knowing which version of the system you have. 

DealCloud is different- and no third party tools required. What we offer is a multi-faceted approach to solving the duplicate dilemma. First, during the setup process, our professional services team can work with you to collect your data from various sources, including existing systems, spreadsheets or even outlook contacts, to de-duplicate records and normalize them upon initial upload to the system.

Next, we can turn on a duplicate catcher for different inputs to the system such as contacts or deals. Based on a unique field, such as a contacts email address, or a deals name, it can flag a duplicate before its created. This step is optional to turn on as some firms prefer to let users create whatever entries they want and have a data steward or central administrator manage the process as to not prevent people from adding data to the system.

De-Dupe Catcher
DealCloud duplicate catcher happens upon creation or entry of new items into the system. 

The duplicate check step is part of the creation flow, you can even switch to edit the other entry rather than needing to back out or start over.

Lastly, and my favorite option, is an algorithmic solution built right into the DealCloud platform. All entries like contacts, companies, and deals can have their own de-duplication preferences.

De-Duplication Preferences
De-duplication preferences in DealCloud.

De-duplication preferences are rules that you can set to identify duplicates. A person named Joseph or Joe will not be found using traditional tools, so DealCloud lets you say things like if 80% of a persons’ name is the same, and they have the same phone number, flag this as a possible duplicate.

For Companies, you might have 2 records: ABC Company and ABC Company, Inc., just trying to flag it on its name won’t work. The same holds true for New York and New York City, and the United States vs the United States of America, etc.

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DealCloud lets you establish rules in the database that flag duplicates for your review. It can even handle differences in peoples name like Joseph vs Joe.

By establishing the rules and fields that are important to you, the system lets you flag and potentially merge duplicate records without preventing people from adding data to the system which could have a negative impact on user adoption.

With DealCloud, even if “garbage” goes in, garbage doesn’t have to come out.

 

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