Last month, we announced the launch of our new cross-object dataset comparison feature. If you missed out on the announcement, you can read all about the new time-saving feature here. In July we evolved cross-object comparison and added a few minor features.
So, without further ado here’s what we’ve added in this month’s release…
Lead to Contact and Lead to Account Conversion
We’ve extended cross-object dataset comparison functionality to include an easy way for users to convert leads that were identified as existing contacts and/or accounts.
The Lead converted to a contact will be associated with the contact’s account and when you convert a lead to the matching account a new contact will be automatically created.
Append Field Data During Conversion
If the master record (Contact or Account) has no value in a field, DataGroomr’s convert will automatically take values from the most recently modified lead. Review dialog also includes inline editing support, allowing you to easily update fields during conversion.
We suggest to start off with deduping leads, then merge duplicate contacts and accounts. Then use the cross-object comparison and convert duplicate leads to contacts and lastly, convert duplicate leads to accounts.
Multi Select and Reference Fields Support
We’ve added support for multi-select and reference fields for modifications in Review dialog. Note, that in order to enable reference fields in the existing datasets created before July release you need to resave the dataset by simply opening the dataset configuration and clicking Save for the changes to take effect.
Machine Learning Models Improvements
DataGroomr’s core matching algorithm has been enhanced to support more data types and understand text values more intelligently, for example it will automatically parse and compare company names, addresses and surnames. The best part is, you don’t have to do anything as it all happens behind the scenes.
In addition, newly created datasets will allow all fields to be either included or excluded from the duplicate analysis. Excluding certain fields may be useful if you want to narrow down matching criteria for specific purposes (for example for marketing automation software). If you want to exclude a field that is currently disabled in the dataset configuration simply recreate the dataset.
What’s Coming in the Next Release?
Unsurprisingly, we’ve already canvassed our customers to get a handle on what we should be prioritizing for the next release. Here’s what you can expect in August:
- Mass lead conversion – yes, you read that right! We’re further extending the lead conversion functionality so that you can mass convert leads to contacts.
- Export identified duplicate records from TRIMMR for backup and/or analysis.
As usual, please do not hesitate to reach out to us if you have any feature in mind that you’d like to see in DataGroomr.
Until next month, Trailblazers!