Enriched and deduplicated data for everyday benefit



When he first joined Momentum, Bryon Main, Chief Operation Officer, inherited a database full of duplicate and incomplete records. He shared some examples of this with us: “a lot of times you will see that email addresses are the same, but on different records. The first name and last name are different, but the email address is the same.”

In order to work more efficiently, he needed a way to clean up their database and improve overall data hygiene while successfully merging fields together. “When coming into this organization, there was a database in place with a lot of information that was entered in by a variety of users. I wanted to avoid the scenario where all of a sudden we were merging duplicate data and losing valuable data through the process,” Maine explained.

After trying Salesforce’s native deduplication feature, Main found that the duplicate prevention didn’t suit Momentum’s needs because it couldn’t be done in bulk only real-time.

“As an admin for salesforce.com, I wanted to be in control of being able to mass merge accounts, contacts, leads, and opportunities, so the power of Salesforce Native Deduplication itself was not enough for our team,” said Main.

But he quickly realized this was only half the battle. Momentum needed a flexible data quality platform that prioritized access, cloud access, and ability to access the data from any location from any site.

“To find a tool that was able to not only enrich that data, but to dedupe it that day was a tremendous help to the organization and something that we benefit through everyday.”

Bryon Main

Chief Operation Officer at Momentum


As Main looked at third party vendors to solve their duplication and data quality issues, he quickly found that other vendors lacked the flexibility to execute their data cleansing campaigns. After trial and error, Momentum decided on OperationsOS.

Main was particularly excited about the deduplication matching rules built into OperationsOS Cleanse and its ability to take legacy information in the database and make sure that those fields survive when merging records, so no valuable data is lost.
The ability to set up the way objects are merged–especially custom objects— has become a huge time saver for Bryon–helping to quickly resolve situations in which multiple users create custom objects under the same name.

Of the many features Main has leveraged in the OperationsOS platform–from creating updates or deleting records in bulk, to importing lists or deduplicating records, he has been most pleasantly surprised by how much his team uses the Normalization feature to clean up records and standardize fields.

“To find a tool that was able to not only enrich that data, but to dedupe it that day was a tremendous help to the organization and something that we benefit through everyday,” Brian shared.

He added, “as the head of a conference organization that is frequently printing badges that people wear at conferences, to have the ability to have standard title formats on their badges has really improved the quality of our data.”

The Results

Momentum Events leveraged batch deduplication, list import duplicate prevention, and custom surviving field value rules all built into OperationsOS Cleanse to eliminate the duplicate record problem they were facing without deleting potentially useful information. Once Momentum Events deduped its database, they set up duplicate protection going forward.

Speaking to the benefits of scheduled deduplication and the future of duplicate prevention at Momentum, “you can schedule Salesforce APIs to occur over the weekend when no one else is using Salesforce. So it’s not only still getting the deduplication done, but it’s being efficient with your Salesforce APIs which can typically be a headache for Salesforce users,” explained Main.

Momentum Events continues to use OperationsOS to maintain clean data with our suite of data quality tools such as List Import Duplicate Prevention, Custom Object Deduplication, Mass Update, and Mass Delete, as well as Normalization.

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