Are your customers having to adopt expensive 3rd party identity solutions that are competing with your existing offerings?
Is your inability to deal with duplicate customers slowing down the onboarding of new customers?
When working with customer data, one of the core assumptions is that you can define the customer. However, in most organizations, any consolidation of customer data reveals a rash of duplicate touchpoints that the customer has had with the organization. So how do you deal with these crazy clone records? The solution is to conduct a deep comparative analysis between the records to uncover and tag the unique customers. In the past, this process was facilitated through a clunky data exchange process where the Identity Resolution processor would charge a boatload of money to have the data shipped to their data centers for processing the record sets. Snowflake has made some of the logistics of shipping the data a little easier, but even then customers are required to share their custody chain of data with a third party.
Truelty is designed to process unique records directly inside of Snowflake. This means that the client can leave the data where it has already been centralized, and the processing for unique customer ID can happen right there. The Truelty Deep Chain compute application is a highly tuned query generator that directly leverages Snowflake’s native asynchronous query capabilities to handle billions of records and trillions of comparisons within X Small warehouses.