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Leverage Twilio Segment, LiveRamp, and Snowflake to create 'Golden Profiles,' enabling precise targeting and improved return on ad spend in a changing privacy-first, cookie-less marketing world. This guide offers a step-by-step process for unifying first-party data for richer customer insights and streamlined audience onboarding.

In this recipe, you’ll set up rETL to automatically pull in both backfill customer data and events from your warehouse to help complete your identity graph and provide a holistic view of your customer’s journey over an extended period of time.

In this recipe, you’ll set up reverse ETL to automatically pull in conversion events that originated from a Google Ad that are locked away in a Snowflake table or view. You’ll learn how to use Twilio Segment Reverse ETL to gain a more accurate return on ad spend without having to manually upload files to Google. This will allow you to capture the extended conversion value* (see a further description of this concept below) when a customer leaves your app or site to complete a conversion.

The nature of iterative development cycles is that you find yourself at some point with multiple systems that need to be integrated. Maybe you built your customer database in Snowflake and your frontend applications are integrated with it, but now that your organization has grown, you’re investing in a CRM like Salesforce. You could eliminate the database and try to sync everything directly to Salesforce, but that’s probably a huge lift. You can’t just leave the systems separate, because having two sources of truth is not a good idea; you’ll introduce endless bugs and mismatches that affect your organization’s reputation and effectiveness. If your data warehouse could sync with your Salesforce, though… you’d be able to run both without the worry about divergent databases! In this recipe we’ll explore how to set up this synchronization so that your systems don’t diverge, and you don’t have extra work to keep them that way.