Applications: A Technical Overview
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Applications: A Technical Overview

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Article Summary

Reverse ETL (Data Activation)

Dataddo supports sending data to SaaS apps. This feature is known as Reverse ETL or Data Activation.

Reverse ETL is the copying of enriched data from a data warehouse into business applications like CRMs, finance management systems, and marketing tools. This gives teams that spend most of their time in these applications immediate, in-context insights, and eliminates the data warehouse as a data silo.

Benefits:

  • Completely eliminates data silos
  • Improves data accuracy
  • Enables proprietary company data to be shared across departments
  • Eliminates the need for separate dashboards

Example 1: Marketing

Customer behavior data synced to the main database can be routed to a CRM like HubSpot, or an in-app messaging tool like Intercom. As a result, customer marketing teams can configure any kind of communication to trigger in response to any customer behavior in an app or on a website.

For example, when a customer starts using a new feature, or if they spend a certain amount of time examining that feature without successfully using it, an email or in-app communication will be triggered automatically to help them along their way.

Example 2: Sales

Any metric that involves first-party data, like lifetime value or different kinds of customer scores, can be synced regularly to a CRM. This allows sales reps, for example, to pull up the profile of the customer or lead they are currently talking to and have a clear picture of their potential value to the company, risk of churn, or most recent in-app behavior.

Example 3: Product Management

Thanks to customer behavior data, product managers can can configure feedback prompts to fire in response to any kind of in-app behavior (similar to marketing departments). This greatly increases the chances that customers will actually take the time to give feedback.

Any data, such as data on feature requests, can also be sent back to their CRM, making it easier to prioritize the implementation of new features.

For more details on data integration types, see our blog.



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