Braze Announcements


Activate Customer Data from Amazon Redshift with Cloud Data Ingestion

Brandon Hughes By Brandon Hughes Mar 2, 2023

As customer expectations evolve, the data ecosystem surrounding customer engagement is changing, too. But this shift can pose a big challenge for modern brands as they work to make sense of their customer data. With so many touch points out there (e.g. devices, platforms, channels, and more), understanding what data you have at your disposal and how to organize and act on it effectively takes thought, care, and the right technologies. One key technology for effective data activation? The cloud data warehouse.

Thankfully, the Braze customer engagement platform is built with data flexibility in mind, making it easier than ever before to activate your customer data to support your customer engagement efforts. Braze Cloud Data Ingestion (CDI), which we launched last fall at our FORGE 22 conference, allows you to quickly collect, process, and unlock value from your data by creating a seamless link between selected data warehouses and your customer engagement platform. Building on that foundation, we’re pleased to announce a new CDI integration with our Braze Alloys technology partner, Amazon Redshift, designed to support even more flexible data management and activation.

Understanding Cloud Data Ingestion

This new integration allows brands to directly integrate data from Amazon Redshift into the Braze platform for further segmentation, message targeting, and personalization. CDI with Redshift lets brands sync data between the platforms on the schedule of their choice; when a sync runs, Braze will connect to Redshift, pulling in new data and updating relevant user profiles within Braze, supporting more relevant, effective customer experiences.

Because the Braze data model is built to support arrays and nested attributes, brands can easily sync both structured and unstructured data from any Braze-supported source, avoiding the headaches that come with building out cumbersome data pipelines. That puts more data into the hands of marketers faster, allowing them to manage campaigns thoughtfully and leverage data in personalization tools to support relevant, value-add experiences for consumers across the full range of devices, platforms, and channels.

Connecting Braze and Amazon RedShift Via Cloud Data Ingestion

This new integration is a pre-built, direct connection that’s designed to be turnkey in nature. Your organization should be able to easily set it up right within the Braze dashboard in just a few simple steps—no complex coding required. The process is as follows:

  1. Set up data table parameters in your Amazon Redshift instance

  2. Navigate to the Redshift page in the Braze dashboard, under the “Technology Partners” section

  3. Begin a new import sync between the two systems

  4. Provide user authentication data from both Braze and Redshift

  5. Set a name, data type, and frequency for your Braze/Redshift integration

  6. Run a quick test to ensure that the data in question is all in order

Once you’ve got that set up, you’re ready to start taking advantage of your data from Redshift to support nuanced user personalization and to inform rich, responsive campaigns across the full range of digital messaging channels (e.g. email, SMS, and mobile and web channels).

Key Use Cases That Braze and Amazon RedShift Make Possible

Curious how bringing together Braze and Amazon Redshift can help to support your customer relationships and make it easier to meet your business goals? Check out these notable use cases to see how the new integration can help you get a better handle on your data and support your customer engagement efforts:

1. Data-driven personalization

By connecting Braze and Redshift via CDI, brands can aggregate data from a wide range of different touch points in a single location, then take effective, targeted action on that data to support better customer experiences.

What does that look like? Imagine that you’re a gaming publisher. This integration allows you to aggregate all of your game purchase data from different platforms (e.g. in store, online, in-console marketplaces, etc.) in Redshift. Then, using that purchase data, you can track all purchases across your digital properties and leverage Braze to carry out targeted messaging to your “recent purchasers” and “biggest spenders” audience segments.

2. Easy, scalable data syncing to live customer profiles

By connecting Braze and Redshift via CDI, you can significantly decrease the developer support needed to sync information between your data warehouse and your customer engagement platform, boosting flexibility and allowing your marketing team to move fast without overburdening your engineering team.

What does that look like? Imagine that you’re a streaming service. Once you enable CDI and connect Braze to Redshift, the integration allows you to update your customers’ profiles based on data within Redshift. In fact, you can easily sync even massive object arrays across customers in a matter of minutes, reducing the need for engineering support to carry out your customer engagement program.

3. Thoughtful recommendation powered by Redshift insights

By connecting Braze and Redshift via CDI, brands can get more out of their data warehouse by better utilizing its robust capabilities with transforming customer data.

What does that look like? Imagine that you’re a retail marketplace. This integration allows you to build robust recommendation engines in Redshift that are based on your customer’s past purchase data. This engine can be leveraged to create custom attributes on what customers are most likely to purchase based on the different categories of items they bought in the past. That, in turn, allows marketers to utilize that custom attribute to serve up personalized promotions for other items to purchase within that catalog, supporting smarter suggestions and more personalized experiences.

Final Thoughts

Looking to dig a little deeper into our new Cloud Data Ingestion integration with Amazon Redshift? Check out our documentation and get started today!


Brandon Hughes

Brandon Hughes

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