Use Cases

Unlock more valuable customer insights with Iterable


As customers continue to engage over time, it’s important to draw learnings from their engagements and use those learnings to improve the customer experience.

To do so, you need to be able to integrate engagement data across the systems you’re using for customer engagement, messaging, and analytics. In fact, BCG’s global digital marketing maturity survey has shown that companies that link all of their first-party data sources can generate double the incremental revenue from a single ad placement, communication, or outreach, and 1.5 times the improvement in cost efficiency over companies with limited data integration.

This use case walks through how you can use mParticle to integrate engagement data from Iterable to the rest of your first-party data set, and forward that data to the analytics tool(s) of your choice without any custom development.

Step 1: Collect engagement data into Iterable

When you have the Iterable SDK installed, behavior data is collected as events as users engage with experiences across different channels. Example events are email clicks, in-app opens, push uninstalls, and SMS bounces.

Step 2: Forward engagement data to mParticle

Using mParticle’s Iterable Feed integration, you can forward any data collected into Iterable to mParticle in real time without any custom development. Once this data is collected into mParticle, it is tied to deterministic customer profiles. This allows you to unify Iterable engagement data and cross-channel behavioral data already available in mParticle to a single identifier.

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Step 3: Forward engagement data downstream to your analytics system(s) of choice

With engagement data from Iterable collected into your mParticle workspace, mParticle’s 300+ server-side integrations make it easy to connect that data to downstream tools for further application. For this use case, you can connect engagement data, as well as any other data in your mParticle workspace, to product analytics tools, such as Amplitude and Mixpanel, or to data warehouses, such as Redshift, Snowflake, or BigQuery. To manage data governance and control costs, mParticle Data Filter allows you to specify exactly which events and attributes are forwarded to each system. While transferring this data may normally require the building of custom data pipelines, mParticle allows you to do so without any custom development.

Step 4: Unlock valuable insights

Report on engagement data forwarded from mParticle to unlock valuable insights such as which engagement channel your customers are most responsive to (email, push, SMS, etc.), which time of day your emails receive the most opens, or how successful your reminder emails are at driving customers to purchase. Use these insights to tweak your programs in Iterable and deliver better customer experiences.

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