Sync data from
Amazon Athena to Iterable
Connect your data from Amazon Athena to Iterable with Hightouch. No APIs, no months-long implementations, and no CSV files. Just your data synced forever.
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Integrate your data in 3 easy steps
Add your source and destination
Connect to 15+ data sources, like Amazon Athena, and 140+ destinations, like Iterable.
Define your model
Use SQL or select an existing dbt or Looker model.
Sync your data
Define how fields from your model map to Iterable, and start syncing.
Model your Amazon Athena data using any of these methods
dbt Model Selector
Sync directly with your dbt models saved in a git.
Query using looks. Hightouch turns your look into SQL and will pull from your source.
Create and Edit SQL from your browser. Hightouch supports SQL native to Amazon Athena.
Select available tables and sheets from Amazon Athena and sync using existing views without having to write SQL.
For less technical users, pass traits and audiences from Amazon Athena using our visual segmentation builder.
Where can you sync your Amazon Athena data in Iterable
Every email address you have in Iterable is a user or subscriber/contact. You can use Hightouch to update user information or delete, forget, or unforget users.
An event is an action a user takes on your website or app. They are specific to your business. Use Hightouch to send shopping cart, purchase, or custom events to Iterable.
When sending messages to your users, it's almost always necessary to include information about your organization's products, places, events, or services. Use Hightouch to send this information directly to Iterable.
Iterable's segmentation tool allows you to segment across all of your subscribers and to make static or dynamic lists. Use Hightouch to add users to lists to create highly targeted customer segments, so you can deliver the most relevant marketing messages.
Why is it valuable to sync Amazon Athena data to Iterable?
Lifecycle marketing platforms like Iterable are built on omnichannel experiences and multiple touch points. They allow marketers to experiment and iterate at a moment's notice. However, to build personalized experiences for your customers, you first need access to the rich behavioral data in your data warehouse.
This might include data models built around unique objects in your business like workspaces, subscriptions, playlists, or even custom audiences your data team has defined based on core metrics like items in cart, pages viewed, average order value, time spent in-app, etc.
To truly convert new users and retain existing customers, you need to build customized experiences that feel unique to each user. Usually, this includes sending custom emails, SMS messages, push notifications, or even web notifications.
For example, if you want to encourage users who abandoned their shopping cart in the last seven days to complete their purchase, you might want to send an email letting them know your stock is running low. Maybe you want to target new users with a special offer through an in-app/on-browser notification, or perhaps you simply want to send an SMS notifying your customers that their order has shipped.
Either way, the only complete 360-degree view of your customer lives in your warehouse. Your lifecycle marketing tool is only as good as the data you give it. If you want to offer the best possible experience to your customers, you need to take advantage of the data in your warehouse.
Why should you use reverse ETL to connect Amazon Athena and Iterable data?
Whenever your marketing team wants to launch a new campaign, the typical process is to request a specific data set from your data team (e.g., can you give a list of every user who's visited our pricing page over the last seven days?) One-off requests like these are frequent, and each one pulls away from high-value work your data team could be doing.
To facilitate this, your data engineers must download ad-hoc CSV files so your marketing team can upload that data into Iterable. Alternatively, your data team might build and maintain custom pipelines to consistently ingest that data into Iterable. The problem is CSV files aren't fresh, and data pipelines are prone to failure because integrating with third-party APIs is hard.
Ultimately, your marketers want to self-serve, and that's only possible with Reverse ETL. With Hightouch, you can leverage your existing data models (e.g., lifetime value, last-login date, workspaces, annual recurring revenue, etc.) in your warehouse and sync that data directly to fields in Iterable. You can schedule your syncs to run sequentially or define a set cadence (e.g., running your syncs while your marketing campaign is in progress.)
Hightouch has a visual audience builder so your marketers can self-serve and build custom audiences using the parameters your data team has set. If any of your rows fail, Hightouch will automatically retry them later in the next sync. You can easily view all of your API payload requests/responses in a live debugger, and your sync logs can be written back directly to Snowflake. Ultimately your lifecycle marketing tool is only as good as the data you give it.
Sync data about users and accounts into Iterable to build hyper-personalized campaigns
Automatically update your Iterable segments with fresh data from your warehouse
Deliver better experiences by bringing in data from other customer touchpoints into Iterable
Monitor campaign revenue from purchases or cart-additions
About Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.Learn more about Amazon Athena
Iterable is an integrated, cross-channel platform—built for marketers, trusted by engineers, designed with intelligence.Learn more about Iterable
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