Transactional email API
Tracks spam complaints by registering IPs and providing feedback loops
Groups IPs into pools and commands pool sending based on rules, so developers can control which IPs to send from
Supports custom email tracking to follow opens, clicks, bounces, and spam complaints, and provides a log so developers can filter data based on user information, timestamp, or other pre-defined criteria
Automates and merges email tags based on email sender or template used and supports split testing so teams can optimize and personalize engagement
Supports white labeling and custom sending options by automating actions without adjusting code
How Mandrill works
If you want to get customer data out of Mandrill and into your data warehouse there are a few options. Most people end up building a custom ETL pipeline that pulls from the Mandrill API on a regular basis, but building the pipeline also means handling its maintenance over time. The “build it” option gets more complex if you want to stream email events like deliver, click, or open in realtime. There are also expensive enterprise ETL tools and open source options, but those usually still require a lot of planning and configuration to get the data you want into and out of Mandrill in the format you want it. All of the options can be very time consuming because of the real-time nature of transactional email— you’ll need to build a repeatable upload process for events to be sent into Mandrill as they happen, or else a custom ETL pipeline.
Get more out of Mandrill with Segment
When you use Segment to ETL Mandrill data into your data warehouse, data transfer is handled automatically. Segment will sync all data from Mandrill in realtime. That data is transformed into a clean SQL format ready for analysis and loaded into your warehouse based on your sync schedule. Getting the Mandrill source set up on Segment doesn’t require any coding or configuration. All you need to do is paste a custom Segment URL into your Mandrill Webhooks settings so Segment can receive realtime data, and that’s it! It’s a pretty stark difference to custom building an ETL pipeline as an alternative.