This page provides you with instructions on how to extract data from AppsFlyer and load it into Amazon S3. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is AppsFlyer?
AppsFlyer is an attribution stack for mobile marketers. It lets businesses attribute every install of their apps to the marketing campaign and media source that drove that install. It also provides an analytics dashboard that shows which users engage with an app, how they use it, and how much revenue they generate.
What is S3?
Amazon S3 (Simple Storage Service) provides cloud-based object storage through a web service interface. You can use S3 to store and retrieve any amount of data, at any time, from anywhere on the web. S3 objects, which may be structured in any way, are stored in resources called buckets.
Getting data out of AppsFlyer
AppsFlyer exposes data through its Pull API, which developers can use to extract information. Each API call, which is made in the form of an https query, must contain the user’s external API Authorization Key, as well as from and to dates that specify the date range of the data requested.
Additional parameters can request information like media source, currency, and specific fields. The parameters must be added to the https query – for example:
Each successful API query returns a CSV file of data that you can use as an import source to your data warehouse. The query you use will determine what fields you receive.
Loading data into Amazon S3
To upload files you must first create an S3 bucket. Once you have a bucket you can add an object to it. An object can be any kind of file: a text file, data file, photo, or anything else. You can optionally compress or encrypt the files before you load them.
Keeping AppsFlyer data up to date
At this point you’ve coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.
Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in AppsFlyer.
And remember, as with any code, once you write it, you have to maintain it. If AppsFlyer modifies its API, or sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.
Other data warehouse options
S3 is great, but sometimes you want a more structured repository that can serve as a basis for BI reports and data analytics — in short, a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, Snowflake, Microsoft Azure SQL Data Warehouse, or Panoply, which are RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, To Snowflake, To Azure SQL Data Warehouse, and To Panoply.
Easier and faster alternatives
If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.
Thankfully, products like Stitch were built to move data from AppsFlyer to Amazon S3 automatically. With just a few clicks, Stitch starts extracting your AppsFlyer data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Amazon S3 data warehouse.