Export CSVs with any filtered view or dataset - starting today
We’ve upgraded the way CSV exports (reports in our lingo) are generated from Adjust. As of today, you’re able to pull full CSV exports of any view in your dashboard. Whatever filters you can set in the dashboard, you can also export from the same views.
The previous button for report downloads has been extended with further options. You know have two different types of exports from any view:
- “snapshot” reports that simply export the table you’re looking at, as-is;
- “drill down” reports that are formatted in the same way as the exports you’re used to - ready for all your pivot table needs.
Reports are instantly generated for you and downloaded right in the browser.
With this new option, you can create a custom view - specifying which metrics to display, countries to filter to, drill down into specific trackers, and more - and export that specific dataset. If it’s a regular thing, you can save the views and easily log back in to pull another export later.
Just like with custom views, this of course also applies to your cohort analysis views.
This change does mean we’re removing the regular instant report options from the apps overview. That’s still where you can specify email subscriptions to reports, though.
Drilling down further in Excel
Our granular drill-down reports are designed to be imported into Excel for use with pivot tables, SQL databases, or other further use cases.
Each metric in your view is represented as a column in your CSV, and each segment (such as sources & campaigns, or cohort install dates) is represented as a row.
In Excel, it’s exceedingly easy to apply conditional formatting, create charts, or filter the report as-is. Pivot tables are also very useful to aggregate segments in particular ways, like grouping countries or specific dates based on your business needs.
Getting serious about your exports
We regularly bring stuff into ad-hoc SQL databases or into R for further processing. In case you missed it, our CTO Paul once put together a guide on how to query CSV imports in an interactive SQL environment.
If you’re already handy with either of these, you might even want to try out callbacks or the KPI Service - for which there’s both an R wrapper and a command line interface.