Sensor Tower excels at providing data and insights in a visually appealing, organized, and convenient manner on our website. However, in situations where you have to pull large amounts of raw data from our platform, using the Download CSV button can be a great way to quickly access and analyze the displayed data in a .CSV format. By importing the .CSV into a spreadsheet software such as Microsoft Excel, you can add filters, pivot tables, charts, and more, in order to better customize and analyze data suited towards your needs.
Downloading Frontend Data
You can download the .CSV for the vast majority of features on our platform such as for user reviews, download & revenue figures, usage metrics, and more. You can also adjust the various filters on our frontend (i.e date range, country, category) to display only the relevant information in the downloaded CSV.
To download data from the frontend:
- Navigate to your desired page (i.e Store Intelligence > App Analysis > App)
- Adjust any filters accordingly, such as the date range
*Note: You can also adjust the Date Granularity by clicking on the dropdown menu near the top left. This option lets you toggle how granular you want your data to be - Daily, Weekly, Monthly, or Quarterly.
3. Click Download CSV after you've finalized your filters.
4. The CSV should contain metadata such as your selected time range, as well as a row that lists the various metrics, as shown below:
This example shows how you can pull .CSV data from our frontend. However, this is also possible via the backend through our API. For more information regarding pulling information from the API, please refer to this help document HERE.
Using Filters & Pivot Tables to Format Data
One of the best ways to visualize and analyze CSVs is through the use of filters and pivot tables. These tools allow you to organize aggregate amounts of data by sorting them
into their respective categories. After you apply filters to your selected categories, you can pick and choose which subset of data you wish to see.
To apply filters to a CSV:
- Highlight the row with the selected metrics and select 'Filter' from the Sort & Filter feature.
Now, you can click on each filter and toggle relevant data according to your needs. In this example, you can choose to only display data from a particular country.
However, let's say you wanted to view the sum of all downloads & revenue numbers for every country. Manually filtering and summing each country would take ages to do, so that's where pivot tables can come in handy. Pivot Tables allow you to view aggregate data in a more extensive and significant manner by lumping similar data together.
To create a pivot table:
- Highlight your subset of data and navigate to Insert > PivotTable. Double check the selected Table/Range and hit OK.
2. After you create a Pivot Table, a PivotTable Fields panel will appear on the right. This is where you can drag & drop the appropriate fields into each of the four boxes below.
- The Filters section is responsible for filtering the overall data sets in your pivot table. In this example, it's "App Name".
- The Rows / Columns section allows you to choose with field you'd like to display in rows or columns. Note: A list of country codes can be located HERE on our help page.
- The Values section is the object of interest - what is the primary data that you're interested in? In our case, we want to find the sum of downloads & revenue for both iOS devices.
3. After you've finished placing each field into their respective sections, the data should be neatly summarized in the Pivot Table. You also click on the + button to expand each row to view the nested fields, as well as rearranging them depending on which order you'd prefer.
Pivot Tables are a great way to visualize aggregate amounts of data, especially in scenarios where there are multiple number of fields, and different types of data on the CSV.
For more information or if you have any questions, please email: firstname.lastname@example.org