Pulling and Analyzing Data from our Frontend

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
download_CSV.png
can be a great way to quickly access and analyze the displayed data in a .CSV format. By importing the.CSV into 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.

There are currently 2 ways to download CSVs from the front end: 

  • Export Selected Data
  • Export Detailed Data

Choosing the “Selected Data” option lets you download specific snippets of data from the frontend. Choosing “Detailed Data” will include all information such as App ID, Parent Company, Publisher ID, etc.

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Note: Screenshot depicting the “Selected CSV” export

Export Selected Data is currently available within Store Intelligence App Analysis only. We are actively working on enabling it in more products.

 

To download data from the frontend: 

     1. Navigate to your desired page (i.e Store Intelligence > App Analysis > App)
          app_analysis.jfif

     2. Adjust any filters accordingly, such as the date range
          date_picker.jfif

   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 and select either “Export Selected Data” or “Export Detailed Data”.
            export_options.jfif

Note: Hovering over the “?” icon reveals a short description of the Selected Data export. Clicking on the “?” icon will navigate you to this page.     

4.  
The “Export Detailed Data” option will contain metadata such as your selected date range and a row listing the various metrics:
 

export_detailed_CSV.png

Note: The above screenshot illustrates the “Detailed CSV” export.

5. The X-Axis (Date) on the chart is illustrated in the first column; the breakdown type appears as column headers, and the graphed data will now appear in their respective cells.
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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:

  1. Highlight the row with the selected metrics and select 'Filter' from the Sort & Filter feature.

 

filter.png         

country.png                                                                                 

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:

  1. Highlight your subset of data and navigate to Insert > PivotTable. Double-check the selected Table/Range and hit OK.
pivot_table.png

 

        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.

pivot_table_fields.png


           - 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 a multiple numbers of fields and different types of data on the CSV.



For more information or if you have any questions, please email: support@sensortower.com

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