Product Management

Update and perfect your app by getting a better understanding of your user base

Pull and analyze data from our front end

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 function can be a great way to quickly access and analyze the displayed data.

By importing the CSV file 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 to your needs.

You can download the CSV for the vast majority of features on our platform such as for user reviews, download and revenue figures, usage metrics, and more. You can also adjust the various filters on our front end (e.g. date range, country, category) to display only the relevant information in the
downloaded file.

There are currently two types of CSV you can download from the front end: 

  • Export Detailed Data: Includes all information such as App ID, Parent Company, Publisher ID, etc. This is the default CSV format.
  • Export Selected Data: Lets you download specific snippets of data from the front end.

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

Download front-end data

  1. Navigate to a module such as Store Intelligence > App Analysis.
  2. Adjust filters to target your desired data, such as Date range, Category and Country / Region.
    Select_Filters.png

    You can also adjust the Date Granularity by clicking on the dropdown menu to the top left of the graph. This option lets you toggle how granular you want your data to be: Daily, Weekly, Monthly, or Quarterly.

  3. Click Download CSV at the bottom of the sidebar and, if available, select either Export Selected Data or Export Detailed Data.
    Download_CSV_Button.png

The Detailed Data CSV option will contain metadata such as your selected date range as well as all relevant data including App ID, Publisher ID and Days Since Launch.
Detailed_Data_CSV.png

The Selected Data CSV will populate the first column with the graph's x-axis (e.g. date); the breakdown types appear as column headers, and the graphed data will appear in their respective cells. Facebook_and_Insta_Net_Revenue.png
Selected_Data_CSV.png

This example shows how you can pull CSV data from our front end. However, this is also possible through the back end via our API. For more information regarding pulling information from the API, please refer to our API Reference documentation.

Use filters and pivot tables to analyze 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.

Apply filters to a CSV

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

    filter.png

  2. Now, you can click on each filter and toggle relevant data according to your needs. In this example, you can choose to display only data from a particular country.
    country.png

However, let's say you wanted to view the sum of all downloads and revenue numbers for every country. Manually filtering and summing each country is time-consuming so this is 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.

Create a pivot table

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 in the CSV.

  1. Highlight your subset of data and navigate to Insert > PivotTable. 

    pivot_table.png

  2. Click OK.
  3. After you create a pivot table, a PivotTable Fields panel will appear on the right. This is where you can drag and drop the appropriate fields into each of the four boxes below.

    pivot_table_fields.png

  4. The Filters section is responsible for filtering the overall data sets in your pivot table. In this example, it's App Name.
  5. The Rows / Columns section allows you to choose which fields you'd like to display in rows or columns.

    A list of country codes is available here.

  6. 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 and revenue for both iOS devices.
  7. 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 the order you'd prefer.

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