Understand data definitions

This guide will help explore the six key metric groups we have defined to assess viewer engagement and QoE, helping you optimize content delivery and improve user satisfaction.

Using APIs to retrieve metrics

To get audience metrics like Views across different timeframes and filter options, you can use the FastPix API endpoints. Below is a step-by-step guide to walk you through retrieving these metrics.

Step 1: Set up your API access

Before making requests to the FastPix API, ensure you have your Access Token ID and Secret Key ready for authentication. See the Basic Authentication Guide for details on retrieving these credentials.

Step 2: Retrieve overall values for views

To get the views metric across different timeframes, you can use the list overall values endpoint. Here’s how to make a request:

Example request:

$
curl --request GET \
>
     --url 'https://api.fastpix.com/v1/data/metrics/views/overall?timespan[]=30:days' \
>
     --header 'accept: application/json' \
>
     --user '{Access_Token}:{Secret_Key}'

In the above request, you need to replace Access Token ID and Secret Key with your actual credentials. Also, adjust the timespan parameter as needed (for example, 7:days, 30:days, etc.).

Example response:

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{
2
  "success": true,
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  "metadata": {
4
    "aggregation": "view_end"
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  },
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  "data": {
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    "value": 118,
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    "totalWatchTime": 2643439,
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    "totalViews": 118,
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    "totalPlayTime": 1722574,
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    "uniqueViews": 15,
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    "globalValue": 0.5107432787924294
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  },
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  "timespan": [
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    1735117394,
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    1737709394
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  ]
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}

Please refer to our API reference for overall values to understand more about different parameters that you can apply to get the values for all other metrics.

Similarly, in order to visualize the value of a metric and number of views within a timeframe, you can use the Get timeseries data endpoint. The response includes an array of data points, each representing the metric’s value and view count at specific intervals. This can be used to create graphical representations.

Also, to understand how views are split across different dimensions like browser and device type, you can use List breakdown values. For instance, if you want to analyze how watch time varies across different device types, calling this endpoint for the playing_time metric and filtering by device_type shows how engagement differs between mobile, desktop, and tablet users. This data will guide optimization efforts for different platforms.