Common Metric Definitions and Examples

Common Metric Breakdown

Here are descriptions of some of the common metrics utilized in Ooyala IQ. This is not an inclusive list.

Displays: Measures the number of times that a piece of video content is loaded and displayed within the player before it gets played. Displays are related to each individual video. Each time an embed code is changed, this event gets triggered.

Plays Requested: Measures the number of times that the "Play" button is triggered either manually or automatically. The requested content could be ad content or the actual video content. A plays requested is counted regardless of which type of content is requested to play. Plays requested currently doesn’t include the Replay event.

Video Starts: Measures the number of times that actual non-ad video content starts playing. If the user initiates the playback experience and only watches a pre-roll ad without continuing on to the actual video content, a Plays requested count is reported, but not a Video Start. Video Starts is only recorded if the user waits until the actual video starts playing back.

Hours Watched: The amount of time (in the format HH:MM:SS) all users spent watching the selected video asset(s). The value of this metric will increase if a user rewinds and re-watches part of the video.

Replays: Measures the number of times the end user replays specific contents.

Average Time Watched per Video: The average time watched across all the users viewing this content across the different platforms. Today, we compute Average Time Watched (per video) = hours watched/video starts, converted to HH:MM:SS format.

Note: This number will be smaller than the duration of the video in most cases. However, seeks within the player can influence this number. If the user seeks back and forth during a playback, this will push up the time watched and can potentially cause the average time watched to be greater than the duration of the video.

Playthrough
  • Playthrough 25%: The number of video plays for the selected video assets that reached the state of 25% of completion.
  • Playthrough 50%: The number of video plays for the selected video assets that reached the state of 50% of completion.
  • Playthrough 75%: The number of video plays for the selected video assets that reached the state of 75% of completion.
  • Playthrough 100%: The number of video plays for the selected video assets that reached the state of 100% of completion.

Note: No matter how many times the user rewinds within the same view session, once the "state" is reached it won't be counted again.

Segments Watched: The number of times each segment of a piece of video content is watched. 1 segment is defined as 2.5% of video length.

Note: If a user rewinds and watches the same segment N times, Segments Watched for that segment will count as N times.

Unique Users:
  • Ooyala mobile SDK for iOS: The Ooyala mobile SDK for iOS generates and stores a random unique ID which is application-specific. The unique ID is generated in the "OOClientID" class and is stored in the "standardUserDefaults" object. The unique ID is valid until the application is deleted. This unique ID cannot be erased or reset by the end user without deleting the app. The application developer can store a different ID than the generated ID by erasing the existing ID [OOClientID resetID] and setting a new ID [OOClientID setID:New_ID].
  • Ooyala mobile SDK for Android: The Ooyala mobile SDK for Android generates and store a random unique ID which is application-specific. The unique ID is generated in the "OOClientID" class and is stored in the "SharedPreferences" file. The unique ID is valid until the application is deleted. This unique ID cannot be erased or reset by the end user without deleting the app. The application developer can store a different ID by erasing the existing ID [ClientID.resetID(context)] and setting a new ID [ClientID.resetID(NEW_ID)].
  • All other environments (HTML5, Flash, Chromecast): In other environments, a unique user is identified by local storage or cookie. To generate the GUID, Flash players use the timestamp of when the GUID is generated and append random data to it. The string is then converted to base64. To generate the GUID, HTML5 players use the current time, browser information, and random data and hash it and convert it to base64. Within the same browser on desktop, once a GUID is set by one platform it is used for both platforms for the user. If a user clears their browser cache, that user/device's ID will get regenerated next time they watch video. Incognito modes will track a user for a single session, but once the browser is closed the GUID is erased.

The generated IDs are completely random and don't include any user-identifiable information. When such information is not available for a user (there is no local storage or cookie), a new unique identifier will be created for that user. We de-duplicate when calculating the number of unique users over time. For example, day 1 has users A, B, C; day 2 has users B, E., then when you pick date range = day 1 and day 2, then total unique users = 4 (A, B, C, E), Daily Avg. Unique Users = (3+2) / 2 = 3 (2.5 is converted to the closed integer).

Examples

The following examples show how many displays, plays requested and video starts Ooyala IQ would record in different situations.

Example 1: Pre-roll Ads

The publisher has pre-roll ads delivered during playback.

User A begins watching video X with 2 pre-roll ads but leaves after the first ad. User B begins watching video X (again with 2 pre-roll ads), and leaves after both ads and one minute of play time.
Table 1. Metric Tallies for Example 1
  Displays Plays Requested Video Starts Avg. Time Watched/Video
User A 1 1 0 00:00:00
User B 1 1 1 00:01:00
Video X in total (User A + User B) 2 2 1 00:01:00

Example 2: Replays

The user clicks replay to play the content again during the same viewing experience.

User A begins watching Video X with 1 pre-roll ad, watches the ad and the content all the way through and then hits re-play and watches it all the way again. Alternatively, User B, in the second replay, watches the ad and then exits.
Table 2. Metric Tallies for Example 2
  Displays Plays Requested Video Starts
User A 1 1 1
User B 1 1 1

Example 3: Mid-roll Ads

The publisher also delivers mid-roll ads during the content playback experience.

User A begins watching Video X with 2 pre-roll ads, watches the ads, starts watching the content, sees a mid-roll ad and exits the video. User B begins watching Video X with 2 pre-roll ads, watches the ads, starts watching the content, watches the mid-roll ads and completes the video.
Table 3. Metric Tallies for Example 3
  Displays Plays Requested Video Starts
User A 1 1 1
User B 1 1 1
Video X in total (User A + User B) 2 2 2

Example 4: Seeks

The user can also seek through content back and forth during a single viewing experience within the player.

User A begins watching Video X with 2 pre-roll ads, watches both ads, starts watching the content, watches a mid-roll ad, continues watching and then seeks back to the beginning and plays the content. The user is now shown the mid-roll ad again. This results in 1 display, 1 play requested, 1 video start.
Table 4. Metric Tallies for Example 4
  Displays Plays Requested Video Starts
User A 1 1 1

Example 5: Autoplays

The publisher has autoplay turned on - this means that the video player starts playing the content automatically when the user visits the page containing the player.

User A visits the page (where autoplay is turned on) with 1 pre-roll ad, watches the ad and exits before the video begins playing. User B visits the page (where autoplay is turned on) with 1 pre-roll ad, and exits the page halfway through the video content.
Table 5. Metric Tallies for Example 5
  Displays Plays Requested Video Starts
User A 1 1 0
User B 1 1 1
Video X in total (User A + User B) 2 2 1

Example 6: Playthrough

This example shows how playthrough is counted. The video in this example is 4 minutes in length.

User A watches the video content from its beginning to 2 minutes and 30 seconds and then stops watching.

User B watches the video content from its beginning to 3 minutes and 30 seconds, then rewinds to the beginning and watches all the way to 1 minute and 30 seconds, then stops watching.

User C seeks to 2 minutes directly and watches from there to 2 minutes and 30 seconds then stops watching.
Table 6. Metric Tallies for Example 6
  Playthrough 25% Playthrough 50% Playthrough 75% Playthrough 100%
User A 1 1 0 0
User B 1 1 1 0
User C 1 1 0 0

Example 7: Segments Watched and Hours Watched

In this example a video is 20-minutes in length. This video has 40 buckets assigned to it, where each bucket is 30 seconds in length.

User A plays the video and watches it through 1 minute.

User B plays the video and watches it through 1 minute, then rewinds to 40 seconds and watches through 1 minute again during the same video view session (the user didn't reload the player).

User C plays the video and watches it through 1 minute, then fast-forwards to 19 minutes and 31 seconds of the video content and watches through the end from there.
Table 7. Metric Tallies for Example 7
  Segments Watched Hours Watched
User A

1st bucket has 1 play

2nd bucket has 1 play

00:01:00
User B

1st bucket has 1 play

2nd bucket has 2 plays

00:01:20
User C

1st bucket has 1 play

2nd bucket has 1 play

40th bucket has 1 play

00:01:29

In User B's scenario, the second bucket has 2 plays because the user rewinded within the second bucket. This is because segments watched captures the total number of plays each specific segment incurs in order to measure its popularity (no matter if it's from the same user rewinding or from different users watching it). So within the same video view session the segments watched number could increase if a user rewinds. Percentage watched is still 5% for user B because the user still only watched 2 buckets (1st and 2nd). Percentage watched is used to measure the percentage of the whole video content that ever got watched (the count won't increase if the same user rewinds within the bucket that already got watched during the same video view session).

Percentage watched measures how many percentages of the whole video content ever got watched (40% watched could mean the first 40% of the content got watched or it could mean first 20% of the content got watched and last 20% of the content got watched).

Example 8: Unique Users

This illustrates how unique users are counted. You have a video on your website “myExampleSite.com”.

Situation A: User W watches your video on their iPhone with application 1. Later in the day they decide to watch the video again on their iPhone with application 1.

Situation B: User X watches your video on their laptop. They leave the browser window up and go about their day. Twelve hours later they come back to their laptop and re-watch the video.

Situation C: User Y watches your video on their tablet. They then watch the video on their laptop, while still using the same wifi network as before.

Situation D: User Z watches your video on their laptop in Browser 1. After the video finishes they clear their cookies. They then watch the video again in Browser 1 on their laptop.

Table 8. Metric Tallies for Example 8
  Unique Users
Situation A 1
Situation B 1
Situation C 2
Situation D 2

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