Metric Spotlight: Use Rate

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As part of Watching That’s #RecoverStronger programme, our “Metric Spotlight” series shines a light on particularly useful and effective metrics in video. Today’s post looks at Use Rate – a very handy metric for understanding the performance of inventory at the creative level. 

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What is Use Rate?


Use Rate is the measure of how many times an ad starts playing (the Start Ad event) against how many times it has been successfully loaded (the Ad Loaded event). 


There is a key stage in the sequence of a video ad’s lifecycle where the ad server hands off the available impression to a 3rd party system to fill 

This is the transition between the Request Zone and the Playback Zone, and it straddles the Ad Loaded event (where the ad server has successfully loaded the ad metadata into the ad unit) and the Ad Started event (where the creative file has started to playback). 


Use Rate in Ad Flow

Use Rate is the measure of how well that transition happens, and it provides great insight into:

  • Creative issues like formatting and file delivery problems;
  • Programmatic partner performance, especially any partners that are taking the inventory but ultimately not filling it;
  • In flight campaign performance.


How to Measure Use Rate

To get an accurate Use Rate measure you need to calculate the difference between two key client side events over a given time interval:

  1. Ad Loaded is a client side event emitted at the point in the sequence when the ad server has awarded the ad slot to a specific Line Item, Selling Partner etc.  
  2. Ad Started is a client side event emitted when the first frame of the video ad creative has started to render in the ad unit / video player.

Along with these event markers you’ll need to capture the ad metadata that has been loaded so you can analyse the Use Rate against important dimensions such as its:

  • ID so you can find it in the ad tech stack;
  • System Name of which platform owns it;
  • Wrapper Paths that show you its journey / handoffs;
  • Media URL that point to the server resource that contains its instructions.

You’ll also want to record the environmental context (Browser, Operating System, Device Type, Time of Day etc) so you can cross reference Use Rate performance of any given setup.

Here is an example of one Use Rate Visualisation available in the Watching That Platform.  You can see at a glance a performance of specific Creatives by ID against your global average:

Watching That Use Rate Visualisation

How Do I Use…Use Rate? 

If implemented correctly your best bet is to deploy Use Rate into your inflight campaign monitoring (for direct sold & Programmatic Guaranteed campaigns) and your programmatic partner optimisation work (for header bidding & open market setups).

Ensuring Peak Performance of Direct Campaigns

The most common point of failure for direct sold / PG campaigns is somewhere on the bridge between the Response Zone and the Playback Zone. 

Typically we see campaigns underperform by up to 20% because of inefficiencies and problems occurring in this handoff.

This is the area monitored and measured by Use Rate.

For any campaign creative that is delivering less than 95% Use Rate you want to know exactly where that is occurring (ie its Environmental context) so you can take appropriate action immediately.

This screenshot demonstrates how numerical IDs (nonsense) can be enriched into understandable context (insight).

Resolving Creative IDs to Detailed Context across multiple dimensions


Programmatic Tunnelling Pinpoints Demand Issues

On the other hand, video publishers who rely heavily on programmatic partnerships (via SSPs etc) often find themselves struggling to tunnel the programmatic layers to understand where and why ads fail to start playing.

Use Rate is very helpful here as well to identify creatives that are failing at the handoff.

By cross referencing an underperforming Creative by ID with its associated Wrapper Chain (the series of hand offs performed from the primary ad server to the end ad delivery platform), investigators can identify which demand paths might be inefficient, if not broken.

In the screen shot below you can see that a Creative ID (unhelpfully left blank by the ad delivery system) can actually be resolved into a very detailed statement of origin by crossing it with the Wrapper Chain as well as other environmental context.

This cannot be retrieved by the ad server alone (Google Ad Manager in this case).  It is a client side transaction that must be recorded and analysed. 

Resolving VPAID 901s to meaning


Furthermore, this Tunnelling technique breaks through the dreaded VPAID 901 error code.  

One of the greatest weaknesses of the VAST Spec, the 901 VPAID General Error is the bane of many an ad ops professional. 

However with Programmatic Tunnelling, spurred on by the adoption of the Use Rate measurement, you can identify 901s for failing creatives and finally explain them meaningfully!

And it doesn’t end there – once you have Use Rate in your wheelhouse, you can start looking at creative performance against video content to infer Brand Protection impact.

Or against file format to see if you have an error in your targeting.  

Video Ad Errors by File Type

In fact the list of use cases is endless…

So: adopt Use Rate TODAY to boost your video performance !



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