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Create key values based on viewability with Browsi

Browsi automatically passes a key named “browsiViewability” to Google Ad Manager. This key will be sent out with every ad request. In order to let Google Ad Manager collect this data and show analysis per our viewability prediction, you will need to create this key and associate its values.

  1. Navigate to your Google Ad Manager “Key Value” screen.Create a new Key named “browsiViewability” and create 11 values under this key: 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 1.00 and ‘NA’.

Google_Ad_Manager_-_Key-values3.pngGoogle_Ad_Manager_-_Key-values.png

NOTE:  The values you create need to be written exactly as described above! Otherwise, the value we send and the value written on Google Ad Manager will not match.‘NA’ value is for ad requests that Browsi was unable to predict (due to lack of data). This will be no more than 15% out of the total ad requests (avg. is about 8%).

After creating Key Values for Browsi viewability prediction, Google Ad manager will store the data per key value; generate a report.

  1. Navigate to the reports section and choose “Historical” report typeCreate a new report and filter by any placements/ad units you wish to see.Add “Key Values” as a dimension along with any other dimensions you want (day, ad unit, etc.)Choose the following fields: Total code served count, Unfilled impressions, Ad Exchange impressions, Ad Exchange average eCPM, Ad Exchange revenue.

     

     

Google_Ad_Manager_-_Queries1.png

Note: To measure requests we will add the “Total code served count” to the “Unfilled impressions”. We can measure that vs. the “Ad Exchange impressions field” to get the fill rate (assuming it’s serving only programmatic, otherwise you can remove your direct ad requests from this report).

Review the avg. cpm, fill and revenue per predicted viewability to understand exactly how buyers are reacting to viewability rate.

Google_Ad_Manager_-_Queries4.png
  • Notice the eCPM uplift as the predicted viewability is higher.

 

Analyzing traffic to find the appropriate floor prices:

  1. Different ad ops managers have different ways to find the right floor price for them. For our test, we were looking at the avg. winning bid histogram, and cutting the floor price about +-10 of the avg. bid.You can use whatever method you have in deciding what the floor prices should be – **The important thing is that you test your data per those viewability tiers:**Cut your traffic into 2 groups – one with predicted viewability of 0%-60% and one with predicted viewability 70%-100%.Decide over what floor price each group should get as if these were independent ad units.

Navigate to your Google Ad Manager open auction screen, and create two new pricing rules

Google_Ad_Manager_-_Ad_Exchange_rules.png

For each rule, make sure you target

  1. The correct ad units / placements / urls that you wish to apply the pricing rule on.

  2. The higher viewability tier with a higher pricing rule

  3. The respective values to the “browsiViewability” key.

Examples

If the floor price is for viewability below 70%

Google_Ad_Manager_-_Ad_Exchange_rules2.png

If the floor price is for viewability above 70%

Google_Ad_Manager_-_Ad_Exchange_rules4.png

That’s it! Let buyers pick up on those floor prices and you should start seeing results within a week after setup. Important: one day after setup, test that the inventory you intended reach the desired pricing rule took hold. To test this, generate a Google Ad Manager report per pricing rule.

Pro Tip (lightbulb)

After running the new pricing rules for a bit, check which buyers bought more on the high viewability pricing rule and connect that buyer directly to offer a PMP based on Browsi viewability prediction.

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