Tuesday, June 2, 2015

Player size restricted Video CPM as a function of Demand

Player size restricted Video CPM as a function of Demand

Experiment description and Analysis

Biggest client tactics representing about 9% of total video revenue were duplicated with all prior restrictions (geo, site, device etc.), additionally restricted to Player size > 400 X 300 and budget-density tested at 1X, 2X, 6X and 12X daily budget on 25, 12, 4 and 2 buckets respectively. For each of these budget points we have the spend, cost and impressions in the player size inventory.

We are clearly having trouble delivering at scale for the higher budget density - we are delivering only about 35%. For example, to hit the actual budget density points, every tactic in a line item (targeting different numbers of user buckets) should have had the same cost, yet on 5/19/15 the cost in "2 buckets" is only 129 instead of 379. Hence, while the goal was to explore a range  12X the current total video revenue, in practice we've only been able to get to about 4X. 

From querying our database

we know that about 35% of all our impressions  and 35% of video cost are for player size > 400X300, so for all the video tactics which weren't restricted by player size as part of this test, we uniformly apportioned 35% of spend and cost (assuming margin was same) and 35% impressions in the tested user buckets to player size restricted inventory.

The above spend cost and impressions were added to those for the tested tactics, 

and CPM vs daily cost was plotted and fitted to a power law. 

Why a power law? Because cost (CPM) elasticity of demand (total cost) is the ratio of the logarithmic derivatives, which is just the exponent in a power law. 

The Calculator

dailyCost = (1-margin)*dailySpend

actualDailyCost = (spendFraction + (1-spendFraction)*costFraction) * dailyCost

Cost Based CPM from fit to elasticity curve evaluated at actualDailyCost
Revenue CPM = CostCPM/(1-margin)

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