Challenge: There is little to no consistency in how brands or agencies approach reach/frequency measurement. Because each media buyer, for each spot market buy, has 500 million potential combinations in order to measure maximum reach, ‘reach’ is often completed by best-guess.

Primary Measure of Success (KPI): Maintain or increase reach metric within flat budget across all spot market buys.

Strategy: Use data science to reverse engineer spot buys and create accuracy and consistency in reach measurement – which has never been done before by any company.

Tactics: Data scientist used a neural network to replicate the ad buying platform reach calculation, then built an algorithm that recommended which spot placements to buy to maximize reach. Additionally, the algorithm could identify the point of diminishing return.

Results:

  • Entertainment brand increased reach on average of 10% across all campaigns, while simultaneously decreasing costs 10%.
  • Savings were redeployed to non-traditional video touchpoints.
  • Reach curve analysis consistency across all markets.
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