Teikametrics Launches Hourly Bidding Algorithm for Amazon Advertising

Teikametrics, providers of a retail optimization platform (ROP) for Amazon advertising campaigns, has launched an hourly bidding solution for Teikametrics Flywheel. Flywheel combines advertising data, transaction data, and cost of goods sold to algorithmically optimize for Amazon Advertising profitability.

The hourly bidding algorithm is powered by an econometrics and machine-learning data model that allows Amazon advertisers to automatically adjust bidding strategy, minimize wasted ad spend, and adapt to changing marketplace dynamics. This capability takes advantage of Amazon's recent ad policy that allows for less lag time in reporting advertising performance data.

Being able to calculate the most profitable bid on an hourly basis allows Teikametrics' ROP platform to proactively invest ad dollars where the algorithm predicts the highest return on investment. Keywords and ad groups with high traffic volumes and competitive auctions, such as consumer electronics, household items, and apparel, are among those that will benefit the most during the first few days of bidding. Teikametrics' clients can also explore winning auctions and experiment with more aggressive bidding strategies to extract keyword performance information.

"Amazon is quickly gaining ground on Facebook and Google as a leading online advertising channel," said Alasdair McLean-Foreman, CEO and founder of Teikametrics, in a statement. "In a marketplace as dynamic and competitive as Amazon, reaction time is critical. Teikametrics' hourly bidding algorithm is the first solution to enable brands to react to statistically significant changes in their Amazon ads data with hourly granularity. This is another major milestone in our ongoing mission to help brands maximize profit on Amazon."