IPONWEB's Optimal Price Discovery is reducing media costs by 15% to 30%

IPONWEB today announced that Optimal Price Discovery, IPONWEB's bid shading solution is helping programmatic buyers to reduce media costs by 15% to 30%. IPONWEB states bid shading solution is being helpful to buyers in the transition to first price auctions.

IPONWEB owns BidSwitch, one of the main exchanges on RTB, connecting SSPs and DSPs.

On second price auctions (the standard auction until 2018), buyers bid high on an impression to win, but pay only one cent more than the second-highest bid. On first price auctions the winner pays the amount they bid.

IPONWEB says the bid shading built into most major DSP’s platforms still presents a black box to buyers, and Optimal Price Discovery engine can be integrated with any DSP using OpenRTB protocol.

IPONWEB's bid shading takes into account a number of variables about any given programmatic auction - publisher, ad size, device, geo-location, platform, etc - and calculates a new (lower) maximum a buyer needs to bid, without reducing their probability of winning the auction.

According to IPONWEB, bid shading requires access to massive amounts of constantly changing bidstream data, machine learning capabilities to make sense of that data, and predictive technology that can reduce the amount an advertiser bids on specific inventory without hurting their ability to still win the auction.

"With Google's shift to first price, bid shading has become a necessary tool in buyers' arsenals to ensure they're not overpaying for media purchased via programmatic channels. Platforms that don’t have bid shading capabilities will find it harder to satisfy agency and advertiser demand for performance and efficiencies - and are likely to be optimised out of buys,” says IPONWEB Product Lead, Nikita Borisenko.

Once Optimal Price Discovery is integrated, a DSP identifies an impression opportunity on which it wants to bid, forwards its YES bid to the Optimal Price Discovery engine, which evaluates bidstream data against historical win data to make a prediction on the optimal bid price needed to win the auction. This optimized bid is passed back to the DSP, which returns it to the SSP — all in under 5 milliseconds.