Bid landscape

Bid-landscape data is the full spread of bids and clearing prices that a set of impressions received, broken down by ad unit, buyer, deal or time, and used to set floor prices and bids.

Publishers see every bid that reaches their auctions. They can chart how many bids arrived at each price, from which buyers, for which ad units. The UK CMA notes that publishers can build this full view by ad unit and buyer, and may share it with buyers, header bidders included (CMA, Appendix M, paragraph 484, 1 July 2020). The same appendix describes publishers comparing this bid data with their revenue reports and raising floors when second prices ran far below top bids (paragraph 39).

Buyers have a narrower view. A DSP sees only its own bids, wins and losses. OpenRTB 2.6 added the ${AUCTION_MIN_TO_WIN} macro so an exchange can tell each bidder the lowest price that would have won or tied (IAB Tech Lab, OpenRTB 2.6, section 4.4.1). Collected over millions of auctions, these signals give a bidder its own picture of prices on each supply path. That picture feeds bid shading and supply path optimisation.

The CMA also found that, in a first-price auction, knowing the minimum bid to win makes the market more efficient, because buyers can bid closer to the real clearing level.

Example: Take the OpenRTB 2.6 first-price case: a $0.85 floor and bids of $1.00, $0.90 and $0.80. The $1.00 bidder wins and learns that $0.90 would have tied. The losers learn that $1.00 was needed. A bidder that keeps winning far above the minimum is overpaying and can shade its bids.

Related terms: floor price, bid shading, win rate, second-price auction, log-level data, dynamic floors.

Authoritative source: UK CMA, market study Appendix M, paragraphs 39 and 484 (1 July 2020).