Top Header Bidding Partners Performance Report
January - April 2018
Sample & Methodology
The report is based on the Roxot Prebid Analytics data from publishers who agreed to participate in the research. Roxot Prebid Analytics collects client-side data about all header bidding auctions running in the website's prebid.js wrapper and all demand partners participating. Therefore, the report is based only on the client-side data.
We analyzed almost 3 billion requests generated by North American users on 358 websites from January 1st to April 30th, 2018.
Please, mind that the report is based ONLY on the Roxot Prebid Analytics users data and might be biased to some of the bidders. The users might have implemented demand partners incorrectly, which would affect the results of this report. However, we took measures to prevent any data inconsistency:
- Reduced data contribution of the sites with total revenue share higher than 20%
- Excluded sites with abnormal bidder behavior (e.g. 0 bids, bid rate lower than 5% or higher than 90%)
- Combined data of different adapters for the same demand provider (e.g PulsePoint and PulsePoint Lite, AppNexus and AppNexus AST, etc.)
Header Bidding Partners Performance Analysis
Top bidders by Bid Rate*
Bid Rate shows how often a demand partner replies with a bid to an ad request. If there is no bid, demand partner might be too slow or not have ads for a particular website visitor. The bidding frequency directly affects the competition inside your wrapper and your total Fill Rate.
*Bid Rate - how often a bidder replies with a bid to an ad request
Top bidders by Win Rate*
The Win Rate shows how a bidder competes with other partners in the header. To get impressions and generate revenue a bidder has to both bid often and win often. A high Bid Rate would mean nothing if partner's bids never win.
*Win Rate - how often bidder's bids win prebid auctions
The slowest bidders
The "winners" in this category are the bidders who get timed out more often than others. If you are actively working on improving your page load times, pay the closest attention to this section. Timeout Rate* is a must-have metric when analyzing bidder's performance. It helps you identify adapters that damage your UX and optimization options.
*Timeout Rate - percentage of ad auctions that a bidder didn't provide a bid in the time specified in your prebid.js timeout settings.
Total Bidders Efficiency & Conclusions
The data used for research doesn't represent the whole market but provides valuable information when building your header bidding strategy. Understanding your demand and mapping it to the appropriate bidders is key to crafting a successful mix of SSPs.
The research clearly underlines 4 top bidders by overall efficiency (how many requests to a bidder resulted in its impression) - Facebook Audience Network, Index Exchange, AppNexus, and Rubicon. FAN bids rarely but certainly does its job when matches a user - 80.5% desktop Win Rate and 86.4% mobile Win Rate say it all. In turn, AppNexus, Index Exchange, and Rubicon are the most efficient as they both bid and win often.
Consider adding other demand partners that bid often to increase the total Fill Rate of your site. Despite the low Win Rate, such bidders increase bid density and guarantee there is a bid to compete with the demand in your ad server.
*Total efficiency — how many requests to a bidder resulted in its impressions (Bid Rate * Win Rate)