Header Bidding Analytics

Header Bidding Analytics
Header Bidding Analytics is included in the Headbidder.net Wrapper toolset. This is the complex instrument that collects data directly from auctions, store in DB and provides Users with table- and graph-styled visualization of what is happening with ad sales.

Full reporting

These days a huge number of Publishers implement Header Bidding ad sales on their sites. That's obvious, header bidding wrapper scripts are only scripts and a flow of bids on a browser or server backend. In the majority of cases, wrappers have no UI or reporting interface. Publishers are obliged to trust SSPs reporting while calculating revenues and have no chance for deep bidding process analysis and knowing what is happening in auctions and what were opportunities that lost.

Header Bidding Analytics tool provided by HeadBidder.net collects data on the client's side, directly from the prebid.js auction in the user's browser. It records ALL the bid requests sent and ALL the bids received, not only the winning ones. A user obtains aggregate bidding activity info. This allows to estimate missed auction opportunities, and not only see the auction results. This information is related to both, banner and instream-video ad sales.

Header Bidding Analytics
Go deeper, investigate each bidder bid/win CPM broken by geography, by ad spot size, by a device type. Look into the bid CPM landscape. Find setup errors and identify areas to amend and improve. Constantly monitor actual fill rates, win rates and win prices, eliminate discrepancies between your ad stack and demand partner's reports.

Reporting metrics, dimensions and values

Bids and Wins, Revenue and CPMs, Bid rate, Win rate, Time-out events and Latency, all broken by day or bidder. Dimensions include Country, Device type, Platform, Ad Unit name and size, Site name. If auto-refresh has been activated, reporting might show was the revenue brought by refreshed impression or by initial page load.
Header Bidding Analytics

What answer header bidding analytics answers to:

  • How much revenue do you make each day from each bidder?
  • How does the bid response time of each demand partner compare to others?
  • Who is the underperforming demand partner in terms of bid rate and win rate?
  • Which one of your demand partners is slowing-down bidding, who brings the worst time-out?
  • What is the best time-out value to get the highest website revenue?
  • What discrepancies you have and where they come from?
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