Analytics Strategist

April 5, 2013

Bid quality score: the missing piece in the programmatic exchange puzzle

Filed under: Ad Exchange, Game Theory, Matching game, misc, Technology — Huayin Wang @ 7:45 pm

On the eve of the Programmatic IO and Ad Tech conferences in SF, I want to share my idea for a new design feature of Exchange/SSP, a feature that has the potential of significantly impacting our industry. This feature is the bid auction rule.

Bid auction rule is known to be central to Search Engine Marketing.  Google’s success story underscores how important a role it can play in shaping the process and dynamics of the marketplace. There is reason to believe that it has the similar potential for the RTB Exchange industry.

The current auction model implemented in Ad Exchanges and SSPs are commonly known as Vickrey auction, or the second price auction. It goes like this:  upon receiving a set of bids, exchanges will decide on a winner based on the highest bid amount, and set the price to the second highest bid amount.  In the RTB Bid Process diagram below, this auction rule is indicated by the green arrow #7:

RTB bidding process

RTB bidding process

(I am simplifying the process a lot by removing non-essential details from the actual process for our purpose, e.g Ad Servers)

The new auction I’d like to propose is a familiar one: it is a modified Vickrey auction with quality score!  Here, the bid quality score is defined as the quality of an ad to the publisher, aside from the bid price.  It essentially captures all things that a publisher may care about the ad. I can think of a few factors:

  1. Ad transparency and related data availability
  2. Ad quality (adware, design)
  3. Ad content relevancy
  4. Advertiser and product brand reputation
  5. User response

Certainly, the bid quality scores are going to be publisher specific.  In fact, it can be made site-section specific or page specific.  For example, a publisher may have a reason to treat Home Page of their site differently than other pages.  It can also vary by user attributes if the publisher like to.

Given that, the Exchange/SSP will no longer be able to carry out the auction all by itself – as the rule no longer depends only on bid amounts.  We need a new processing component, as shown in the diagram below.


Now, #7 is replaced with this new component, called Publisher Decider.  Owned by the publisher, the decider works through the following steps:

  1. it takes in multiple bids
  2. calculates the bid quality scores
  3. for each bid, calculates the Total Bid Score (TBS), by multiplying bid amount and quality score
  4. ranks the set of bids by the TBS
  5. makes the bid with highest TBS the winner
  6. sets the bid price based on a formula below, as made famous by Google


Here, P1 is the price set for the winner bid. Q1 is the bid quality score. B2 is the bid amount for the bid with second highest TBS. Q2 is the bid quality score for the bid with the second highest TBS.

This is not a surprise and it’s not much of a change. So, why is this so important?

Well, with the implementation of this new auction rule, we can guess some natural impacts coming out:

  • Named Brands will have an advantage on bid price, because they tend to have better quality scores. A premium publisher may be willing to take $1 CPM from apple than $5 CPM from a potential adware.  This will be achieved via Apple having a quality score 5 times or more higher than that of the other crappy ad.
  • Advertisers will have an incentive to be more transparent. Named brands will be better off with being transparent, to distinguish themselves from others. This will drive the quality score from non-transparent ads lower, therefore starting a good cycle.
  • DSPs or biddes will have no reason to not submit multiple bids, for they won’t be able to know which ad will be the winner before hand.
  • Premium Publishers will have more incentive to put their inventory into now that they have transparency and finer level of control.
  • The Ad Tach eco-system will respond with new players, such as ad-centric data companies serving the publisher needs, similar to the contextual companies serving advertisers

You may see missing links in the process I described here.  It is expected, because a complete picture is not the focus of this writing.  I hope you will be convinced that bid quality score / Publisher Decider is interesting, and potentially has significant impact by pushing the Ad Tech space in the direction of more unified technologies and consistent framework.

November 16, 2011

Ad exchange, matching game and mechanism design

Over the years, I have learned some interesting things in this new ad:tech industry, particularly around the Ad Exchange and RTB ad auction market model.  I want to share some of my thoughts here and hope you find them interesting to read.

Ad Exchange is not like a financial exchange

The “exchange” in the name is suggestive of a financial stock exchange market, and interesting observations can be made based on this analogy.  However, there are some fundamental differences such as the lack of liquidity in ad impression and information asymmetry.  Jerry Neumann has blogged about this topic profusely;  it is still a topic of great interest today, as seen in a recent article by Edward Montes.

In fact, the differences are easy to understand. The harder part is, like Jerry asked,  If the ad exchange aren’t exchanges, what are they?  or I should add, what should they be like?

Publisher’s preference is the missing piece

The analogy with financial exchange (stock and future) is not a good analogy partly because of its inability to fully model advertiser preference. Not all impressions are of the same value to an advertiser and not all advertisers give the same value to an impression. The commodity auction model as embedded in ad exchange does better, because it allows advertisers to bid based on any form of evaluation – a chance for advertiser to fully express its preference over audience, contextual content and publishers’ brand.

Still, there is a problem for the current auction model: after collecting all the bids from advertisers, it takes the highest bidder to be the winner, as if price is the only thing publishers care about.  In reality, not all bids with the same price are of the same value to a publisher.  Publishers care about brand safety and contextual relevancy as well; in fact, the quality of user experience may mean more to publishers than advertisers!  In sum, publishers care about the quality of the ads above and beyond the bid price.  Unfortunately, the current ad exchanges lack the proper mechanism allowing publishers to articulate their full preferences.  This results in lost of market efficiency and lost of opportunities to remove transaction frictions.  This is a design flaw.

Display marketplace is still far from perfectly efficient and this design flaw does not help.  The recent developments of Private Marketplace are piecemeal attempts to overcome this design issue.  Some market movements in late merge and acquisition attempts can be understood from this angle.

Where can we look for design idea on how to handle this issue?  – paid search and game theory!

The quality score framework from paid search

In many ways, paid search is just like ad exchange, with Google plays one of a few “publisher” roles.   In both markets, advertisers are competing for ad-view through auction bidding;  if we equate audience in display to keywords in search, then the bidding processes is quite the same:  search advertisers do extensive keyword research, look at past performance along side of other planning parameters such as time of the day etc. to optimize their bids;  similarly display advertisers look at the audience attributes, the site and page contents, past performance and planning parameters as they perform bid optimization.

The bidding processes in both markets are similar;  the differences lie in the post-bidding ad evaluation.

After all bids are collected, ad exchange today simply select the highest bidder.  In case of paid search, bids are evaluated on price, ad relevancy and many other attributes.  Google has mastered the evaluation process with its Quality Score framework.  This difference in having a Quality Score framework vs not is not a small thing.  As anyone familiar with the history of paid search know, the quality score framework played a pivotal role in shaping the search industry when Google introduced it around the turn of the century.  The post-bidding ad evaluation for display may just be a critical piece of technology and have potentially significant impact on the efficiency and the health of the display market.

The need for a non-trivial post-bidding ad evaluation calls for an extra decision process (and algorithm) to be added, either at ad exchange or at publisher’s site, or both.  In this new model and with this extra component, ad exchange will send the full list of bidding to the publisher instead of picking a winner based on price alone.  It is then up to the publisher to decide which ad will be shown.  With millions of publishers, large and small, this seemingly small change may be a trigger for more inside this industry where technology is already orders of magnitude more complex than paid search.

The matching game analogy

With full preferences being taking into account for both advertisers and publishers, ad exchange looks less like a commodity marketplace and more like the matching game.  It will be interesting to look at market efficiency from the perspective of mechanism design in game theory, which is another way of saying operational market process.

Matching advertisers with publishers under a continuous series of Vickrey auctions is our setup for the discussion – the best model I can think of that mimic the matching game setup;  it shouldn’t be too surprising to anyone that matching game is an interesting analogy to ad exchange.  As a game theory abstraction of many practical cases, matching game includes college admission and marriage market.  Let’s take the marriage market as an example.

Using a simplistic description, a marriage market involves a set of Men and a set of Women.  Each man has a preference vector over the set of women (a ranking of women);  similarly each woman has a preference vector over the set of men (a ranking of men).  A matching is an assignment of men to women such that each man is assigned to at most one woman and vice versa.  A matching is unstable if there exist a man-woman pair not currently matched to each other but both prefer match to each other than their current match – the pair as such is called a blocking pair.  When there is no blocking pair exist, a match will be called a stable match.

Clearly, stability of a match is a good quality: a stable match is not vulnerable to any voluntary pairwise rematch (translating into ad exchange language, a stable match is one such that no pair of advertiser – publisher currently not matched to each other have incentive to switch and form a new match).  A matching is male-optimal if no two males have incentive to switch partners. Female-Optimal is defined similarly.  A stable matching that is both male-optimal and female optimal looks like an perfect efficient market; we hope to find a mechanism that lead to the unique stable matching as such – something we can then mimic to implement for a future ad exchange model.

Unfortunately, there is no unique stable matching for matching game in general (in this case, having too many good things may not be a good thing).  There is also no unique optimal matching that is optimal from both men and women’s perspective.  We learned that Male Proposals Deferred Acceptance Algorithm, sort of like the current auction process in ad exchange in which advertisers played the male roles, produce Male-Optimal stable matching.  If we switch the role of men and women, a similar algorithm exists that produces Female-Optimal matching.  The two algorithms/mechanisms lead to two distinctly different results.  You can read more about algorithmic game theorycomputational game theory, specifically on matching game and mechanism design if interested.

So, why are we looking into this and what we’ve learned from it?  Below is my translation, or transliteration to be more appropriate, from game theory speak to the ad:tech domain.

We all like to believe that there is an efficient market design for everything, including the exchange marketplace for ads. Our believe is justified for all commodity marketplace by the general equilibrium theory.  Unfortunately, there is no equivalence of a “general equilibrium” or universal optimal stable match for a marriage market, which implies that there is no universal optimal advertiser-publisher matching in ad exchange.  If this is the case, the search for an optimal market mechanism for ad exchange will be a mission impossible.

However, there exist one-sided optimal condition, advertiser-optimal and/or publisher-optimal matching.  It is also easy to find the corresponding mechanisms that lead to those one-sided optimal stable matching.  The auction market as currently implemented in ad exchanges, with the addition of post-bidding evaluation process, is similar to the mechanism leading to advertiser-optimal matching.

The future seems open for all kinds of good mechanism design.  Still, I believe that there is a “naturalness” in the current style auction market.  It is quite natural for the auction process to start from the publisher side, by putting the ad impression on auction, because it is all start with the audience requesting a webpage – a request send to a publisher. It is not easy to imagine how advertiser can set up a “reverse auction” starting from the demand side, within a RTB context. We can never rule out the possibility, and it may work potentially for trading the ad future.


I am reluctant to draw any conclusions – these are all food for thought and discussion.  I’d love to hear your comments!

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