Analytics Strategist

April 5, 2013

Multi-touch attribution problem is solved, agree?

Filed under: attribution analytics — Huayin Wang @ 10:08 pm

I believe the MTA modeling problem is solved with the approach I discussed in the Unusually Blunt Dialogue on Attribution.  I have since received some questions about the approach, or the agenda; some related to the contents and others about formatting.  Today, I am going to try a simple recap, to address those questions.

First of all, the formatting issue. The format in WP is hard to read. A friend of mine (thank you, Steve!) is kind enough to put the content into MS-Word.  Anyone interested in reading the dialogues in a better format, can download it here:  the attribution dialogue.

Below are Q&A for other questions:

Q: Is attribution problem solved?

A: Hardly. Attribution problem consists of many challenges: data, model/modeling, behavioral insight, reporting, and finally optimization.

Q: When you started, you were aiming to reach a consensus on Attribution Model and Modeling. Have we reached the consensus? Is this attribution modeling problem solved?

A: Consensus is never easy to build and may never be achieved. I believe I have covered enough ground to build consensus on this issue, so we can move on to other businesses. I believe the MTA modeling problem is solved, but I am open to someone who can convince me otherwise.

Q: Is there any remaining issues not covered in your agenda?

A: Yes. One example of the left out issues is the search – display interaction; we handles part of it, but not completely.

Q: What do you mean?

A: There are two types of interactions:  the interaction effect at behavioral level, which is covered in the conversion model, and the interaction effect on media exposure.  The latter type of interaction is not capturable by conversion models.

Q: This is quite dense … do we need another methodology to model the likelihood of exposure?

A: I do not think individual level modeling is the right approach – lack of data is not the only challenge …

Q: Ok, if this is so, how can we say attribution modeling is solved?

A: I consider this to be outside the main attribution modeling.  This trailing piece may need a different handle – a “re-attribution” methodology?

(more to come)

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.

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