Analytics Strategist

December 31, 2008

Attribution Models

In marketing, particularly in search engine marketing, there has been a growing interest in attribution models.  It is perhaps no coincidence that the same period saw a tighten-up budget and increasing demand for accountability – afterall, attribution is the process of how success are credited to its source(s) – a highly contentious field in marketing. 

This is one of the many reasons I expect attribution modeling to atrract even more attention in 2009 – with SEM and multi-channel marketing at the center of it all. 

There are many uses of “attribution”: in arts and academia it refers to crediting the original authors; in performance attribution – a large area covering investment, marketing etc – it refers to crediting results (or partitioning the results) to its sources or its causes; still it has a place in psychology where the attribution processes of behaivor is the focus of study.

Attribution in marketing/advertising world is the process of attributing the success (usually sales or other metrics) to the marketing/advertising activities.  Since most of the time different activities result in different customer touch points, it reduce to crediting sucess to different touch points.  From this perspective, multi-protocol attribution, engagement mapping, marketing mix modeling, even customized 800 numbers are all attribution approach and techniques.

In the follow up post, I will discuss in details the other aspects of attribution modeling; why attribution modeling is important, what are the different type of attribution challenges, how to do it, and finally what are the limitations of the whole attribution modeling approach …

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December 30, 2008

The annoying misuse of web analytics

Filed under: Business, Web Analytics — Tags: — Huayin Wang @ 10:04 pm

I really dislike people using Web Analytics as a synonym for web analytic tools and softwares working with web traffic data.  Software is not discipline; wake up people!

The confusing usage comes from the fact, based on my wild guess, that there are some people for whom there is no analytics other than Web Analytics.  Well, get educated!

For those who have trouble with how I felt, please read the following paragraphes:

“Analytics solutions typically fall short in understanding post-impression data …”

“the common limitation of analytics is that it lacks the data insights of offline behavior …”

The misuse of the word “Web Analytics” is corrupting the commnication – it may make sense in the little corner of some people and only within their little corner.

Web Analytics is not refering to a set of software/tools (which includes Google Analytics), it refers to a subdiscipline of data analytics.  Please, stop labeling “Best Web Analytics” when just you really mean just a comparison of web analytics tools.

December 18, 2008

Google’s achilles’ heel – a follow up

Filed under: Datarology, Technology — Tags: , , , , — Huayin Wang @ 9:52 pm

Follow up to one of my early post about google’s achillis’ heel, I’d like to add that Google’s latest searchwiki seems to be an interesting response to what I mentioned earlier — I know I know it is not quite like that 🙂

I love to count the many different ways of ranking stuff in response to a search query.  The objects, the stuffs, can be text, link, document, image, video etc..  The ranking principle is the essentially a rule of relevance and/or similarity. I count four main types:

1) by content similarity, the algorithm could be PageRank, HITS etc..  For images and videos, this can prove to be very difficult because it involves not only the hard core technology such as pattern recognization for images, but also involves large stocks of prior knowledge about object categorization etc..

2) by similarity of user behavior, when applied some kinds of collective intelligence, or collaborative filtering type of algorithms.  User behavior can serve as implicit voting; with algorithms’ help, the complexity of the ranking operation can be dramatically reduced.

3) by similarity of user explicit ratings.  Users’ search phrase and explicit ratings ( ratings/reviews on amazon, as well as Google’s latest searchWiki, which interestingly only affect what user see next time, not anyone else’).  Some types of social/collective intelligence algorithm has to be applied in order to solve the complexity issue, as well as the sparse data problem associated it when crossing search query with user ratings.

4) of course, there is always the money logic.

If you know more ranking logic than what posted here, I’d like to know it ..

December 16, 2008

migrate from blogger to wordpress

Filed under: misc — Tags: — Huayin Wang @ 4:56 am

I have just consolidated all posts from 6 of my prior bloger blogs to wordpress – feeling light and fit 🙂

oh ya.

Blog at WordPress.com.