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SmartData Collective > Analytics > Predictive Analytics > The Next Wave in Recommendation Systems?
AnalyticsExclusivePredictive AnalyticsWeb Analytics

The Next Wave in Recommendation Systems?

paulbarsch
Last updated: 2011/04/26 at 2:23 PM
paulbarsch
4 Min Read
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While some internet privacy experts fret over use of cookies and web profiles for targeted advertising, the quest for personalization is about to go much deeper as web companies create new profiling techniques based on the science of influence.

While some internet privacy experts fret over use of cookies and web profiles for targeted advertising, the quest for personalization is about to go much deeper as web companies create new profiling techniques based on the science of influence.

Behavioral targeting on the web using cookies, http referrer data, registered user accounts and more is about to be significantly enhanced says columnist Eli Pariser.  In the May 2011 issue of Wired Magazine, in an article titled “Mind Reading”, Pariser discusses how website recommendation and targeting algorithms; “analyze our consumption patterns and use that information to figure out (what to pitch us next).”   However, Parser notes that the next chapter for recommendation systems is to discern the best approach in influencing online shoppers to buy.

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Editor’s note: Paul Barsch is an employee of Teradata. Teradata is a sponsor of The Smart Data Collective.

In the article, Pariser cites an experiment by a doctoral student at Stanford where online shopping sites attempted to not only track clicks and items of interest, but also determine the best way to pitch a product. For example, pitches would alternate between an “Appeals to Authority”; as in someone you respect says you’ll like this product to “Social Proof”—everyone’s buying this product, so should you!

Taking a cue from the work completed by Dr. Robert Cialdini it appears that the next wave in recommendation algorithms is to learn our “decision triggers”, or the best way to persuade us to act. In his book “Influence: Science and Practice”, Cialdini documented six decision triggers of consistency, reciprocation, social proof, liking, authority and scarcity as mental shortcuts that help humans deal with the “richness and intricacy of the outside environment.” 

Getting back to the Wired Magazine article, Eli Pariser says this means that websites will hone in on the best pitch for a particular online consumer and –if effective—continue to use it.  To illustrate this concept, Pariser says; “If you respond a few times to a 50% off in the next ten minutes deal, you could find yourself surfing a web filled with blaring red headlines and countdown clocks.”

Of course, shoppers buy in various ways and not always in the same manner. However, the work of Robert Cialdini shows that in the messy and complicated lives of most consumers that mental shortcuts help with the daily deluge of information. Therefore, this new approach of recommendation systems using principles of psychology in tailoring the right way to “pitch” online shoppers, might just work.

There’s no doubt that recommendation systems already take into account principles of social proof and liking, but there’s a lot more room for improvement, especially other areas that Cialdini has researched. The answer to ‘why we buy’ is about to be taken to a whole new level.

 Questions:

  • What’s your take on this next development in recommendation systems? Benefit or too much “Big Brother”?
  • Are you moved by “act now” exhortations? What persuasion technique/s work best on you?

TAGGED: privacy, security, web analytics
paulbarsch April 26, 2011
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