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PRIZM Clusters Not as Predictive as Behavior

Posted By Robert Gorell On August 30, 2007 @ 8:00 am In Metrics,Web Analytics | 1 Comment

Don't be fooled by the PRIZMOn his Marketing Productivity Blog [1], Jim Novo drills down into the misconception that PRIZM (define [2]) clusters can be more predictive than actual human behavior. A rare breed of marketer who understands both the statistical and behavior ends of the spectrum, Jim [3] explains the danger of distorting one’s vision by gazing only through the PRIZM:

[...] what is the likelihood these households reflect the overall “label” of the PRIZM cluster? Combine this with the fact that for customer analysis, demographics are generally descriptive or suggestive but not nearly as predictive as behavior and you have a bit of a mess.

Here’s a test for you. It only requires rough knowledge of your neighbors, so should not be very difficult (for most people!)

1. What is your “demographic”?
2. If you were to walk around the block and knock on doors, how many households would you find that are “in your demographic”?

Right. Maybe a handful, unless you live in a brand new housing development or other special situation. Now think about walking your zip code, or walking out 10 blocks or so from your house in any direction, and knocking on doors. Do you find most of these people are in the same demographic as you are? Did you ever find the “cluster average” neighbor? [Keep reading "PRIZM Clusters Not as Predictive as Behavior [1]"... ]

For a bit of background context, check out “The Marketing/Technology Interface [4],” where Jim discusses how the scientists among us are making it difficult for the
marketing folks to learn about using data by obscuring the actionable with the scientific. He pleas for “the technical side to be a little ‘less scientific‘ and the marketing side to be a little ‘more specific,’ so they can meet in the middle.

With all the talk of “engagement” as the elusive metric, chased by marketers and statisticians alike, it’s worth noting that Jim Novo & Bryan Eisenberg formulated it some 7 years ago in the Marketer’s Common Sense Guide to E-Metrics [5]. It’s just that back in them days, it didn’t have such an elegant name: “Scanning Visitor Share/Index/Volume” and “Committed Visitor Share/Index/Volume“.

I reckon “engagement” has a better ring to it.

Article printed from Conversion Rate Optimization & Marketing Blog | FutureNow: http://www.grokdotcom.com

URL to article: http://www.grokdotcom.com/2007/08/30/prizm-clusters-not-as-predictive-as-behavior/

URLs in this post:

[1] Marketing Productivity Blog: http://blog.jimnovo.com/2007/08/22/prizm-clusters/

[2] define: http://www.answers.com/topic/prizm-1?cat=biz-fin

[3] Jim: http://www.futurenowinc.com/bios.htm#Jim

[4] The Marketing/Technology Interface: http://blog.jimnovo.com/2007/08/10/marketing-technology-interface/

[5] Marketer’s Common Sense Guide to E-Metrics: http://www.cafepress.com/buy/marketing/-/pv_design_prod/p_storeid.8103777/pNo_8103777/id_3192874/opt_/pg_/c_/fpt_

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