Facebook Ad Optimization: Ad Clustering

Posted by bkloss | facebook | Monday 4 May 2009 2:10 pm

This is the second post of my Facebook ad serving optimization article.  If you haven’t read my first post in the series , check it out here for a fleshed out version of the problem statement. To recap, we are looking at the problem of identifying Facebook ads that are misspecified, then giving marketers a gentle nudge to help them get the highest CTR.  This post employs text mining to discover similar ad groups.  This would provide Facebook with a basis of comparison to determine if an ad is not optimally targeted.

Ad Text Clustering

The first step to correcting over targeting would entail identifying similar ad groups.  Once these groups are identified, Facebook can then amass demographic and response data into a large data set for later analysis.

Ads are composed of text and pictures describing a product or service.  To evaluate the worth of ad clustering based on textual attributes, a sample of 47 distinct Facebook ads were copied from search result pages.  SAS Enterprise Miner (EM) was used to create and describe ad clusters.  Below is an outline of the text clustering process flow:

This is an upper level overview of the text mining process

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Creating a Cartesian Product in SAS

Posted by bkloss | SAS | Friday 13 February 2009 6:49 am

Here’s the first of several question/answer posts.

Feel free to write me with your SAS question and I’ll provide the answer in a post.

Question

Suppose I have two SAS datasets, set A contains 5 variables having 3000 unique records and set B contains just 1 variable having 500 unique records (just a bunch of ID numbers). Suppose I would like to create a new dataset where each of the records from set A would be duplicated so that the first record would be repeated 500 times where each of those would be paired with a unique ID from set B. The goal is to have the new dataset with 6 variables (the five from A and the one from B) containing a total of 1,500,000 records produced in this way.

Any help or suggestions you can provide is greatly appreciated.

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GeoSpatial Analytics Gallary

Posted by bkloss | Geospatial Analytics | Monday 1 December 2008 6:54 pm

One of the most difficult, yet rewarding, parts of my job is communicating complex analysis results in a compelling, intuitive manner.   Often times, numbers are not enough.  Instead, you need a visual representation to hammer home your main points and insights to upper level stakeholders.

GeoSpatial analytics is on a meteoric rise because of its ability to do just that. Look no further than the flashy touch screen maps used by CNN during the election to convey numeric data in a sticky fashion.

Please enjoy a gallery of my most recent visualizations below.   Feel free to ask questions if you would like to know how any of these maps were produced. (click any image to see a slideshow).


Tools Used

ArcGIS, SAS/Base, Excel, SAS Bridge