{"id":1144,"date":"2010-05-31T10:01:22","date_gmt":"2010-05-31T14:01:22","guid":{"rendered":"http:\/\/mat.tepper.cmu.edu\/blog\/?p=1144"},"modified":"2010-05-31T10:01:22","modified_gmt":"2010-05-31T14:01:22","slug":"optimizing-discounts-with-data-mining","status":"publish","type":"post","link":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/2010\/05\/31\/optimizing-discounts-with-data-mining\/","title":{"rendered":"Optimizing Discounts with Data Mining"},"content":{"rendered":"

The New York Times<\/em> has an article today about tailoring discounts to individuals<\/a>.\u00a0\u00a0\u00a0 They concentrated on Sam’s Club<\/a>, a warehouse chain.\u00a0 Sam’s Club is a good place for this sort of individual discounting since you have to be a member to shop there, and your membership is associated with every purchase you make.\u00a0 So Sam’s Club has a very good record of what you are buying there.\u00a0 (In fact, as a division of Walmart Stores, perhaps Sam’s has an even better picture based on the other stores in the chain, but no membership card is shown at Walmart, so it would have to be done through credit card or other information.)<\/p>\n

The article stressed how predictive analytics could predict what an individual consumer might be interested in, and could then offer discounts or other messages to encourage buying.<\/p>\n

Given how many loyalty cards I have, it is surprising how few really take advantage of the data they get.\u00a0 Once in a while, my local supermarket seems to offer individualized coupons. \u00a0 Barnes and Noble and Borders seem to offer nothing beyond “Take 20% of one item” coupons, even though everything in my buying behavior says “If you hook me on a mystery or science fiction series, I will buy each and every one of the series, including those that are only in hardcover”.<\/p>\n

Amazon does market to me individually, seeming to offer discounts that may be designed for me alone (online retailers can hide individual versus group discounts very well:\u00a0 it is hard to know what others are seeing).<\/p>\n

For both Sam’s and Amazon, though, I would be worried that the companies would be using my data against me.\u00a0 If the goal is to optimize net revenue, any optimal discounting scheme would have the following property:\u00a0 if I am sufficiently likely to buy a product without a discount, then no discount should be given.\u00a0 The NY Times article had two quotes from customers:<\/p>\n

\u201cThere\u2019s a dollar off Bounce. I use that all the time.\u201d<\/p><\/blockquote>\n

and<\/p>\n

\u201c[A customer]\u00a0 said the best eValues deal yet was $300 off a $1,200 television.<\/p>\n

\u201cI remember that day,\u201d he said later. \u201cI came to buy food, and I bought two TVs.\u201d<\/p><\/blockquote>\n

The second story is a success for data mining (assuming the company made a profit off of a $900 TV):\u00a0 the customer would not have purchased without it.<\/p>\n

In the first first story, the evaluation is more complicated:\u00a0 if she really was going to buy Bounce anyway, then the $1 coupon was a $1 loss for Sam’s.\u00a0 But consumer behavior is complicated:\u00a0 by offering small discounts on many items, Sam’s encourages customers to buy all of their items there, not just the ones on discount.\u00a0 So the overall effect may be positive.\u00a0 But optimal discounting for these sorts of interrelated items with a lifetime environment is pretty complicated.<\/p>\n

But here is a hypothetical situation (presumably):\u00a0 it turns out that 25 year olds (say) are at a critical point in purchasing behavior when they decide exactly what brands they will purchase for the rest of their lifetime;\u00a0 50 year olds are set in their ways (“I always buy Colgate, I never buy Crest”).\u00a0 A 25 year old goes into Sam’s, hits the kiosk and walks away with 10 pages of coupons;\u00a0 a 50 year old gets nothing.\u00a0 Is this a success for data mining?\u00a0 Perhaps the answer depends on whether you are 25 or 50!<\/p>\n

And, more importantly for me, does Amazon not give me discounts once it is sufficiently certain I am going to want a book?<\/p>\n","protected":false},"excerpt":{"rendered":"

The New York Times has an article today about tailoring discounts to individuals.\u00a0\u00a0\u00a0 They concentrated on Sam’s Club, a warehouse chain.\u00a0 Sam’s Club is a good place for this sort of individual discounting since you have to be a member to shop there, and your membership is associated with every purchase you make.\u00a0 So Sam’s … Continue reading “Optimizing Discounts with Data Mining”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15,39],"tags":[],"class_list":["post-1144","post","type-post","status-publish","format-standard","hentry","category-data-mining","category-or-in-the-press"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1144","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=1144"}],"version-history":[{"count":0,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1144\/revisions"}],"wp:attachment":[{"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mat.tepper.cmu.edu\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}