Databases Reference
In-Depth Information
On-Line versus Brick-and-Mortar Retailing
We suggested in Section 3.1.3 that an on-line retailer would use similar-
ity measures for items to find pairs items that, while they might not be
bought by many customers, had a significant fraction of their customers
in common. An on-line retailer could then advertise one item of the pair
to the few customers who had bought the other item of the pair. This
methodology makes no sense for a bricks-and-mortar retailer, because un-
less lots of people buy an item, it cannot be cost effective to advertise a
sale on the item. Thus, the techniques of Chapter 3 are not often useful
for brick-and-mortar retailers.
Conversely, the on-line retailer has little need for the analysis we dis-
cuss in this chapter, since it is designed to search for itemsets that appear
frequently. If the on-line retailer was limited to frequent itemsets, they
would miss all the opportunities that are present in the “'long tail” to
select advertisements for each customer individually.
checkout. Here the “items” are the different products that the store sells, and
the “baskets” are the sets of items in a single market basket. A major chain
might sell 100,000 different items and collect data about millions of market
baskets.
By finding frequent itemsets, a retailer can learn what is commonly bought
together. Especially important are pairs or larger sets of items that occur much
more frequently than would be expected were the items bought independently.
We shall discuss this aspect of the problem in Section 6.1.3, but for the moment
let us simply consider the search for frequent itemsets. We will discover by this
analysis that many people buy bread and milk together, but that is of little
interest, since we already knew that these were popular items individually. We
might discover that many people buy hot dogs and mustard together. That,
again, should be no surprise to people who like hot dogs, but it offers the
supermarket an opportunity to do some clever marketing. They can advertise
a sale on hot dogs and raise the price of mustard. When people come to the
store for the cheap hot dogs, they often will remember that they need mustard,
and buy that too. Either they will not notice the price is high, or they reason
that it is not worth the trouble to go somewhere else for cheaper mustard.
The famous example of this type is “diapers and beer.” One would hardly
expect these two items to be related, but through data analysis one chain store
discovered that people who buy diapers are unusually likely to buy beer. The
theory is that if you buy diapers, you probably have a baby at home, and if you
have a baby, then you are unlikely to be drinking at a bar; hence you are more
likely to bring beer home. The same sort of marketing ploy that we suggested
for hot dogs and mustard could be used for diapers and beer.
