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Basket Analysis
Emcien Corporation

www.emcien.com

Emcien: ��Գ��𲹲��Բ��¾��ٳ��Basket Analysis

I came in to buy milk and I am walking out with 10 things in my basket.  The man
behind me had only one item in his basket.  “How do you do that?” I asked.  “It
depends on what you come in to buy,” he responded.

There are a few “seed items” in the store that drive additional sales because of key
concept ‘this is often bought with that’. These items are often found together in
customer baskets and orders.   Smart retailers will put these items as far away as
possible, so that you have to walk through more aisles to get from one item to the
other, in hope that you will buy more along the way.  Bread and milk is a good
example of that.  The reverse is also true. For items that are often bought together, if
the store does not carry both, they will lose the customer.

Every retailer knows that it is very profitable when a customer comes in to buy one
item, but ends up with many more in his basket.  Understanding the product
relationships in the market basket is key to driving up the order size or basket size.

Understanding the product relationships in the market basket is key
to driving up the order size or basket size. Adding one more item to
10% of the baskets can increase sales by 5%.

www.emcien.com                                                                                                    Page 2 of 6


Understanding the Customer Basket Makeup

A retailer typically carries thousands of items.  A small convenience store may carry
1,500 items.   A grocery store typically carries 15,000.  And the super stores like
Wal‐Mart and Targets carry well over 25,000 SKUs in each store.

The SKU management is a tremendous challenge because the buying pattern is truly
a long tail.  Retailers know their top sellers; these are easy to identify, but the
frequency of buying falls of very sharply.

The chart shows an example of one retail store operation over a 3‐month period.
The store carries 25,000 SKUs, has 100,000 transactions per month.  The analysis
covers a 3‐month period, and shows the distribution and popularity of SKUs based
on the frequency of purchase.   Here are a few quick facts:

 The most popular SKU has a frequency of 3,435. That means is has
been bought in 3,435 baskets.
 The frequency of the 100th most popular item drops off to 225. That
means it is only in 225 baskets over the 3‐month period.
 There are 4,000 SKUs that are bought only once.
 But the really interesting fact is that 1,800 SKUs are bought together
98% of the times.



 None of these 1,800 SKUs are top sellers!  But when they are
purchased, they are very often paired with other items.

This level of SKU intelligence is key to increasing basket size and ensuring the store
is carrying the right items.

There basket analysis also showed the low‐frequency/high‐correlation SKUs.  Every
retailer knows the challenge with these items. These items sell rarely, they sit on the
shelf for along time, and when it is placed in a basket it will only sell if the paired
item is available!  These are problem SKUs because they are capital hogs and always
show up in inventory issues.

The SKU management is a tremendous challenge because the
buying pattern is truly a long tail.



Opportunity to increase order size

Insight into the basket make‐up and the product affinities based on buying behavior
is key to merchandising and increasing order size.   Merchandizing, up selling, cross
selling and add‐ons based on buying behavior results in increased sales and
enhanced customer experience.   On the other hand, suggestive selling based on
tribal knowledge and ‘he said/she said anecdotes’ will result in poor results and loss
of customer good will.

The basket size or order size analysis shows the revenue potential of increasing the
order size.  The chart shows a typical basket size analysis and the upside
opportunity of increasing order size.   The results from this case study showed that
adding one more item to 10% of the baskets can increase sales by 5%.



Quick review of definitions:

Frequency – Number of orders that contain this item

Volume – Number of items sold.

The volume of an item may be high because one customer bought a lot. However,
frequency is better measure because it measures the popularity across many
purchases, and is not skewed by a one‐time large volume sale.

About Emcien

Emcien provides Pattern Based Analytics that takes your sales data and
automatically reveals what choice combinations your customers are buying.
Emcien’s software‐as‐a‐service solution eliminates the need for data models and can
be deployed instantly, increasing your sales and revenue. To learn more, visit
www.emcien.com


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