Shopping Basket Analysis

Ever since the computerization of point-of-sale systems, retailers have been collecting vast amounts of customer purchasing and behavior data. The problem is how to make sense of it all.  Traditional reports reveal item counts and amounts by store, region or channel.  But the challenge is to take it one step further – to identify relationships between products.  Plain and simple, POS data is only valuable if it can be quickly interpreted, analyzed and turned into action.

Wouldn’t it be great to know the answers to these questions?

  • If a customer purchases Product A, does it drive or indicate other purchases?
  • If the price of a Product A goes up or down, how does it impact the sales of Product B?
  • Knowing that a customer has purchased, or is in the process of purchasing, Product A, can an offer be made that will incent the customer to purchase additional products?  Or can up-sell or cross-sell opportunities be presented?
  • Each customer is unique and has different buying habits. Can an offer be customized to each customer?
  • How can less-frequently-purchased items be exposed to customers?
Shopping Basket Analysis is a technique that examines customer buying habits at the product and transaction level.  When each customer’s real or virtual shopping basket is analyzed, insightful and often unexpected buying patterns often emerge.  For example:

  • If man buys diapers, he is 90% likely to buy beer (but not the other way around)
  • 96% of people who bought hammers also purchased AA batteries.
  • 87% of customers over the age of 34 that purchased 100-watt light bulbs also purchased work gloves.
The patterns might also be obvious and reaffirm product grouping, but they can also test price elasticity:


Shopping Basket Analysis also can dynamically generate recommendations during an online shopping experience.  Using this technique, when a customer calls into a call center to place an order, the call center operator can present the customer with additional products, and even present product cross-sell and up-sell opportunities:

  • "People who have these same books/items in their cart also like these other books/items. Can I tell you about them?"
  • "I see that you purchased Product A, Product B and Product C. Might I recommend Product D?"
  • "I see that you are buying Product C. Can I offer you a 10% discount if you upgrade to Product X, if you buy it right now?"
Our Shopping Basket Analysis solutions give you a better, more in-depth understanding of your customers’ purchases and buying behavior, and deliver these benefits:

  • Customer segments can be created, and each customer segment can be identified by a set of attributes and their values.
  • Product groupings can be created to see what products sell together and what types of customers are buying within each group.
  • Because you know more about your customers’ needs and behavior, you can be more attentive, and make highly targeted offers.  The result is higher customer loyalty, and reduced attrition.
  • By offering different products, or giving promotions or discounts, you can increase customer satisfaction.
  • By having more insightful information about your customers and product groupings, store owners, planners and marketers can make smarter and better-informed decisions.
  • The ability to understand and calculate price elasticity can help determine the best price point for each product.
  • The ability to make precisely targeted offers, advertising and promotions can deliver improved marketing ROI
  • The ability to effectively incent new customers to visit your store/website