Market Basket Analysis

Know your customers better & deliver what they want

Market Basket Analysis

Why retailers need to carry out market basket analysis

The science of identifying customer behavior, buying patterns, and finding the relationship between products and content delivery by the retailer inside the store or on their online shop is known as market basket analysis.

It helps in identifying target markets, getting, retaining, and growing customers through creating, delivering, and communicating a superior customer experience. Technically, it’s a combination of association rule mining techniques to identify frequent patterns, affinities, correlations or casual structure among different sets of items in the transactional database.

Our data scientists help you in identifying the right point of sale to maximize your profits. They will find out the products/items associations that have a good buying history to sell them together. They will create a customer profile based on their buying patterns to help you reach the right target market. Ultimately, this helps in predicting sales on the right time at the right place for the right customer.

Implementing market basket analysis for a supermarket chain

Our client is a supermarket chain in the U.S. and the company wanted to analyze different aspects of customer behavior inside the store. Softweb’s data scientists experimented with different sets of data to analyze customer behavior inside the chain’s stores and then classified it for defining the right product association, trip types, point of sale and marketing.

After analyzing consumer behavior inside the store, the next step was to apply modern data science techniques on different data sets. By applying association rule on gathered data our data scientists used different mathematical formulas to identify association between products/items, which is helpful in creating appropriate item sets.

Overall, the practice helps in finding frequent patterns, associations, correlations or casual structures among the set of items or objects in a transactional database. In our project, the Apriori algorithm was used which is the most popular algorithm when it comes to market basket analysis algorithms. It is used to create associations between the item sets.

Outcomes

  • As part of the deliverables, our team delivered inter-departmental co-occurrence graphs which show the relationship between different goods sold in the store.
  • Based on customer classification and segmentation that we implemented for the supermarket, it is easy for the store managers to assign the probabilities to each trip-type.
  • It is helpful in defining the right point of sale (POS), classifying product sets, trip type and the right marketing strategy inside the store.

How market basket analytics services can be used to boost retail businesses

  • Retailers can develop combo offers based on products sold together
  • Organize and place associated products/categories nearby inside the store
  • Optimize the layout of the catalog of an eCommerce site
  • Control inventory based on product demands and what products sell better together
  • Implement customer segmentation and create customer profiling based on their buying pattern
  • Classify different shopping trips for creating the best shopping experience
  • Finding the best product association
  • Creating more appealing product sets and identifying sales seasons and items
Let our data science team help you solve complex data and business problems