Product Basket Analysis
Product Basket Analysis is one of the key techniques used by large retailers to uncover associations between items derived from customer purchasing patterns. It works by looking for combinations of items that occur together frequently in transactions.
It helps to formulate bundle of items to increase sale and customer satisfaction. By analysing POS data, retailers can optimize product placement, shelf arrangements, Up-sell, cross-sell, and bundling opportunities and customer retention.
A Grocery Store shared the transactional data with us. We have identified the most popular combos that can be suggested to the Grocery Store chain after a thorough analysis of the most commonly occurring sets of items in the customer orders.
The given dataset consists information regarding orders received by the grocery store for the period 01-01-2018 to 26-02-2020 against Order id with the product included in that Order id. The information is received for 20641 orders.
Why ACLYSIS ?
Even making a product combo is challenging. Traditional approaches require a significant amount of human labour, data engineering experience and statistical knowledge. Even non- technical teams can forecast values rapidly and economically by using this analytical podium.
In the parts that follow, we'll examine how to design the product bundle with the help of some matrices from a historical dataset by using our Auto Machine Learning platform.
A key use-case that affects the company's strategy for more attractive offers for the customers within their business principle.
Insights
- • 603 different orders have been placed involving 37 products / items within the time period 01-01-2018 and 26- 02-2020.
- • All products except ‘poultry’ are ordered within 500 & 600 times which indicates that the listed products are almost equally consumed. They are regular and necessary household items.
- • ‘Poultry’ is the most and ‘Hand Soap’ is the least ordered item.
- • There was no order during October to December in both the years (2018 & 2019). This indicates that the grocery shop remains closed / or not operating during last quarter of every year.
- • Count of Order increased in the month of March, May, July & August compare to their preceding months.
- • Weekly fluctuations are observed. Highest weekly order is in the last week of February 2018 followed by 1st week of March 2019.
Recommended Product Combos
