Market basket analysis scrutinizes the products customers tend to buy together, and uses the information to decide which products should be cross-sold or promoted together. The term arises from the shopping carts supermarket shoppers fill up during a shopping trip.
Association Rule Mining is used when we want to find an association between different objects in a set, find frequent patterns in a transaction database, relational databases or any other information repository.
The most common approach to find these patterns is Market Basket Analysis, which is a key technique used by large retailers like Amazon, Flipkart, etc to analyze customer buying habits by finding associations between the different items that customers place in their “shopping baskets”. The discovery of these associations can help retailers develop marketing strategies by gaining insight into which items are frequently purchased together by customers. The strategies may include:
- Changing the store layout according to trends
- Customers behavior analysis
- Catalog Design
- Cross marketing on online stores
- Customized emails with add-on sales, etc.
08/08/2021
This project is geared towards determining products that are to be shelved in the stores, or advertised online, and products that may be shelved together given that these products are historically purchased together.
AHG Relational Database
I am using apriori and association rules to frame a solution structure for the problem and I come up with a robust methodology for separating and dealing with the problems components.
I Carry out problem domain evaluation through extensive data discovery, highlighting where the areas of focus must be and propose action steps and gain buy-in from your my analytics lead in Kernel Limited.
We expect a great progress and quick change in market penetration and revenue in online shops.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent