What is Market Basket Analysis ?
It is a mathematical modelling technique based upon the theory that if a customer buy a certain group of items, they are likely to buy another group of items.
What is the use of Market Basket Analysis ?
It is used to analyse the customer purchasing behavior & helps in increasing the sales and maintain inventory by focusing on the point of sales transaction data.
Market Basket Analysis
- Allows us to identify patterns in customer purchases.
- MBA uses the information to:
- Identify who customers are (not by name)
- Understand why they make certain purchases
- Gain insight about its merchandise (products):
- Fast and slow movers
- Products which are purchased together
- Products which might benefit from promotion
- Take action:
- Store layouts
- Which products to put on specials, promote, coupons…
- Ideally, we would like to answer questions like
- What products tend to be bought together?
- What products may benefit from promotion?
- What are the best cross‐selling opportunities?
Example:
- One basket tells about what one customer purchased at one time.
- A loyalty card makes it possible to tie together purchases by a single customer (or household) over time.
Apriori Algorithm:
It is a level wise, breadth first algorithm which counts transaction to find frequent item sets & them derive association rules from them.
The following measures are used to evaluate the strength of association. Suppose, we are interested in the association between two events A and B:
- Support = (Number of Rows having both A & B)/(Total Number of Rows)
- Confidence = (Number of Rows having both A & B)/(Total Number of Rows with A)
- Expected Confidence = (Number of Rows having B)/(Total Number of Rows)
- Lift = Confidence/(Expected Confidence)
Analysis done for given data using Market Basket Analysis:
We had a data containing the purchasing behavior of the customer in which we did the following analysis:
Analysis 1: Top 5 related product:
Here we can know customers buying lhs products may also buy rhs products for example customers buying Instant food products & soda also buy Hamburger meat, people buying flour & baking powder also buy sugar, etc.
Analysis 2: Top 25 most frequently purchased items:
Analysis 3: Rules that lead to buying specific product(Milk):
- By this we can analyse that if a customer is buying Other Vegetables, rolls/buns, yogurt, root vegetables & tropical fruits then with that they prefer buying Milk mostly.
Analysis 4: Those who took particular product (‘milk’) also took:
- By this we can analyse that if a customer is buying Milk with that they prefer Other Vegetables, rolls/buns, yogurt, root vegetables & tropical fruits.
For any queries or any services (in Analytics) please contact us:
Nikhil Analytics (Nikhilguru Consulting Analytics Service LLP)
Contact No.: +91-(080)-42124127, +91- 9741267715, +91-9945339324
Email: dyutilal@nikhilanalytics.com, alokranjan@nikhilanalytics.com