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What is Market Basket Analysis?
Market Basket Analysis (MBA) is a data mining technique used to identify patterns and relationships between products that customers frequently purchase together. It helps businesses understand buying behaviour and optimize product placement, cross-selling, and promotions.
Definition
Market Basket Analysis is a statistical method that evaluates co-occurrence patterns in transaction data to determine which items are commonly bought together.
Key Takeaways
- Identifies links between products in customer transactions.
- Improves cross-selling and product bundling strategies.
- Uses association rules and support, confidence, and lift metrics.
Understanding Market Basket Analysis
Market Basket Analysis is commonly used in retail and e‑commerce. By analyzing purchase data, businesses can uncover associations such as:
- Customers who buy bread often buy butter.
- Shoppers purchasing pet food frequently buy cat litter.
This is done using association rule learning, typically with the Apriori or FP‑Growth algorithms.
Key metrics include:
- Support – Frequency of an itemset.
- Confidence – Probability that customers buy item B when they buy item A.
- Lift – Strength of the association compared to random chance.
Formula (If Applicable)
Support(A → B):
Support = (Transactions containing A and B) ÷ (Total transactions)
Confidence(A → B):
Confidence = Support(A and B) ÷ Support(A)
Lift(A → B):
Lift = Confidence(A → B) ÷ Support(B)
Real-World Example
A supermarket discovers through Market Basket Analysis that shoppers who buy pasta frequently also buy tomato sauce. As a result, they bundle these items or place them near each other to increase sales.
Importance in Business or Economics
Market Basket Analysis helps businesses:
- Increase average order value (AOV)
- Improve store layout and product placement
- Design effective promotions and coupons
- Enhance personalization in e‑commerce
Types or Variations
- Association Rule Mining
- Sequential Pattern Mining
- Affinity Analysis
- Collaborative Filtering (related)
Related Terms
- Data Mining
- Customer Insights
- Cross-Selling
Sources and Further Reading
- IBM Analytics – Market Basket Analysis: https://www.ibm.com
- SAS – Association Analysis: https://www.sas.com
- Investopedia – Market Basket Analysis: https://www.investopedia.com
Quick Reference
- Identifies which products are purchased together.
- Relies on association rule learning.
- Drives cross-selling and product optimization.
Frequently Asked Questions (FAQs)
Is Market Basket Analysis only for retail?
No, it is used in banking, telecom, healthcare, and e‑commerce.
What algorithm is commonly used?
Apriori and FP‑Growth.
Does Market Basket Analysis require big data?
It works best with large transactional datasets but can be applied to smaller ones.
