This case study tells the story of Victory Farms, one of the largest aquaculture operations in Africa. Focused on sustainable fish farming on Lake Victoria, it uses innovative digitally-driven sales strategies and a network of branches throughout Kenya that harness customer transaction data to offer more value to its customers, partners, and local communities.
The case has multiple parts. Part A provides an overview of the industry and the company, while subsequent parts describe various data-driven opportunities. Part B is about customer segmentation, and Part C presents a “buy now, pay later” credit offering.
The case is an effective vehicle to teach both the higher level elements of the ‘Agriculture 4.0’ revolution and the specific data-driven opportunities it presents.
Part B and C must not be used without Part A.
1. How to use unsupervised machine learning methods and data to make business decisions. 2. How to apply clustering techniques in relevant business applications, in particular for customer segmentation using customer transaction data. 3. Apply several machine learning methods for clustering. 4. How to profile customer segments produced from clustering techniques. 5. How to apply feature engineering in business decision making. 6. Use customer segmentation to derive business insights for sales & marketing strategy. 7. Implement various machine learning methods and customer segmentation modeling with code.
- Fish Farming
- Customer Segmentation
- Trade Credit
- Buy Now Pay Later
- Machine Learning
- Unsupervised Learning
- Feature Engineering
- Agriculture 4.0