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PoC - Retail

Commercial strategy

  1. Performance of individual categories
    1. Sales
    2. Margin
    3. Shrinkage
    4. # Customer buying product
    5. Quantity
  2. Implementation of CDT (customer decision trees)
    1. Categorization of database along CDTs
    2. Within leafs of the tree, for each product we need to see performance
      1. Sales
      2. Margin
      3. Shrinkage
      4. Quantity
  3. Products frequently bought together for cross-merchandising proposals
    1. Each 2 products (“square”)
    2. Each 3 products (“cube”)
  4. Promotions
    1. What percentage of basket comes from Promotions
    2. Which SKUs are most frequently bought in promotions
    3. Channel analysis (what works better, mouka for 8ckz or kinder for 8 czk)
  5. Price sensitivity
    1. Price sensitivity estimates (how to compute, how to drive, do you do for other clients?)
  6. Customer profile
    1. Age-group
    2. Income
    3. Children
    4. Size of family
    5. Business customers
    6. Frequency
    7. First-timers
    8. Regular customers (frequency of shopping)
    9. Loyalty
    10. Competitive behavior (are they shopping at iTesco?)
    11. Special needs, i.e. gluten free
    12. Acquisition channel
    13. … (what next?)
  7. Basket
    1. Price and quantity
    2. Category share (beer and chips, … )
    3. Promo-share
    4. Comparison with average basket
    5. Average price per SKU
    6. Preference for specific product group, i.e. exclusive range, brands, …
      1. How to categorize, lowest price point, A-brands, exclusive products?
  8. Segmentation
    1. How to drive?
    2. How to split into groups
      1. Manual rule-set
      2. AI Segmentation (e.g., K-Means algorithm, neural networks with backward learning)
  9. Suppliers
    1. Sales
    2. Margin
    3. Shrinkage
    4. Quantity
    5. Category share
  10. Competitive analysis 
    1. Price benchmarks against competition
    2. What else?
  11. What else?
  12. What did we forget to ask? 

Operations (warehouse)
  1. TBD 





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