Product clustering: The system automatically clusters products based on elasticity, weighted average price and turnover.

Role-based pricing strategy: It assigns a pricing strategy according to each product’s role in the assortment:

• Traffic driver – products with the highest sales in each category
• Promo support – highly elastic products sold only during promotions
• Perception driver – elastic products with strong regular sales
• Profit generator – inelastic products with lower prices and moderate sales
• Profit enhancer – expensive, inelastic products with occasional sales

The algorithms also identify Key Value Items (KVI), Back Basket and Long Tail products, and are adaptable to the First Price and Private Label contexts.
BaOne’s approach involves joint clustering of product and store, where the same SKU can serve different roles at different locations and should be priced accordingly.

Price optimization: Prices are adjusted up or down to reach optimal levels, in line with KPIs.

Constraint management: The system respects essential constraints, including:

• Relationships within horizontal and vertical product lines
• Limits on one-off price adjustments under specific pricing strategies
• Thresholds that prevent minor, non-impactful price changes
• Rounding rules
• Quotas for price tag updates
• Government-imposed price controls on socially significant goods

Competitive price positioning: The system fine-tunes pricing relative to competitors using:

• Macro-level data – market-wide insights (e.g., from Nielsen)
• Local competitor data – rivals present in each store’s catchment area

B1 Pricing’s algorithms clean and refine competitor price data, factoring in each rival’s weight in the pricing model. Clustering can be at different levels of granularity, e.g., chain, region, store group, or outlet. Using external inputs, the system refines its understanding of elasticity and adjusts for any inconsistencies in historical data.

Maximizing revenue and margin at store level: The algorithm automatically identifies SKUs with similar demand patterns by analyzing price ranges and market clusters. Each step of the pricing process is visible in the user interface, with the option to fine-tune the algorithm when needed.