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Customer cases
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Success stories of companies that transformed their pricing with Priceonix
150+ supermarkets across 16 cities in Kazakhstan.
Problem
✗ No unified, data-driven approach for local store pricing; limited ability to adapt prices to geographic and price clusters while protecting margin.
Pricerium Solution
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Dynamic pricing with store-level automation, competitor context, price rules/constraints by category/cluster/SKU, and process support for “indicator items” (KVI-like positions).
Outcomes
Delivered +8–10% gross income uplift for selected items/groups, with positive dynamics in revenue and penetration index on pilot vs control stores.
After broader use, a median gross income uplift >10% was reported for stores/categories under test (details limited by NDA).
A multi-country auto parts eCommerce business (pan-European operations; high order volume and a distributed warehouse network).
Problem
✗ Quantify the growth potential for sales and gross profit in key categories and understand demand drivers, taking into account competitor pricing, RRP, and private label strategy.
Pricerium Solution
ML discounts optimization combining transactional and behavioral data, competitor price/availability, RRP, and a vehicle compatibility catalog; ML modeling, elasticity estimation, and factor explainability.
Brand segmentation by response type: where to adjust the base price versus where to use targeted promo mechanics without diluting margin.
Outcomes
A quantified estimate of gross profit upside in selected categories, with identified key factors influencing margin and demand, gross margin improved up to 2,5M Euro.
A “carryover effect” was highlighted: timing matters—several smaller price cuts across different days can lift traffic more than one large cut “today”.
Noted that more granular linking of product views to purchases is needed for precise conversion/ROI calculations.
140 stores across Uzbekistan (supermarkets + convenience + wholesale + online delivery).
Problem
✗ Need to modernize pricing processes (regular + competitive + KVI baskets + events/revaluations) and assess automation potential and integration feasibility.
Pricerium Solution
Pilot of core modules: regular pricing, competitive pricing, basket/KVI management, pricing for new items & private label, optimization based on elasticity/probabilities, and event/revaluation management; plus assessment of labor reduction, human-error reduction, and SAP integration feasibility.
Outcomes
Pilot to more stores and Results were recognized as positive (details under NDA) and the retailer decided to scale the categories.
A large B2B player in the electrical market CIS with multi-channel sales (including a retail perimeter) with revenue more than 1,9Bln Euro annually
Problem
✗ A high share of negotiated (deal-by-deal) pricing; the need to account for multiple sales channels (direct B2B, distribution/DIY, project sales) and competitive dynamics while keeping governance and reducing transaction costs.
Pricerium Solution
Pricing methodology and “to-be” process design + a roadmap: methodology → architecture/specification → platform development and rollout.
Modeling framework: customer segmentation/clustering, price positioning and KVI, competitive dynamics, price list optimization by channel/segment, demand forecasting, contract & individualized pricing (WTP/risk, discount optimization).
Outcomes
Moving to dynamic, targeted individualized pricing: potential operating profit uplift up to 52%.
Gross profit uplift potential: up to 6% for regular pricing; and up to 15% for promo in mass channels (as design targets for the future system).
Reduced transaction costs: lowering the share of pricing that requires individual approvals from ~60% of turnover to 10–15%.
Average customer results
Key performance indicators for Priceonix implementation
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