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From Source to Shelf, a Round Up of Retail AI Innovation

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Price Optimization

The right price at the right time – automatically

  • 15%

    improved revenues

  • 5%

    improved profits

  • 20%

    stock levels reduction

  • Automating price adjustments
  • Optimizing high-level KPIs
  • Decreasing write-off rates
  • Increasing competitiveness

Why Price Optimization?

Blue Yonder Price Optimization is a machine learning solution that delivers retailers optimized pricing decisions for every product while improving revenue and profit by more than 5%. Ready for automation and scale, the solution measures the relationship between price changes and customer demand while incorporating a retailer’s business strategy.

Whether in grocery or fashion retailing, pricing is the core strategic component affecting a company's profitability. Price Optimization automatically sets the optimal prices to deliver the best bottom line for retailers.

Considering competitors’ prices and other factors, including weather and inventory levels, our solution rapidly reacts to changes in the market and adjusts prices automatically to each product and store. Price Optimization serves your greater pricing strategy and provides a measurable impact and return on investment in a short period of time.


Base Pricing for Online Retailers


Retailers currently face fierce competition, with rising online players taking over a big chunk of the market. In order to stop declining sales and falling profits, retailers must carefully look at a their base pricing strategy.

  • Increased competition, mostly from online retailers
  • Deciding which prices should follow competition trends
  • Optimized pricing, which accurately calculates how external factors such as competition affect the price elasticity per product
  • A strategic price optimization, depending on the desired business strategy, e.g. focus on revenue and/or profits
  • Retailers experience up to 5% improvement in profits and revenue lifts of up to 15%
  • Fast return on investment

Markdown for Fashion Retailers


With new trends rapidly changing market dynamics, accurately forecasting demand can allow fashion retailers to improve inventory levels as well as avoid costly price discounts during seasons´ end.

  • Price optimization covering the whole markdown phase at seasons´ end
  • Synching inventory levels, inventory costs and pricing decisions
  • Positive impact on profit figures for products in markdown phase
  • Up to 20% reduction in stock levels during markdown

Pricing in Omnichannel


Challenge: New channels open new opportunities for retailers, but a consistent pricing strategy across online and brick and mortar can deliver a seamless and profitable customer experience.

  • No silo optimization on e-commerce or brick and mortar, but a true cross-channel price optimization
  • The optimization considers cost differences across channels
  • Overall improved revenue and profit figures
  • Ensuring price consistency for a better customer experience

How Does Blue Yonder Price Optimization Work?

Highlights of Our Solution

  • Scientific optimization based on machine learning instead of a a rule-based system. Our scientific price optimization is based on machine learning instead of preset rules or hypotheses, making it more accurate and able to rapidly adapt to market changes
  • Price optimization covers thousands of products at SKU/store level on a daily basis
  • Serving a customizable pricing strategy and strategic KPIs such as revenue or profit.

Customers Using Blue Yonder Price Optimization

Some book

How OTTO automates its pricing and increases sales and revenue

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Price Optimization: Delivering automated pricing decisions daily for grocery retailers

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Data sheets

Price Optimization for E-Commerce

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Data sheets

Price Optimization for Brick and Mortar

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McKinsey: The Secret to Smarter Fresh Food Replenishment? Machine Learning

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Fashion's New Rules for Pricing

4 global fashion insights that prove smarter pricing leads to higher profits

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