Our omni-channel price management solutions help leading retailers to optimize promotions, personalize offers, and prevent profit loses.

Use cases

Strategy

Optimize your pricing strategies

We provide tools that help to optimize price and promotion strategies for each product based on various factors such as price sensitivity, profitability, and the stage of the life cycle. These tools are backed by advanced machine learning models that can evaluate different pricing strategies even for new and slow-moving products.

Planning

Evaluate promotion calendars, stop losses

Our tools are able to evaluate price and promotion plans for individual products, product groups, and categories, taking into account complex factors and effects such as cannibalization, halo, and pull-forward. Evaluation models are able to produce both short- and long-term demand, revenue, and profit forecasts that further guide the price setting process. The forecasting and evaluation models are further combined with various solvers to optimize prices for replenishable and seasonal products and to detect new promotion opportunities.

Execution

Enable dynamic pricing

We build best-in-class price management models that incorporate competitor pricing, historical sales data, inventory constraints, and many other factors to autonomously optimize pricing. These models can be directly integrated with digital channels and marketplaces to perform price optimization in real time.

Execution

Personalize offers in real time

We provide offer and promotion personalization components that help to increase customer engagement and reduce cart abandonment rates using real-time scoring techniques. These models account for customer demographic and behavior data, product and customer similarities, and many other factors to determine optimal prices and offer decisions.

Execution

Integrate with marketplaces

Our algorithmic price management solutions support integration with major marketplaces such as Amazon and other 3rd parties to optimize prices dynamically through marketplace APIs.

Measurement

Understand your ROI

ROI measurement in B2C environments is complicated because of various cross-product effects such as cannibalization and halo. We use advanced machine learning methods to quantify these effects and make the necessary corrections in ROI estimates. This helps to produce trustworthy reports and avoid misleading results.

Our clients

Retail
Hi-tech
Manufacturing
Finance

How our price optimization software works

Data collection and extrapolation
Our price optimization pipeline usually starts with advanced data collection components and extrapolation models that help to improve catalog coverage even for slow-moving and new products.
Advanced planning tools
We use state-of-the-art demand forecasting models that account for complex effects such as cannibalization and halo. These models are integrated with convenient interfaces for strategic analysis and scenario planning.
Personalization models
We provide a comprehensive set of propensity models that help to dynamically determine optimal offers and discounts, accounting for both profitability and customer satisfaction metrics.

How to get started

We provide flexible engagement options to help you build B2C price optimization solutions faster. Contact us today to start with a workshop, discovery, or proof of concept.

Get in touch

If you have any additional questions, please feel free to reach out to our experts directly

Learn more about price optimization techniques

A guide to dynamic pricing algorithms
This article is a deep dive into dynamic pricing algorithms that use reinforcement learning and Bayesian inference ideas and were tested at scale by companies such as Walmart and Groupon. We focus on the engineering aspects through code snippets and numerical examples; theoretical details can be found in the referenced articles.
Read more
Retail price modeling for replenishable and seasonal products
In this article, we discuss the common process retailers use to set pricing, the challenges they face in the area of price management, and how they incorporate big data analytics and machine learning into their pricing strategies.
Read more
Predictive analytics for promotion and price optimization
Pricing decisions are critical for any business, as pricing is directly linked to consumer demand and company profits. In this blog post, we demonstrate a reference implementation of a price management tool for effective price optimization using AI and machine learning methods.
Read more
Read more on price optimization

Would you like to learn more about algorithmic foundations of price optimization and revenue management? We published a 500-page book on enterprise data science and machine learning that is available for free download, and there is a whole chapter on price and promotion management in it.

Read more on advanced revenue analytics and optimization

This white paper describes the functional design of a price intelligence platform that extensively uses data science and machine learning methods to provide state-of-the-art decision support and decision automation capabilities. This white paper covers the following aspects of pricing analytics and revenue management:

  • Advanced decision support systems for strategic pricing analytics.
  • Predictive and prescriptive analytics for the optimization of pricing actions.
  • Automatic decision-making components for near real-time and personalized price optimization.
  • Advanced statistical analysis for the measurement and decomposition of observed sales and demand data.

We have made this report publicly available to help practitioners create sound price optimization strategies and implement effective price optimization models and tools.

Events

Grid Dynamics is an organizer of Data Points Summit, a leading regional conference on data science, enterprise AI, and data engineering.
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