Trade promotion optimization solutions & tools

SCIENTIFIC EVALUATION

Evaluate prices and trade promotion calendars

Traditional trade promotion planning relies on year-over-year comparisons, domain knowledge, and intuition. However, it provides very few guarantees with regard to the optimality of decisions. Predictive modeling provides more formal guarantees for price and trade promotion optimality, boosts financial outcomes, and streamlines the work process.

AUTOMATIC DATA DRIVEN OPTIMIZATION

Find new promotion opportunities

Predictive analytics can help not only with optimizing existing trade promotions but also with discovering completely new opportunities that are impossible to spot using traditional methods. Our solution can generate and analyze millions promotional scenarios and can identify the options with the best performance.

DATA-DRIVEN PERSONALIZATION

Personalize offers and trade promotions

Targeting and personalization can greatly improve the efficiency of offers and promotions. Our promotion management solutions can automatically determine the optimal audience, communication time, communication channel, and other parameters for each offer in real time. This enables in-session promotion personalization on ecommerce websites and real-time basket-based personalization at point of sales in retail stores. Up-selling has proved to be a business sales booster, and we can ensure the consumer gets the correct products based on the previous sales data that our TPO system collects.

MICRO-MOMENTS

Optimize offers in real time

Our AI-powered promotion optimization components dynamically personalize offers and promotions based on the customer profile, current web session, channel, and other factors. Real-time offer optimization based on price sensitivity and cart abandonment propensity greatly helps to improve conversion rates.

EXPLAINABILITY AND DIAGNOSTICS

Understand what drives sales

Our solutions for trade promotion optimization are based on complex forecasting models, but they provide comprehensive diagnostics information for business users. This information helps to understand the key factors that stand behind successful promotion campaigns. Examples of the factors that are typically estimated include in-category cannibalization, cross-category cannibalization, and pull-forward effects.

B2C and B2B promotions

Our solutions work for both B2C and B2B environments. We use methods that can process large amounts of clickstream data in B2C settings, and we use advanced techniques to handle sparse data in B2B setups. The complex data come in, but we manage it well to ensure your company has the most effective trade spend.

Comprehensive optimization

We provide a comprehensive toolkit to optimize the parameters of existing trade promotions, identify new promotion opportunities, and jointly optimize promotion calendars for entire categories. This ensures that the trade promotion optimization process truly helps to improve the business performance of the company, as opposed to only boosting selected metrics and negatively impacting related products and customer experiences.

Strategic and real-time decisions

We build tools that optimize promotion calendars for several months ahead, but we also develop components that can dynamically optimize and personalize promotions for micro-moment marketing. This enables the integration of smart price promotion management with online product catalogs, search engines, point of sale systems, and more. We ensure that all the data coming in your trade promotion system drive an increase in your sales.

Wide range of signals

We put considerable emphasis on data completeness and data quality. Our solutions for trade promotion optimization usually integrate with third-party data providers or include web scraping components to collect competitor pricing, information about the customer base, macroeconomic data, and more. Comprehensive data collection from your business sales along with market data from other companies helps to provide long-term sustainability and business growth.

Book

Introduction to Algorithmic Marketing

Would you like to learn more about the economic and algorithmic foundations of trade promotion optimization? We have published a 500-page book on enterprise data science that is available for free download, and there is an entire chapter on price and promotion management in it.

We develop trade promotion optimization solutions for customers from many B2B and B2C industries including retail, manufacturing, CPG, and video games

Retail

For retail customers, we create trade promotion optimization solutions that analyze promotion calendars, detect promotions that drive negative profits and need to be turned off, identify new promotion opportunities, and maximize the overall performance of a promotion calendar. The retailers we work with have a proven track record of optimizing promotion strategies using our TPO.

Manufacturing and CPG

Our decision support tools help manufacturers to optimize their B2B trade promotion planning and execution, ensure trade promotion consistency across retail partners, and directly integrate with digital channels and marketplaces such as Amazon.

Video Games

We help technology companies and video game publishers to understand their markets and the structure of the demand to optimize prices and promotions. We have extensive experience in handling international sales data and implementing trade promotion optimization for multiple countries, which is typically the case for technology and video game companies.

This article is a deep dive into dynamic pricing algorithms that use reinforcement learning and Bayesian inference ideas and that were tested at scale by companies such as Walmart and Groupon. We focus on the engineering aspects through code snippets and numerical examples
the theoretical details can be found in the referenced articles.

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 that were tested at scale by companies such as Walmart and Groupon. We focus on the engineering aspects through code snippets and numerical examples
the theoretical details can be found in the referenced articles.

This article is a deep dive into dynamic pricing algorithms that use reinforcement learning and Bayesian inference ideas and that were tested at scale by companies such as Walmart and Groupon. We focus on the engineering aspects through code snippets and numerical examples
the theoretical details can be found in the referenced articles.

Retail price modeling for replenishable and seasonal products

Predictive analytics for promotion and price optimization

We provide flexible engagement options to design and build your own trade promotion management solution. Contact us today to start with a workshop, discovery, or proof-of-concept (POC).

Workshop

We offer free half-day workshops with our top experts in price management and data science to discuss your pricing strategy, competition, profit margins, and opportunities for trade promotion optimization.

Proof-of-Concept

If you have already identified a specific use case that can be solved using data science or automated price management, we usually can start with a 4–8-week proof-of-concept project to deliver improvements and tangible results.

Discovery

If you are in the stage of requirements analysis and strategy development, we can start with a 2–3 week discovery phase to identify the correct use cases for price and promotion optimization, design your solution or product using industry best practices, and build a roadmap.

Customer intelligence and personalization

Anomaly detection

Supply chain optimization

Revenue and price optimization

Marketing spend optimization

Fraud detection and prevention

Grid Genie: open AI platform for conversational commerce

Voice applications

Analytical data platform