Pricing isn’t just a business function; it’s a strategic powerhouse. Research shows that even a 1% improvement in pricing can boost operating profits by 11%. Yet, most mid-market companies struggle with inconsistent strategies, market fluctuations, and discount variability. The future lies in elevating Pricing Analysts into Revenue Management Analysts—strategic professionals who leverage advanced analytics to drive holistic growth and profitability.

Achieving sustainable revenue growth means moving beyond traditional approaches and embracing advanced analytics, AI, and machine learning. These tools empower businesses to refine pricing, boost sales effectiveness, and make promotions more impactful—all in alignment with their strategic goals.

By embedding a culture of analytics within their organization, companies not only harness data-driven insights to make informed decisions but also foster agility, positioning themselves as proactive market leaders who drive profitability and stay ahead of shifting customer demands.

As market pressures intensify, distributors are increasingly challenged to maintain profitable growth. Traditional strategies often fall short in today’s volatile landscape, leaving many distributors grappling with price realization gaps, customer churn, and missed cross-selling opportunities.

This whitepaper explores how AI/ML-enabled Revenue Growth Management (RGM) strategies can address these issues, providing a comprehensive guide to leveraging advanced analytics for sustainable growth. With actionable insights into dynamic pricing, customer retention, and data integration, this resource empowers distribution leaders to navigate complex growth obstacles and build resilient, data-driven strategies for the future.

A solid pricing strategy can be the key to gaining market share and fueling business growth.

Competitive pricing, when done right, goes beyond just undercutting competitors. It's about strategically positioning your products to maximize market share, maintain profitability, and align with long-term business goals.

For example, a premium skincare company successfully used price skimming to launch a high-end anti-aging cream at a premium price, capturing early adopters and reinforcing brand exclusivity. Later, they strategically lowered prices to attract broader market segments.

This article'll explore how competitive pricing works, discuss real-world implementation strategies, and examine how it fits within a broader Revenue Growth Management (RGM) framework. We'll also weigh the pros and cons, ensuring you have the tools to craft an effective pricing strategy that drives sustainable growth.

The distribution industry faces unprecedented challenges—market saturation, heightened competition, and changing customer expectations—that are stifling growth and profitability. While Artificial Intelligence (AI) and Machine Learning (ML) are often hailed as game-changers, their true value lies in strategic, practical applications.

This blog explores how distributors can leverage AI/ML to optimize pricing, retain customers, and capitalize on cross-sell opportunities. By addressing key issues such as price realization gaps, customer churn, and missed revenue opportunities, distributors can overcome growth headwinds and accelerate profitable growth.

Discount strategies play a critical role in driving sales and maintaining profit margins in retail. Finding the right balance between offering discounts to attract customers and protecting profitability is key.

This guide covers different discount tactics like Premium Pricing and High-Low Pricing, showing how they influence consumer behavior and brand perception. You'll also learn about common mistakes like excessive discounting and how pricing psychology impacts buying decisions. Whether you need to clear inventory or boost customer loyalty, this article provides practical strategies to use discounts effectively while sustaining growth.

Understand the power of value-based pricing strategies in driving profitability. Learn how aligning price with perceived customer value can boost revenue, and profits and strengthen customer relationships.

By focusing on what customers are willing to pay based on the unique benefits they perceive, businesses can create tailored pricing models that not only increase competitiveness but also foster brand loyalty. Explore key examples, strategic implementation techniques, and the long-term advantages of adopting a value-based approach to maximize growth and profitability.

Dynamic pricing has evolved from a niche concept into a fundamental capability for both B2C and B2B businesses seeking to optimize profits and remain competitive in a market characterized by increasing volatility and data proliferation. By adjusting prices in real-time (or near real-time, like daily or weekly batches) based on factors like market demand, customer behavior, social media sentiment, and inventory levels, companies can respond much faster to fluctuations and preferences. 

As pricing consultants with decades of combined experience, we’ve witnessed firsthand how dynamic pricing can significantly impact Operating Profits and pricing team productivity. In this article, we'll explore the nuances of dynamic pricing, exploring its various models, industry applications, best practices for implementation, challenges, ethical considerations, technological requirements, and future trends. 

With AI/ML at the center of current and future commercial capabilities, understanding dynamic pricing is essential for driving growth, driving positive price perception, and augmenting customer satisfaction.

Private equity firms can unlock significant value by integrating robust Pricing & Revenue Growth Management strategies both before and after acquisitions.

From AI-driven market analysis to post-acquisition margin optimization, these initiatives empower investors to boost profitability, increase valuations, and maintain a competitive edge. Our latest blog explores how in-sourcing these capabilities can help private equity firms maximize portfolio returns and long-term growth potential.

Price optimization is crucial for maintaining profitability and ensuring customer satisfaction. Our latest article, 'A Brief Guide to Price Optimization: Strategies, Tools, and Best Practices,' provides practical insights into implementing data-driven pricing strategies.

Learn how to effectively apply dynamic pricing, value-based approaches, and competitive analysis to enhance revenue and support sustainable business growth. This brief guide offers a clear overview of the essential tools and techniques needed to navigate the complexities of modern pricing.

For retailers and distributors, keeping customers happy and engaged is more critical than ever. But did you know that 6 out of 10 mid-market firms lack the tools to predict churn or identify upsell/cross-sell opportunities?

Our latest article dives into how AI/ML is revolutionizing customer retention. Learn how to leverage these technologies to:

• Predict and prevent churn with advanced analytics.

• Identify personalized upsell/cross-sell opportunities.

• Tailor marketing campaigns for maximum impact.

• Build stronger customer relationships through personalization at scale.

Read the full article to discover how to build an insights-driven retention strategy that maximizes customer lifetime value and drives sustainable growth for your company.

Enhanced by AI and machine learning, price elasticity modeling enables businesses to optimize pricing strategies by understanding how customer demand reacts to price changes. Unlike traditional methods that often overlook the complexities of consumer behavior, these advanced models provide data-driven insights to set prices that maximize revenue.

Mid-market manufacturing businesses often struggle with accurate demand predictions due to evolving customer preferences and changing market trends. This complicates stock management and necessitates innovative strategies to reduce waste.

Advanced AI/ML-enabled demand forecasting can significantly improve capacity planning, financial planning, and profit margins by enhancing forecast accuracy. Traditional methods, relying on outdated data and gut instinct, fall short, while AI/ML technologies analyze vast data sets to identify patterns and adapt to dynamic market conditions.

Many mid-market retailers and wholesalers' pricing, finance, and merchandising executives have inherited outdated pricing solutions. These legacy pricing processes don't quickly scale and heavily rely on expensive human, mundane tasks. There are no intelligent dynamic pricing capabilities that automatically set prices based on sales patterns, corporate objectives, and changing marketplace behavior. It often results in missed profit opportunities and liquidity problems.

Fortunately, you can build simple yet effective dynamic pricing solutions in 3-to 4 months that achieve up to 80% of its incremental Gross Profit $ potential. You can design and implement using practical methods and accessible technologies that empower your teams to take complete control without expensive 3rd party support.

Read more below about how you can achieve this and unlock an extra 1-3% in GP% in year 1.

Unlock the full potential of your sales and marketing teams with AI-driven tools! Discover how artificial intelligence can revolutionize your business by streamlining processes, enhancing customer engagement, and boosting performance. Learn about top AI tools for lead generation, sales forecasting, and campaign optimization. Find out how predictive analytics can forecast demand and automate routine tasks, freeing up time for strategic activities. Get practical tips for selecting and integrating AI tools seamlessly into your workflows. Stay ahead of the competition and drive business growth with AI. Read more now!

Revenue Growth Management (RGM) is often mistakenly equated solely with pricing strategies. However, true RGM encompasses a broader scope, leveraging comprehensive commercial analytics to drive business growth across multiple dimensions.

Beyond pricing optimization, RGM integrates advanced metrics and analytics efforts such as Customer Acquisition Cost, Lifetime Value, Churn Rate, Marketing ROI, and Net Revenue Retention to provide a holistic view of revenue and profit opportunities.

By analyzing these diverse data points, companies can unlock insights that lead to improved customer segmentation, targeted marketing campaigns, optimized product and customer mix, and enhanced operational efficiencies.

Companies that expand their RGM focus beyond pricing are better positioned to identify untapped revenue streams, boost profitability, and achieve sustainable growth in an increasingly competitive and insights-driven marketplace.

Manufacturers need more than great products to stay competitive—they need deep customer understanding and smart decision-making. Traditional methods like Excel spreadsheets fall short. Advanced insights capabilities help manufacturers uncover hidden opportunities, streamline operations, and connect meaningfully with customers by turning data into actionable strategies.

To achieve this, manufacturers should collect, analyze, and apply accurate data across their sales and marketing infrastructure. Clean data, the right tools, and a data-driven culture are essential for leveraging insights to drive growth and improve customer engagement.

Explains how mid-market companies can revolutionize their revenue strategies using advanced analytics, machine learning, and AI. It details how these technologies help identify inefficiencies, enabling companies to make informed, data-driven decisions. This strategic approach is essential for optimizing sales and marketing operations, ultimately leading to sustainable growth and a stronger competitive position.

Is the lack of robust clearance pricing strategy and manual pricing processes causing unnecessary and costly inventory buildup in your warehouses?

A leading $5B consumer durables wholesaler in North America wanted to unlock significant liquidity tied up in unproductive inventory by deploying in-house markdown optimization capabilities. Please read the below case study to understand how we helped them solve a $150MM unproductive inventory problem with dynamic clearance pricing.

This article is one in a series of five detailed case studies we will publish bi-weekly on key B2B Commercial Analytics topics. It gives insight into our outcome-based analytics process, including both technical and change management pieces.

In the complex world of marketing analytics, understanding the effectiveness of different marketing channels in driving customer conversions remains elusive for many.

Our latest article explores two powerful analytics techniques that can illuminate your marketing efforts: Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM). Even if you're not a data science expert, we break down these complex methodologies into easily digestible insights for any commercial professional.

Discover the pros, cons, and best-use cases for MTA and MMM and how advancements in marketing analytics are democratizing access to these potent tools. Join me and Gabriele Franco, co-founder of the breakthrough marketing analytics startup Cassandra, as we unlock the full potential of your marketing investments.