Understanding the business impact of price changes and promotional investments is crucial for effective revenue management. In this webinar, we'll guide you through building a B2B Price Elasticity Model in under 90 minutes, using both Linear Regression and Machine Learning methods. Learn how to increase price realization, optimize inventory, and drive net sales and gross profits. Attendees will receive a comprehensive blueprint and R code to implement in their organizations.

A 1% Net Price realization can drive, on average, an 11% improvement in Operating Profits, making Pricing the most critical business lever.

To achieve this, robust Margin Analytics & Optimization capabilities are essential.

These capabilities help control price discounts, reduce variability in margin profiles, and empower sales teams with rapid pricing insights. Using open-source tools like R and Python, along with self-serve BI tools like Tableau and Power BI, organizations can build a best-in-class Margin Analytics platform efficiently.

Discover how to build a B2B Margin Analytics & Optimization platform in Tableau, addressing key pricing and discounting challenges. Learn to identify Gross Profit drivers, coach your Sales team, and optimize discount strategies to boost Net Sales and profitability. Watch now for actionable insights and practical solutions.

In the Auto Service, Repair, & Tire retail industry, mastering pricing strategies is critical for maximizing profit margins and driving sustainable growth. This guide reveals powerful pricing tactics for automotive parts, tires, and services, enabling retailers to outpace competitors and boost profitability. Discover how to leverage advanced analytics and implement strategic discounting to enhance financial performance and secure long-term success in the automotive retail market.

A leading West Coast thrift retailer with $350M in revenue needed to optimize its promotional and marketing spending to support growth. Revology Analytics implemented comprehensive analytical models and a custom dashboard to guide strategic couponing and promotional bundling. This approach identified $80M in growth opportunities and reallocated marketing budgets for enhanced effectiveness, positioning the retailer for sustained growth.

A $150MM Public Interest enterprise struggled with inefficient marketing spending and an over-reliance on offline channels. Revology Analytics transformed their approach by merging marketing mix modeling with advanced multi-touch attribution. This shift revealed the effectiveness of digital channels, leading to a strategic reallocation of the marketing budget. A dynamic Power BI dashboard further empowered the organization to make data-driven decisions.

Leverage the power of revenue growth analytics and Price-Cost-Volume-Mix (PCVM) analysis to optimize your financial performance. Uncover key revenue drivers, assess pricing strategies, and identify growth opportunities with data-driven pricing insights.

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.

One of the critical mistakes earlier in my Revenue Growth Analytics career was relying on internal experts to inform the building of "Price-Value Maps" (aka. "PVM") for our Products and those of key Competitors. It proved to be a costly mistake, and we ended up eroding Gross Profits and EBITDA as all of our Price List increases were heavily offset by increased Rebates, Promotional and Shopper Marketing spend.

Modern companies collect substantial amounts of data. The data captured worldwide is expected to exceed 180 zettabytes by 2025, up from 64.2 zettabytes in 2020. This proliferation of data presents a massive opportunity for companies seeking to gain valuable insights into their customers and operations.

Yet, most businesses don't use data effectively, as up to 73% of all data goes unused. So, how can companies leverage the data they collect to boost profitability? In this article, we'll explore how businesses, particularly in the mid-market space, or those finding themselves "data rich, but insights poor," can gather and use data better and increase profit margins through advanced analytics.