Discover how Revology Analytics propels mid-market businesses to sustainable, profitable growth by building advanced, in-house Revenue Growth Analytics & Management (RGM) capabilities—fast.
Our senior expert-led, hands-on approach ensures you own the tools, insights, strategy and processes needed to thrive long-term.
Gain exclusive access to the latest insights from over 150 commercial leaders on the state of Revenue Growth Analytics in 2025, based on our expanded Revenue Growth Analytics Maturity Scorecard™.
Discover how Revology Analytics propels mid-market businesses to sustainable, profitable growth by building advanced, in-house Revenue Growth Analytics & Management (RGM) capabilities—fast.
Our senior expert-led, hands-on approach ensures you own the tools, insights, strategy and processes needed to thrive long-term.
Gain exclusive access to the latest insights from over 150 commercial leaders on the state of Revenue Growth Analytics in 2025, based on our expanded Revenue Growth Analytics Maturity Scorecard™.
Discover how strategic discounting transforms customer engagement and drives profitability in this week’s Revology Analytics Insights video. Learn to tailor discounts effectively, ensuring sales growth and customer loyalty without compromising your bottom line.
Discover the latest insights in our newest video: The State of Promotion Analytics & Optimization. A must-watch for this week!
AI and ML have been reshaping industries, and Sales and Marketing Executives stand at a pivotal crossroads as capabilities from leading tech platforms accelerate.
The key to a competitive edge and increased profitability is leveraging popular tech stacks like Microsoft and Google. However, navigating through an oversaturated market of ~ 10,000 “turnkey” software products for Sales & Marketing Enablement is daunting.
Enter In-Sourcing, the strategic approach that elevates your company’s analytics maturity, using popular tools like Microsoft’s Power Platform and Azure or Google Cloud AI. In-sourcing your Revenue Growth Analytics capabilities highlights the transformation from vendor-reliance to an empowered, insights-driven organization, offering a path for executives to transform their companies to truly data and insights-driven.
Two decades later, Promotion Effectiveness & Optimization is still a substantial business problem for companies; at least 50% struggle in this arena.
When we asked ~ 150 commercial leaders about their organization’s Promotion Effectiveness & Optimization capabilities, the Consumer Goods industry emerged with a high score of 3.3 (a little better than Average). This is unsurprising since this is one industry where Promotional spending is routinely 15-30% of Gross Revenues and where the Trade Promotion Management, Effectiveness & Optimization (TPX) software industry grew the fastest.
Why Price Realization Matters: Key Findings from our Inaugural Revenue Growth Analytics Survey.
A company’s ability to consistently measure and manage its Net Price Realization is a crucial, yet often overlooked, element of a robust Profit Growth Strategy.
Price Realization – the difference between your List Price and Actual Price (after discounts, rebates, and other incentives/concessions) impacts your bottom line in a significant way.
Over 125 commercial leaders have taken our Revenue Growth Analytics Maturity Quiz, which measured maturity/competency scores across three major areas:
1) Margin Analytics & Optimization
2) Promotion Effectiveness & Optimization
3) Sales & Customer Growth Analytics
The first question in the “Margin Analytics & Optimization” section asked respondents, “How frequently is pricing performance (net price realization) measured and reported to company leaders?”.
It’s time to rethink traditional sales and price elasticity modeling methods.
Aggregated data at the retail chain level and modern machine learning models are vital in shaping an efficient, practical, and robust approach for predicting and explaining retail sales.
Why this shift? The traditional reliance on granular, disaggregated (i.e., store-product-day level) data and old-school models are costly, complex, and often misaligned with practical management strategies.
Turning to aggregated data and modern ML approaches reduces costs, enhances model accuracy and efficiency, and makes these valuable insights more accessible to smaller firms and faster for larger ones.
Moreover, in-sourcing these capabilities builds critical, sustainable expertise for Revenue Growth Management, freeing companies from reliance on 3rd parties. This shift signifies an effective and sustainable future for Revenue Analytics and redefines competitive positioning, enabling superior service and product offerings.
Understanding the impact of price changes and promotional investments on business outcomes is crucial for all commercial teams (revenue management, finance, analytics, sales, and marketing). In today’s data-driven world, it is essential to have a deep understanding of price and promotional elasticities at the customer-product level to optimize sales, profitability, and market share.
The below guide gives an overview of the typical modeling approaches for price elasticities and contrasts regression vs. machine learning methods for industry best practices.
Companies are in the business of making money, and most often, they care about maximizing their Revenues, Gross Profit, and Operating Income. One of the biggest challenges Finance and Revenue Management teams face is the ability to systematically diagnose the drivers of fundamental business performance changes near real-time.
The price-cost-volume-mix analysis, sometimes known as Revenue or Gross Profit Growth Deep Dive, helps you understand the relevant components that drove your revenue, gross Profit, or other critical financial changes from one period to the next (or for actuals vs. budget).
This short video will show you a simple Gross Profit Growth Deep Dive built on customer transactional data.
This week, I wanted to show you another simple yet effective revenue analytics technique to steer sales behavior in the right direction and drive Gross Profits. Part 2: Discount Curve Analysis
It often amuses me that in the era of ChatGPT (and despite the countless books I have in my library on AI/ML), I’ve never used any Deep Learning model for any of my client engagements or prior advanced analytics leadership roles.
For 99.95% of data problems in traditional (non-tech) companies, Deep Learning (and any of its derivations like LSTMs, GANs, CNNs, etc.) are overkill at best and a complete waste of time (or not applicable) at worst.
Data science is an ever-evolving field, and its roles are also changing. As businesses increasingly rely on data to inform their decisions, there is a growing need for people with both the technical skills and domain/industry expertise to drive measurable value.
It’s no secret that many retailers and distributors are struggling with suboptimal prices, leading to substantial profit losses or missed revenues.
But by developing a solid price-testing playbook, retailers and distributors can maximize profits without sacrificing sales.
You don’t need to spend 12-18 months deploying an enterprise price optimization solution or waste a ton of CAPEX. You can start building your own semi-automated price-testing solution today at a fraction of the development times and costs.
If you’re a Pricing or Finance executive looking for a way to improve your company’s bottom line, read this 5-minute guide on how to build a sustainable Price Testing playbook.
Have a Revenue Growth Analytics pain point, a question, or a content suggestion?
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Centered on proven best practices, Revology Analytics® provides Revenue Growth Analytics advisory services and thought leadership, driving profitable revenue growth for middle-market companies.
Over 225 companies took our scorecard to improve their Revenue Growth Analytics & Management capabilities.
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