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™.
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
Revenue Growth Analytics (RGA) is a foundational enabler for organizations looking to transform their Revenue Growth Management strategies. RGA goes beyond traditional pricing techniques and provides insights into areas such as customer mix management, customer retention and cross-sell opportunities, and customer lifetime value. One of the key techniques used in RGA is RFM (Recency-Frequency-Monetary) Analysis.
RFM Analysis is a simple yet effective method of analyzing customer transactional data to drive better customer insights and improve customer retention, profits, and customer satisfaction.
The article discusses the common issue faced by Analytics/Data Science COEs where they invest heavily in new initiatives but struggle to see adoption and measurable outcomes. I advise new leaders in the field, data practitioners, and CXOs to focus on fewer initiatives that directly impact the revenue and gross profit drivers of the business, prioritize a subset with the right balance of impact, effort, and support, and involve an internal team of experts from relevant functions in the development process. Additionally, I advocate focusing on specific areas, such as price optimization, customer churn reduction, cross-sell optimization, promotion and discount optimization, and procurement optimization, to generate substantial value and internal adoption in the first couple of years before tackling larger-scale digital transformation type efforts.
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.
Analytical fire drills and knee-jerk pricing actions are becoming increasingly common in the consumer goods industry. With intense competition and ever-changing customer needs, companies must be agile enough to rapidly adjust their strategies to remain competitive and deliver relative value to their consumers.
By creating a dynamic integrated performance deep dive, CPGs can identify specific areas of improvement to maximize efficiency while delivering high-quality products at competitive prices — all of which will help them stay ahead of the competition in today’s market.
In the below quick guide, we’ll explore the steps needed to build a reproducible and highly actionable (and impactful) performance deep dive that can help CPGs address Revenue performance shortfalls.
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.
A brief guide for Manufacturers and Distributors to boost profits by 5-10% using simple, effective pricing and analytics techniques.
If you’re a manufacturer or distributor, you know that discounting is vital to the success of your sales force. But are you discounting enough? Are you discounting too much?
This article will discuss the importance of discounting in B2B settings and how to determine the right discounts for your customers and products. We’ll also discuss when to use each type of discount and offer tips for increasing Net Revenue and Gross Profit with analytics and surgical discounting.
Below are my top Revenue Growth Analytics quick wins that Distributors should implement (or right-size) to boost gross profits $ by 5-20% and increase liquidity.
Have a Revenue Growth Analytics pain point, a question, or a content suggestion?
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