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.
We would love to hear from you.
Let’s chat!
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.
We would love to hear from you.
Let’s chat!
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™.
Overview: AI in Practice This article from Revology Analytics explains AI in the context of modern pricing analytics and revenue growth management. It draws on
It’s easy for us to get caught in the hype surrounding the latest and greatest tech advancements. Currently, AI is at the forefront of this phenomenon (what Gartner calls “peak of inflated expectations”). While AI certainly holds transformative potential, companies must approach its adoption with a measured perspective, especially in the mid-market sector (think $100MM-$1B in revenues).
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.
In our recent webinar titled “Supercharge Your Revenue Growth Strategy with Knowledge Graphs,” we discussed how this unique commercial analytics approach makes understanding multi-dimensional business data more accessible and substantially faster, helping you make smarter decisions and drive Profitable Growth quicker.
Revology Analytics had the opportunity to join 25 leading Revenue Growth Management executives in CPG and Manufacturing in St. Louis earlier this week. We discussed the state of Revenue Growth Analytics in the CPG industry and the significant opportunity to in-source and own many of the advanced analytics capabilities foundational to a successful RGM and Pricing strategy.
In many ways, the state of Revenue Growth Management and its associated analytics capabilities have not changed meaningfully in the last ten years for Consumer Goods companies. There’s still a heavy reliance on data and information providers like Nielsen and IRI to carry out foundational Pricing & Promotional Analytics efforts, including Price Elasticity and Marketing Mix Modeling, or a heavy reliance on 3rd party software for price analytics, scenario analyses, and optimization efforts.
However, the world is changing….fast.
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?”.
GPT-4 is already starting to reshape the field of commercial analytics, and we at Revology Analytics are huge proponents of it.
In our recent webinar titled “GPT-Powered Speed: Supercharging your Revenue Analytics,” we delved deep into how GPT-4 is a game changer for analytics teams. More specifically, we explored GPT-4’s ability to accelerate productivity around diagnostic and predictive analytics for Revenue growth problems.
In addition to exploring how to create the perfect prompts for analytical workstreams, we provided hands-on examples in Python using simulated data sets for things like Price Elasticity modeling, Cohort Analyses, and Churn Modeling.
We have the full recording available here for those who missed the live session or wished to revisit the insights.
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.
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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