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™.
A brief example of how visual analytics using Sales & Pricing metrics can be powerful in driving real, measurable change for your company.
Many middle-market companies are struggling to do action-oriented Commercial Analytics on a real-time basis. Understanding Sales, Pricing, and Margin performance vs. corporate objectives and strategies, along with proactively identifying and quantifying quick wins for improvement, is often a multi-day reactive, knee-jerk exercise. Pricing, Finance, and Commercial leaders are reticent to invest $MMs in turnkey price analytics solutions given high costs and long lead times – not to mention lack of flexibility and adoption issues that often yield a suboptimal return on investment.
Fortunately, you can do most of the above quickly, effectively (and cheaply!) using popular self-serve BI solutions like Tableau or Power BI.
Unproductive inventory often accounts for 20-30% of wholesale businesses’ merchandise. For many, it’s just the cost of doing business. But it doesn’t have to be that way. Unproductive inventory ties up your cash, erodes your profitability, and puts you at the risk of not meeting debt obligations for your asset-backed loans. Automated markdown pricing is one of the most effective ways to address this problem, and simple analytical solutions (no “ML and AI) can often yield significant benefits. Learn more below how.
I welcome your comments or similar experiences.
Fixing our CRM data hygiene should be a top leadership priority to drive sales productivity and revenue growth. However, for many B2B environments particularly in Manufacturing and Wholesale, there’s often a big disconnect between strategy and execution. Companies spend a disproportionate time and investment on market research studies to understand their buyer archetypes and personas, only to stop at great Power Points, executive updates and cross-functional pontifications.
Meanwhile, the CRM systems are plagued by outdated and missing data and no value- or needs-based segmentation information, which lays the foundation for automated lead scoring or prescriptive capabilities like upsell, cross-sell or churn mitigation.
Now is the time to act and start treating our holistic CRM data with the attention and priority it deserves!
The Apple Mobility index, published from January 13, 2020 to April 13, 2022, tracked the relative volume of map direction requests for various cities, regions and countries as people were driving, walking or taking public transportation to places.
As the US went into a lockdown in early 2020, key retail segments suffered tremendously, but with many recovering and accelerating their performance thanks to stimulus checks and the pent-up need for consumers to be out & about again.
Thanks to the demise of 3rd party digital IDs, our old friend Marketing Mix Modeling (MMM) is here to stay! Learn about MMM, how it’s done, and how it can be highly impactful to you and your company.
Companies are in the business of making money, and most often they care about maximizing their Revenues, Gross profit or Operating income. One of the biggest challenges companies face is the ability to correctly and systematically diagnose and isolate the individual drivers of key business performance changes and build fast, surgical actions to increase profitability. This week I talk about the benefits of doing a proper price-cost-volume-mix analysis for your business, and get you started on building a production level application with analysis examples and explanations in Excel and R.
Data science, AI and ML have been overhyped for at least the last decade, resulting in often unrealistic and misaligned expectations between data scientists and employers. Over the next couple of weeks, I shed light on the three major challenges data scientists typically encounter in their companies and provide concrete suggestions on how to tackle them for both personal and organizational success. Would love to hear from you about your experiences!
Most of us are familiar with the term customer price sensitivity as an important concept especially for sales, marketing and revenue management teams. It helps us understand how price changes affect demand, profitability or market share of our products or services. This week, I will describe the most popular analytical methods that help you measure your product or service price elasticities, including a few simple and proven machine learning based approaches that your analytics or data science teams can easily do.
Last week I wrote about the key tenets for building analytics teams for real, measurable impact in your organization. This week, I’ll focus on one of the four fundamental #datamonetization strategies that companies should employ: capitalizing on their data assets to deploy #operational improvement initiatives that drive cost savings, revenue increases or both. Operational #optimization initiatives are usually a good place for companies to start their #analytics journey, assuming some foundational data capabilities are already in place: reliable internal data, decent #datagovernance and tech stack, a good understanding of customer behavioral profiles and foundational #datascience capabilities.
Read about key analytics use cases across three industries that optimize operational processes to drive real performance. If you have your own analytics use case stories from the trenches (successes or lessons learned), or just want to chat analytics, machine learning or revenue management, drop me a note.
Most analytics transformation efforts do not deliver a positive ROI for the enterprise even after several years. CEOs and their boards know they need to execute an AI-led differentiation strategy to either future-proof themselves, address an existential risk in the marketplace, or simply to make some operational improvements to their business. Yet, according to most estimates, 75-90% of digital transformations fail and less than 1 in 5 companies have fully extracted value out of their analytics journey. Most organizations fail on the last-mile delivery – in other words, front-line employees and decision-makers are not using the analytics tools and processes as intended, or not using at all.
Over the last decade of leading analytics teams, I have succeeded and failed many times. Below are five lessons learned from these experiences. I hope it can serve as a helpful 10K foot roadmap for nascent or aspiring analytics leaders or seasoned business executives who want to build a sustainable practice that adds real, quantifiable value for their company and its customers.
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.
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