Building a Dynamic Pricing Capability (In Under 90 Days)

July 21, 2024

Many mid-market retailers and wholesalers’ pricing, finance, and merchandising executives have inherited outdated pricing solutions.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.

RFM Analysis as an Important Revenue Growth Analytics Capability – Part 2

February 22, 2023

RFM Analysis is a powerful tool for businesses seeking insights into customer behavior and segmenting them based on purchasing habits. By calculating RFM scores and creating segments, companies can identify valuable customer groups and target them with personalized sales and marketing campaigns. RFM Analysis is not limited to the retail industry or the marketing domain. It can be applied to most industries and functional domains that touch the customer, including pricing, supply chain, A/R, product management, and customer service. Additionally, RFM Analysis can benefit nonprofit organizations by understanding donor behavior to optimize fundraising initiatives.

In part 2 of our RFM Analysis article, we’ll dive deeper into how we can calculate RFM scores, visualize customer performance by RFM segment and discuss sales and marketing implications.

Beyond the Hype: Practical Revenue Growth Analytics Use Cases that Drive Impact

February 18, 2023

AI/ML is not the ultimate solution for every data-related problem. We must first set up foundational descriptive and diagnostic analytics capabilities and more straightforward ML approaches before applying more advanced techniques. It’s essential to understand the business problems and work closely with functional partners to solve them in a way that aligns well with the company’s analytical readiness and operating rhythm.

The examples of Revenue Growth Analytics use cases mentioned, such as Promotional Analytics, Everyday Price Optimization, Dynamic, Automated Clearance Pricing, Bulk Purchase Optimization, Customer Segmentation & Predictive Insights, and Customer Churn & Cross-Sell Modeling, are practical and impactful capabilities that can drive measurable sales and gross profit improvements. They can be implemented using simple math and essential ML and with popular tech stacks with which pricing, supply chain, and sales partners are familiar.

Overall, the focus should be on pragmatic and co-created approaches with business stakeholders that are most likely to get adoption and impact rather than on celebrating complexity for its own sake.

RFM Analysis as an Important Revenue Growth Analytics Capability – Part 1

February 7, 2023

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.

Unlocking the Power of Revenue Growth Analytics for Sustainable Growth

January 29, 2023

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.

If you need to use Machine Learning, keep it simple!

January 27, 2023

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.

RA Quick Insights: Top Pricing Quick Wins for Distributors

December 19, 2022

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.

RA Quick Insights Video Series: Driving rapid margin actions with transactional data analysis (Part 1 – Margin vs. Sales Matrix)

October 26, 2022

Part 1: Using Gross Margin % vs. Net Sales Customer Matrix to segment customers into actionable Sales & Pricing performance clusters.

RA Quick Insights: Break-Even Price Elasticities – a Simple, but Powerful Sanity Check

October 24, 2022

Have you ever offered a deep Price Discount in December in hopes of accelerating 4Q and YE target achievement, only to drive Unit Sales but suffer huge Gross Profit losses?

RA Quick Insights: Using Sales Stack Ranking to Grow Net Sales & Profits

September 29, 2022

Commercial Analytics, aimed at improving Gross Profits and Sales Productivity, doesn’t have to be complex to drive the proper outcomes with Pricing and Sales teams.

𝐒𝐚𝐥𝐞𝐬 & 𝐃𝐢𝐬𝐜𝐨𝐮𝐧𝐭𝐢𝐧𝐠 𝐒𝐭𝐚𝐜𝐤 𝐑𝐚𝐧𝐤𝐢𝐧𝐠 is another simple yet effective Revenue Analytics technique to steer Sales behavior in the right direction and drive incremental Net Sales (and Gross Profits).

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