Revology Analytics

The distribution industry is at a pivotal crossroads. Market saturation, fierce competition, and evolving customer expectations create unprecedented challenges for sustainable growth. Even with a wealth of data and technological advancements, many distributors find their growth rates stagnating, unable to meet internal goals, or outpace industry benchmarks. So, what's holding back the momentum? Traditional business models and outdated analytical tools are no longer sufficient. To break through these barriers, distributors need to leverage the power of Artificial Intelligence (AI) and Machine Learning (ML) to achieve tangible results in critical Revenue Growth Management (RGM) areas like Pricing, Customer Retention, and Personalized Marketing. Price Realization Gaps: Capturing revenue through optimized pricing is a significant hurdle. Sales teams often offer unplanned discounts to close deals, which erodes margins over time. AI/ML-enabled pricing models eliminate the guesswork by providing model-driven insights that help set prices, balancing competitiveness with profitability. This strategic approach ensures you're not leaving money on the table. Customer Churn: Customer churn silently undermines revenue growth. Traditional reporting methods flag churn too late. AI/ML changes the game by predicting churn early - often 90 days in advance, by analyzing patterns like reduced order frequency or increased complaints. With actionable insights for sales teams (including why the customer is predicted to churn), they can proactively engage at-risk customers, strengthening relationships and improving Customer Lifetime Values and long-term profitability. Missed Cross-Selling and Up-Selling Opportunities Your existing customers represent a large pool of untapped revenue potential. Without the right tools, identifying cross-sell and up-sell opportunities can be time-consuming. Algorithms can quickly analyze purchasing behavior to surface ideal product recommendations, helping you maximize each customer's value and boost sales without significant additional costs. Cut through the AI/ML hype: AI/ML capabilities can transform overwhelming data into actionable insights. By starting small—implementing dynamic pricing models or predictive analytics for churn—you can achieve quick wins that drive growth and profitability. It's not about overhauling your entire operation overnight or chasing some ambitious "North Star" initiative; it's about strategic steps that make a real, measurable difference. Make incremental improvements demonstrating tangible wins for business KPIs and working teams before investing in more aggressive and higher-risk AI/ML initiatives.

Discounts can be a double-edged sword in retail—are yours boosting growth or draining profits? Retailers face the critical challenge of balancing enticing discounts with sustaining profitable growth. While strategic discounting can drive sales and build customer loyalty, overusing promotions can erode profits and weaken a brand's value over time, especially in high-low retail settings. So, how can you refine your discount strategies to achieve growth while preserving profitability? Retailers typically operate under one of three pricing models, each requiring a tailored discount approach: 1. Premium Pricing: Discounts are rare (or non-existent) and strategic, used primarily to clear dusty inventory without impacting exclusivity or brand perception. High-end retailers like Louis Vuitton, Rolex, Hermès, and Chanel excel at this, as they rarely offer discounts to maintain their exclusivity and brand value. 2. Everyday Low Pricing (EDLP): Consistent low prices with minimal promotions help maintain customer loyalty without sacrificing margins. Mass Merchandise and Club chains like Walmart and Costco epitomize this model. 3. High-Low Pricing: Regular prices remain high, but frequent deep promotions attract bargain hunters without compromising long-term profitability. Department stores like Macy's and many grocery chains excel here. Understanding these pricing strategies helps avoid common pitfalls like over-discounting and brand devaluation. Mismanaged discounts can reset customer expectations (and reference prices), squeeze profits, and potentially reposition your brand as a discount retailer. Key Insights from Our Article: • The Role of Discounts in Retail Strategy: Learn how discounts function within various pricing models and their impact on purchasing habits. • Customer Psychology and Price Perception: Discover how psychological pricing techniques and concepts like scarcity and urgency influence buying decisions. • Avoiding Discounting Pitfalls: Recognize why excessive or frequent discounts can harm your brand and profitability (both in the short- and long-run). An effective discount strategy is essential for expanding your customer base without compromising profits or brand integrity. Understanding the interplay between pricing models and consumer psychology allows you to develop discount programs that stimulate growth while reinforcing customer loyalty and brand strength. The link to our full article is in the comments.

Is your distribution business plateauing despite your best efforts? Escalating costs, shifting market demands, and relentless competition mean traditional strategies are no longer enough to sustain growth. Distributors across industries—including industrial, consumer goods, and specialty sectors—face complex challenges like pricing inefficiencies, under-leveraged customer relationships, and retention hurdles that hinder profitability. Join Revology Analytics and our partner, Pricing Lever, for an exclusive, expert-level webinar designed for industry leaders and seasoned professionals eager to break through growth barriers. In this intensive session, we'll dive deep into how cutting-edge analytics and technology can empower you to: 1. Uncover and Seal Revenue Leaks Apply advanced diagnostic techniques to identify hidden profit drains such as price erosion, unnoticed customer churn trends, and untapped cross-selling or upselling opportunities. 2. Leverage AI & Machine Learning for Strategic Advantage Integrate sophisticated AI algorithms and machine learning models to gain predictive insights into customer behavior, optimize pricing structures, and elevate sales performance beyond conventional benchmarks. 3. Optimize Pricing & Discount Strategies with Data Precision Utilize granular data analytics to refine your pricing and discount frameworks, maximizing margins while maintaining a competitive edge in a dynamic market landscape. 4. Amplify Customer Lifetime Value (CLV) Implement advanced retention and engagement strategies focused on increasing CLV through personalized upselling and cross-selling initiatives, backed by robust data segmentation and customer profiling. Through in-depth case studies and real-world success stories, we'll demonstrate how leading distributors have harnessed advanced Revenue Growth Analytics to not just meet but surpass their ambitious growth objectives. Why Attend? •Gain Insider Knowledge: Access exclusive insights that aren't available in mainstream discussions. •Equip Yourself with Advanced Tools: Learn about the latest analytics tools that can be immediately applied to your business. •Network with Peers: Connect with other industry experts facing similar challenges and share strategies. Register Now to secure your place in this transformative session. All attendees will receive our comprehensive whitepaper on Revenue Growth Optimization and gain access to a suite of advanced analytics resources tailored for the distribution industry. Don't let growth headwinds hold your business back. Seize this opportunity to equip your team with the expertise and innovative strategies necessary to thrive and lead in today's complex distribution environment.

Are your retailer discount strategies boosting growth or undermining profits? Effective pricing and discount tactics influence customers' purchasing decisions and sustain same-store growth. While strategic discounts can enhance sales and build customer loyalty, overusing discounts and promotions can erode gross profits and weaken your brand's value over time. We've all seen this repeatedly - especially in high-low retail settings. So, how can you refine your discount strategies to achieve growth while maintaining profitability? Our latest article explores how different retailer pricing models—Premium (Prestige) Pricing, Everyday Low Pricing (EDLP), and High-Low Pricing—shape discounting approaches and affect consumer behavior. By understanding the nuances of these pricing strategies, you can avoid common pitfalls like over-discounting and brand devaluation. Key Insights from our article: + Understanding the Role of Discounts in Retail Strategy: Learn how discounts function within various pricing models and their impact on your customers' purchasing habits. + Customer Psychology and Price Perception: Discover how psychological pricing techniques and concepts like scarcity and urgency influence buying decisions. + Avoiding Discounting Pitfalls: Recognize why excessive or frequent discounts can be detrimental, potentially repositioning your brand as a discount retailer and affecting profitability. + Profit Margin Management Strategies: Explore methods to balance discount offerings while maintaining healthy profit margin thresholds across different pricing scenarios, with an overarching focus on driving profitable revenue growth. An effective discount strategy is essential for expanding your customer base without compromising profits or brand integrity. Understanding the interplay between pricing models and consumer psychology allows you to develop discount programs that stimulate growth and reinforce customer loyalty and brand strength. Read our brief article for mid-market retailers to gain actionable insights into optimizing your discount strategies to enable **profitable sales growth**.

What happens when you combine Revenue Growth Management with Advanced Analytics? Intended for industrial distributors, this webinar will be just as applicable for all B2B Pricing/RGM/Finance/Commercial Strategy professionals. Hope to see you on October 23!

Are you maximizing profits by aligning prices with the differential value you deliver to your customers? The most straightforward pricing strategy for companies is cost-plus or competition-based pricing models. When done right, a mix of automated, smart (i.e., based on segmentation) comp-index-based pricing coupled with minimum margin thresholds can be an excellent way for companies to drive substantial operating profit increases - if their current baseline is more gut-feel and cost-based. However, nirvana is value-based pricing (VBP). This strategic approach matches your product's price with its perceived value (or differential value relative to competition), allowing you to capture more of the value you create for customers. Unlike traditional pricing methods, which focus on costs or competitor benchmarks, VBP puts your customer at the center. It's about understanding what customers are willing to pay for the perceived benefits they receive. When done right (i.e., based on customer segmentation and research), VBP can boost revenues and profitability and strengthen customer relationships. Read more about value-based pricing, various industry applications, and how it can realize additional value over traditional pricing methods. (image courtesy of Robert Ribciuc)

Are you still using static pricing in a dynamic world? As markets continue to shift and customer behavior becomes more unpredictable, sticking with outdated static pricing models means leaving profit on the table. Mid-market companies that embrace dynamic, automated pricing strategies are positioning themselves to boost their profits, improve operational efficiency, and maintain a competitive edge. Dynamic pricing isn’t just about adjusting prices frequently. It’s about using advanced algorithms to adapt prices based on factors such as customer demand, competitor pricing, inventory levels, and even external influences like social media sentiment or weather conditions. The ability to adjust prices in real-time or near real-time—whether in daily or weekly batches—empowers companies to respond quickly to market fluctuations and customer preferences. By doing so, businesses can align their prices with changing market and internal conditions, optimizing their profitability while meeting customer expectations. Here’s how dynamic pricing can help your business: •Time-Based Pricing: Adjusts prices based on time of day, season, or special events to capitalize on fluctuating demand. •Segmented Pricing: Differentiates prices for specific customer groups, store/warehouse clusters or regions, recognizing that value is perceived differently (with different sales mix) across segments. •Peak Pricing: Increases prices during periods of high demand, maximizing revenue when customers are most willing to pay. •Market-Based Pricing: Responds to competitors in real-time, using smart indexing strategies to stay competitive while protecting margins. Even for companies just starting out, dynamic pricing can be relatively simple to implement. A basic setup might involve automated weekly price adjustments using a smart indexing approach against competitors and considering inventory turnover goals, combined with price elasticity models and expert-driven insights. This type of approach can often deliver 80-90% of the value achievable through dynamic pricing, even without the complexity of real-time machine learning. AI and machine learning are now essential to modern pricing strategies, and businesses that haven’t adopted automated, algorithmic pricing are missing out on both increased revenue and customer loyalty. Dynamic pricing is no longer optional—it's a critical tool for companies aiming to drive profitable growth. If your business model aligns with dynamic pricing but you haven’t implemented it yet, you’re already behind. It’s time to take the step toward smarter pricing strategies that will not only optimize your revenue streams but also improve your competitive position in the market.

Are you an industrial distributor struggling to meet growth targets despite winning new business and navigating price increases? You're not alone. Many distributors face hidden Operating Profit leaks in areas like net price realization, customer churn, and cross/up-selling opportunities. Traditional methods often fail to identify and address these challenges, leaving significant potential untapped. Join me and Enrico Sieni, founder of Pricing Lever and our Practice Lead for Industrial Manufacturing & Distribution, for this insightful webinar and learn how: 1. AI and Machine Learning can uncover hidden opportunities in your pricing, customer retention, and sales strategies. 2. Real-time insights can help you optimize pricing & discounting strategies and increase customer lifetime value. 3. Predictive models can empower you to anticipate customer behavior and take proactive actions to drive revenue growth. 4. Real-world examples and case studies demonstrate the power of advanced Pricing & Revenue Growth Management in transforming industrial distribution businesses. Don't let the status quo prevent you from maximizing your Operating Profits. Register today (link in comments) and discover how advanced Revenue Growth Analytics & Management can help unlock your full growth potential. All registrants and attendees will receive our corresponding whitepaper and access to our growing list of Revenue Growth Analytics resources.

Revology Analytics is a holistic Revenue Growth Analytics & Management advisory firm. While the majority of our engagements are Pricing Analytics & Strategy related, about 30-40% of our projects are all about advanced analytics (incl. AI/ML) in support of Sales & Marketing Enablement. Check out one of our smaller projects that otherwise had a substantial client impact at a leading agricultural manufacturer. While it's 2024, and we're sitting here debating when AGI will happen, a large % of mid-market firms (those typically under < $2B) are still operating on random Excel workbooks, taking several days and weeks of effort to produce key insights that should be at the fingertips of decision-makers. Standing up foundational capabilities, like in our video, is a straightforward (and very affordable) exercise, and it often frees up a ton of time for salespeople (who no longer have to spend hours doing VLOOKUPs each week). p.s.: This dynamic platform was developed by one of the best Power BI developers out there, Lukas Reese. We frequently partner with Lukas on client-specific Power BI projects, and I encourage everyone to check out his other work examples.

Are you still using static pricing in a dynamic world? As customer behavior becomes increasingly unpredictable and competitors move faster than ever, why stick to outdated, static pricing models? Mid-market companies that fail to evolve their pricing strategies leave money on the table. Dynamic, automated pricing helps address this and has been proven to be a powerful lever for maximizing profits while accelerating productivity on both the pricing intelligence and execution side. Dynamic pricing isn't just about frequent price adjustments. It's a model / algorithm-driven approach that enables companies to adapt prices based on predicted customer demand, competitor behavior, inventory levels, and external factors like weather or social media sentiment. When done right, dynamic pricing can also improve customer satisfaction and margins, operational efficiency, and competitive position. For most B2C and B2B companies who are not yet doing it (but it makes sense for their business operating rhythm), a beginner's dynamic pricing setup can be as simple as a weekly, automated pricing approach that employs some smart indexing approach vs. competition, and perhaps taking inventory DOH goals into account. This indexing approach could be based on a combination of price elasticity models, internal expert heuristics, or some refreshable profit optimization exercise. In fact, for many companies, this simplistic approach (no real-time ML) often drives 80-90% of the potential value realization from dynamic pricing. On the other hand, dynamic pricing could be as complex as real-time, personalized price adjustments based on various demand signals, such as cart abandonment rates, RFM scores, or predicted customer lifetime values. If your business model aligns with it, but you're not yet using some form of automated, algorithmic pricing, you are behind.