Pricing Strategy Insights

Some of you have heard me say that there are only two types of pricing discounts: smart and stupid. And you want to get rid of the stupid ones. Stupid discounts are bad for five reasons: 1. They eat directly into your margin. 2. They lower the value perception of your product and service. 3. They create pricing inconsistencies. 4 They encourage customers to haggle and reward the wrong type of customers with lower prices. 5.Because of (3) and (4), sales cycles in B2B markets tend to be longer and focused on price, not on value. Today, I want to emphasize the second point- discounts lower the value perception of your products and services. There is sufficient empirical evidence that this is true across product categories, customer segments, and cultures. One remarkable study did not only measure the perception of discounted products but also actual performance. The study by Shiv, Carmon, and Ariely explored how discounts influence consumers' perceptions and actual experiences with a product. The researchers demonstrated that when participants purchased an energy drink at a discounted price, they performed worse on cognitive tasks compared to those who paid full price for the same drink. This phenomenon was attributed to participants' expectations about the efficacy of the product, which were influenced by its price. Study Design The research consisted of three experiments designed to test the hypothesis that lower prices negatively impact perceived and actual efficacy due to placebo effects: - Participants: Individuals were recruited and randomly assigned to different pricing conditions. - Product: The energy drink used in the study was marketed to enhance mental acuity and cognitive performance. - Procedure: Participants were told they would consume an energy drink before completing a series of word-jumble puzzles (e.g., solving anagrams). The drink was offered at either its regular price or a discounted price. Participants then consumed the drink and completed the puzzles within a set time limit. - Outcome Measures: Cognitive performance was measured by the number of puzzles solved correctly. Participants also rated the perceived effectiveness of the drink on a scale. Key Findings Participants who paid full price for the energy drink solved more puzzles on average than those who purchased it at a discounted price. The results indicated that the lower price activated weaker expectations about the product's efficacy, which in turn led to poorer performance. This effect was consistent across all experiments, supporting the role of expectancy in mediating placebo effects. The key takeaway from this and other studies is obvious: your price serves as an indicator of quality, whether it makes sense or not. Price discounts cost you five times. Shiv, B., Carmon, Z., & Ariely, D. (2005). Placebo effects of marketing actions: Consumers may get what they pay for. Journal of Marketing Research, 42(4), 383-393. DOI:10.1509/jmkr.2005.42.4.383. #pricing

Replit's gross margins went from 36% to negative 14% in two months. Same product. Same pricing. Same team. The only thing that changed: they launched a more autonomous AI agent that consumed more LLM resources than their pricing covered. Traditional SaaS has 70-80% gross margins because one more subscriber costs almost nothing. AI products pay for compute on every prompt. Your best users are your most expensive users. That single fact breaks every pricing model designed for the SaaS era. I mapped pricing across the top 50 AI startups by valuation with Moe Ali. Six patterns emerged. The scariest finding: in most AI products, the P90 user costs 10-40x more than the P50 user. Both pay the same subscription. You're subsidizing your heaviest users with revenue from your lightest ones. And that subsidy grows as power users discover more ways to use the product. Cursor learned this the hard way. They switched from flat 500 requests/month to a credit pool system. A developer burned the entire monthly allocation in a single day. $7,225 invoice. The CEO published a public apology on July 4th. The plan description quietly changed from "Unlimited" to "Extended" twelve days after launch. Anthropic took a different approach. Their $17/$100/$200 tiers map to genuinely different user personas. A casual user, a power user, and a developer replacing an IDE. Those are different products with different willingness to pay. Then weekly rate limits targeting less than 5% of subscribers to push the heaviest users toward the API, where per-token pricing covers actual compute. The pattern across all 50 companies: pure flat pricing is dying. Nearly half use two or three models simultaneously. Here's the full breakdown: 1. Complete AI pricing guide: https://lnkd.in/gdKaQSMk 2. Replit guide: https://lnkd.in/gmA_c_AG 3. AI product strategy: https://lnkd.in/egemMhMF 4. AI agents guide for PMs: https://lnkd.in/eeey5Cxr If you can't estimate your cost distribution across P10 to P90, you're not ready to set a price.

Two similar and simultaneous promotions, but one attracts four times as many new buyers for the brand as the other! One thing I have learnt over the last few years is that new buyers of a brand usually purchase a smaller pack size with a corresponding lower price point. It’s an intuitive finding – there is no great surprise that first time buyers of a brand tend to dip a toe in the water with a small pack thereby minimising the risk associated with their purchase. Hence a price promotion on a smaller pack size can be a very good way to attract those non and occasional buyers who Byron Sharp has shown us are essential for growth. So what about these two promotions? Our research using NIQ data shows that whilst the single bottle at £1.25 attracts a significant number of new to brand buyers, the multibuy offer is bought almost exclusively by existing buyers! Brands need to understand how each pack, price and promotion contributes to new buyer growth in order to optimise the returns from their promotions and shopper activities. I’m sharing insights on how brands gain new buyers derived from the First Purchase approach. Please follow or connect if you want to see some more ¨

This week, Cursor, the beloved AI coding assistant, nuked its "Unlimited" plan. • $20/𝐦𝐨𝐧𝐭𝐡? Suddenly became ~225 requests. • 𝐏𝐨𝐰𝐞𝐫 𝐮𝐬𝐞𝐫𝐬? Burned through it in hours. • 𝐃𝐞𝐯 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲? Absolutely furious. 𝐁𝐮𝐭 𝐥𝐞𝐭’𝐬 𝐛𝐞 𝐫𝐞𝐚𝐥: The cursor’s mistake wasn’t pricing too high… It was priced like a traditional SaaS product in an AI-native world. Let me show you why that's a disaster waiting to happen. 1. 𝐀𝐈 ≠ 𝐒𝐚𝐚𝐒 Traditional SaaS has near-zero marginal cost. AI-native apps? Every user interaction costs real money. 2. 𝐓𝐡𝐞 𝐅𝐨𝐮𝐧𝐝𝐞𝐫 𝐃𝐢𝐥𝐞𝐦𝐦𝐚 You want usage to grow… But every success drains your wallet faster. I learned this the hard way. Launched our beta with 15 users. Burned $500 in 72 hours. Why? Each interaction triggered 5+ API calls. Multiply that at scale… you’re toast. 3. 𝐔𝐧𝐥𝐢𝐦𝐢𝐭𝐞𝐝 𝐢𝐬 𝐚 𝐋𝐢𝐞 Founders pricing AI tools with "Unlimited" plans are either: • Hiding limits (destroying trust) • Losing money (slow death) • Overpricing to subsidize whales (alienating core users) None of these are sustainable. 4. 𝐌𝐲 𝐍𝐞𝐰 𝐑𝐮𝐥𝐞𝐛𝐨𝐨𝐤 After my $500 wake-up call, I rebuilt our pricing from scratch: ✅ Usage-based ✅ Transparent ✅ Margins that make sense ✅ Value at every step And most importantly no surprises. #Cursor's fall is a warning. Not just about trust. But about the illusion that AI tools can run on SaaS economics. The next wave of AI-native startups will win not by hiding cost… …but by designing models that make success profitable, not punishing. Founders, how are you tackling AI pricing? Let’s compare notes. This entire ecosystem is still figuring it out together. Read full here: https://lnkd.in/diQB4VMp 

This peak season, protect your margins by controlling discount stacking. As we approach peak trade and the peak discounting period, brands often default to the bluntest tool in the box: heavy sitewide sales. The logic is simple “drop the price, drive volume, clear stock.” But too many brands forget one crucial detail: stacking discounts can quickly turn profitable orders into loss-making ones. The Overlooked Discounts: Sitewide promotions don’t operate in isolation. Sitting in the background are your: High-intent pop-ups Welcome series discounts Cart abandonment flow incentives These are designed to capture incremental conversions in normal trading periods. But when layered on top of aggressive sitewide offers, they often wipe out already-thin margins. A Quick Example: RRP: $100 Sitewide discount: 30% → Sale price = $70 Product cost (COGS): $20 Customer acquisition cost (CAC): $30 Shipping / merchant / pick & pack costs: $15 At this stage: Revenue: $70 Costs: $20 + $30 + $15 = $65 Profit: $5 per order (5% margin) Not great, but still positive. Now add in an additional 20% discount from a pop-up or triggered flow: Extra discount: 20% off $70 = -$14 Adjusted sale price = $56 Recalculate: Revenue: $56 Costs: $65 🛑 Net loss: -$9 per order Why It Matters At scale, these “hidden discounts” mean businesses spend thousands acquiring customers and fulfilling orders at a negative contribution margin. Instead of driving growth, they quietly erode cashflow and profitability during the most critical sales period of the year. How to Avoid This Trap: Audit your flows before peak trade. Adjust high-intent pop-ups, welcome offers, and cart abandonment discounts during sitewide promotions. Set a CAC ceiling. Ensure that even with discounts applied, your contribution margin remains positive. Model scenarios. Calculate “worst case” blended discounts and costs before launching campaigns. Use AI or rules-based systems. Automate safeguards so discounts can’t stack beyond a certain threshold. Discounting can be a powerful lever, but unmanaged, it becomes a profit killer. You may risk turning your busiest period into your least profitable one.

📘 Apparel Knowledge Series | Episode 11 Achieving the Buyer's Target FOB A Business Case Study on Cost Structure Optimization A factory received an inquiry for 250,000 garments. The costing/merchant team worked for two days. Fabric price was negotiated. Trim prices were finalized. CM was calculated. Commercial and finance costs were included. Profit margin was added. Finally............ The quotation was sent to the buyer. Two days later, the buyer replied: "Your FOB is higher than other suppliers." The buyer didn't reject the factory. The buyer didn't reject the quality. The buyer didn't reject the delivery. They rejected the costing. The management team immediately called a meeting. The first reaction was predictable: "Reduce the profit." But the Costing Manager asked a different question: "Before reducing profit, do we know why our cost is higher?" Instead of reducing the selling price........ The team started reviewing every cost element. What They Found ✔ Fabric utilization was only 82%. ✔ Marker efficiency could be improved. ✔ Line efficiency was below target. ✔ Commercial Cost was slightly higher than the industry benchmark. ✔ Packaging specification was overdesigned. ✔ Freight assumptions were outdated. None of these looked significant individually. But together... They increased the FOB by $0.28 per garment. For a 250,000 pcs order, that meant: 250,000 × $0.28 = $70,000 The problem wasn't the buyer. The problem wasn't the market. The problem was the cost structure. The Business Decision Instead of cutting profit, the team optimized the cost structure: Improved marker efficiency Increased line efficiency Optimized packaging Updated freight assumptions Reviewed commercial costs The revised FOB became competitive. The buyer confirmed the order. And the factory protected its profit. 📌 Business Lesson Experienced costing professionals don't negotiate the selling price first. They improve the cost structure first. Because... A lower FOB doesn't always come from accepting less profit. Sometimes it comes from making smarter business decisions. 📌 Key Takeaway Winning a buyer's order isn't about offering the lowest price. It's about offering the most competitive FOB while protecting profitability. 📖 Episode 11 of the Apparel Knowledge Series demonstrates how small improvements across multiple cost elements can collectively reduce FOB significantly—without sacrificing profit. 💬 Discussion Question When a buyer asks for a lower FOB, which area do you review first? Fabric CM Commercial Cost Packaging Profit Margin #ApparelManufacturing #GarmentIndustry #Costing #FOB #Merchandising #IndustrialEngineering #LeanManufacturing #SupplyChain #Commercial #ApparelKnowledgeSeries #TextileIndustry #BusinessCaseStudy #ManufacturingExcellence

Price adjustments are one of the most important marketing levers for boosting sales. The key challenge lies in measuring consumers' price sensitivity accurately. How different are the results when using experiments versus MMM-style analyses? A new study sheds light on this critical question, comparing price elasticities for a US grocery retailer using these different methods: 📉 Non-experimental scanner price data (which we also call observational data), analyzed using OLS regressions. This approach is common in Marketing Mix Models (MMM) and is the most widely used method for obtaining pricing insights. 🔬 Experimental random price manipulations. The findings reveal significant differences in price elasticities (accounting for temporary price promotions) across nine product categories: 📉Standard OLS: -1.08 📊 OLS with control functions (inverse instrument): -0.92 * 🔬Experiment-based (2SLS): -0.32 Summary: While OLS-based analyses suggest values close to unit elasticity (around -1), the experimental findings imply that many products likely exhibit inelastic demand. In other words, demand does not change significantly when prices rise. Key takeaways: 🔍 These results highlight how potentially misleading non-experimental analyses, including traditional MMM, can be. Even typical econometric adjustment tricks (e.g., instruments/control functions) may not sufficiently adjust price elasticity estimates. 🛡️Having said this, given the bias found in the study, one could also argue that MMM-based analyses are rather conservative in many cases (at least when it comes to suggesting price hikes). But we should be careful when considering price reductions based on MMM results. 💰 The good news for marketers is that the study findings suggest many brands may have stronger pricing power than previously thought. Reminder: Products with a price elasticity smaller than 1 (in absolute value) may have room to raise prices and boost revenues. Caveats: ⚠️ The study focused on nine product categories (409 products), 35 weeks, and 82 stores before COVID. Prices have shifted significantly since then. Price elasticities vary by brand, product, time period, and region. Thus, we need more replication and tests to understand when and why consumer price sensitivities differ. Put simply, we need more brave brands willing to experiment—even with prices 💪. The original study, which includes many different analyses and robustness checks, is a masterclass in price elasticity analysis (warning: it's a highly technical read) and can be found here: https://lnkd.in/gE5Y3yxZ Technical notes: * I could not find the exact number in the text, so this is an approximate average derived from Figure 12 of Bray, Sanders, and Stamatopoulos 2024.

Procurement teams are no strangers to supplier price hikes. But the truth is: Not every price increase is justified. Inflation, tariffs, and labor costs are real, but so is cost softening. And if you're not tracking those shifts down to the commodity and component level, you’re likely leaving savings on the table. This type of insight should be done for every product, component, and direct material. Here’s a simple, repeatable method to push back with facts, not assumptions: Step 1: Identify Commodity Trends ➡️ Track input commodities. The commodities that are part of the products you buy. If commodity/component prices have decreased, that’s your opportunity window. Step 2: Map Commodities to Products ➡️ Connect those commodities to the SKUs and products in your portfolio. How much does the commodity get used in your buy-space? Which goods are exposed? What suppliers are being affected? What products have that commodity? Step 3: Analyze Cost Structures ➡️ Drill into the cost breakdown of every product that uses that commodity. What % of the total cost does that commodity represent? Repeat the analysis for every product that uses that commodity. Step 4: Supplier Attribution ➡️ Now link those products to the suppliers you buy them from. You should know exactly which suppliers are affected. Step 5: Quantify the Opportunity ➡️ Use real market data to calculate what the savings should be based on recent cost declines. For example, if aluminum dropped 15% in the last three quarters and makes up 30% of a product’s cost, that’s meaningful leverage. Step 6: Negotiate with Confidence ➡️ Approach your supplier with the data. Be precise. Be proactive. “We’ve seen a 15% decrease in aluminum prices, which represents X% of your product cost. We’d like to see that reflected in pricing.” This is how you fight inflation without guesswork. 📌 Bonus: Platforms like Kloopify make this process faster, scalable, easier, and defensible. We embed real-time commodity, tariff, and cost intelligence at the SKU level, location, and supplier level, so you’re never negotiating blind. Procurement isn’t just reacting anymore. We’re leading with data. Let’s make sure our suppliers know it. What did I miss? Or what would you add? Let me know!

I REFUSE to put pricing on my website. Why? Because I LOVE wasting my time with people who can't afford me. Every morning, I wake up excited to spend 4 hours going through emails and calls with completely unqualified leads who gasp when they hear my rates. "THAT MUCH? For THAT?" they say. This is my favorite part of the job. When my competitors started putting pricing on their websites, their sales skyrocketed and their teams stopped having mental breakdowns. Pathetic. Real entrepreneurs THRIVE with mental breakdowns and inefficiency. Sure, we could put pricing on the website and have qualified leads calling us directly about implementation, demos, etc... But where's the HUSTLE in that? Where's the GRIND? Last year we spent 5,428 hours explaining our pricing and closed 3 deals. That's what I call EFFICIENCY. You can't put a price on that. That's why I don't. 👇👇👇👇👇👇 Yesssss, I am being sarcastic. The truth is, transparency isn't just good for customers, it's good for your business. When you hide your pricing, you're not protecting value, you're creating friction that costs you money, time, and customer trust. Remember, we live in a world where people are used to instant information, making them jump through hoops just shows you don't value their time. Be transparent about pricing. It saves everyone time.

𝐑𝐄𝐕𝐄𝐍𝐔𝐄 𝐈𝐒 𝐃𝐄𝐂𝐋𝐈𝐍𝐈𝐍𝐆 — 𝐖𝐇𝐀𝐓 𝐖𝐎𝐔𝐋𝐃 𝐘𝐎𝐔 𝐃𝐎? 𝐌𝐨𝐧𝐭𝐡 𝐛𝐲 𝐦𝐨𝐧𝐭𝐡, 𝐭𝐡𝐞 𝐧𝐮𝐦𝐛𝐞𝐫𝐬 𝐚𝐫𝐞 𝐠𝐨𝐢𝐧𝐠 𝐝𝐨𝐰𝐧. It’s easy to get anxious when revenue starts shrinking. But as finance professionals, our job isn't just to report the trend, it's to understand it and help change it. 𝐒𝐨 𝐰𝐡𝐚𝐭’𝐬 𝐦𝐲 𝐟𝐢𝐫𝐬𝐭 𝐦𝐨𝐯𝐞 𝐰𝐡𝐞𝐧 𝐈 𝐧𝐨𝐭𝐢𝐜𝐞 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐝𝐞𝐜𝐥𝐢𝐧𝐢𝐧𝐠? • I break it down to the fundamentals: • Revenue = Price × Quantity 𝐒𝐞𝐞𝐦𝐬 𝐬𝐢𝐦𝐩𝐥𝐞 𝐛𝐮𝐭 𝐛𝐞𝐡𝐢𝐧𝐝 𝐞𝐚𝐜𝐡 𝐨𝐟 𝐭𝐡𝐞𝐬𝐞 𝐜𝐨𝐦𝐩𝐨𝐧𝐞𝐧𝐭𝐬 𝐢𝐬 𝐚 𝐰𝐞𝐛 𝐨𝐟 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐢𝐧𝐬𝐢𝐠𝐡𝐭𝐬. 📌 𝐒𝐭𝐞𝐩 1: 𝐃𝐞𝐜𝐨𝐦𝐩𝐨𝐬𝐞 𝐑𝐞𝐯𝐞𝐧𝐮𝐞 • Is the drop due to lower sales volume? Or are we cutting prices? • Maybe both? • Are certain products or regions dragging overall performance down? • I always start with a Price-Volume-Mix (PVM) analysis to isolate the root cause. 📌 𝐒𝐭𝐞𝐩 2: 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝐏𝐫𝐢𝐜𝐞 • Has there been a discount strategy in play recently? • Are we losing pricing power due to competition or market saturation? • Is our pricing aligned with value delivered? • Are unit costs rising, forcing margins to shrink even at stable prices? • Here, I connect pricing with cost structures if our unit costs are growing and we can’t raise prices, we’re in trouble. 📌𝐒𝐭𝐞𝐩 3: 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝐐𝐮𝐚𝐧𝐭𝐢𝐭𝐲 • Are customers buying less, or have we lost key accounts? • Is it a seasonal trend or a sign of a market shift? • What’s the performance by channel, sales team, or region? • Understanding quantity is understanding demand, and whether it's external (market-driven) or internal (sales execution, supply issues). 📌𝐒𝐭𝐞𝐩 4: 𝐃𝐢𝐯𝐞 𝐈𝐧𝐭𝐨 𝐂𝐨𝐬𝐭 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐬 • A lot of companies forget this step. • If we’re pricing based on cost-plus logic, then rising costs might be making us uncompetitive. 𝐒𝐨 𝐈 𝐥𝐨𝐨𝐤 𝐚𝐭: • Variable vs. fixed cost trends • Margin compression across products • Opportunities to optimize procurement, logistics, and process costs 📌 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐈𝐬 𝐭𝐡𝐞 𝐊𝐞𝐲 • Revenue decline is a signal, not just a problem. • It’s telling us something about: • Our competitive position • Our customer behavior • Our internal efficiency 𝐅𝐢𝐧𝐚𝐧𝐜𝐞 𝐥𝐞𝐚𝐝𝐞𝐫𝐬 𝐦𝐮𝐬𝐭 𝐠𝐨 𝐛𝐞𝐲𝐨𝐧𝐝 𝐭𝐡𝐞 𝐬𝐩𝐫𝐞𝐚𝐝𝐬𝐡𝐞𝐞𝐭 𝐚𝐧𝐝 𝐚𝐬𝐤 𝐭𝐡𝐞 𝐡𝐚𝐫𝐝 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬. 𝐓𝐡𝐚𝐭’𝐬 𝐡𝐨𝐰 𝐰𝐞 𝐭𝐮𝐫𝐧 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐢𝐧𝐭𝐨 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬. #FPandA #FinanceStrategy #CFOThinking #RevenueDecline #BusinessAnalysis #PricingStrategy #FinancialLeadership #StrategicFinance #CostOptimization #RevenueGrowth