Online Pricing Strategy Adjustment

𝐈𝐟 𝐲𝐨𝐮 𝐜𝐡𝐚𝐫𝐠𝐞 $99 𝐢𝐧 𝐍𝐞𝐰 𝐘𝐨𝐫𝐤 𝐚𝐧𝐝 $99 𝐢𝐧 𝐌𝐮𝐦𝐛𝐚𝐢, 𝐲𝐨𝐮 𝐝𝐨𝐧’𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐦𝐚𝐫𝐤𝐞𝐭𝐬. Flat global pricing feels “fair.” It’s financially lazy. From the breakdown shared here , here’s what most SaaS founders get wrong about global pricing: → $100 in San Francisco is a business lunch. → $100 in Manila is a serious capital expense. Force US pricing on developing markets and you voluntarily abandon 70 to 80 percent of global demand. Purchasing Power Parity is not theory. It is conversion math. Smart operators: • Adjust pricing based on local purchasing power • Use PPP models like the Big Mac Index as reference • Auto-detect geography via IP • Dynamically localize pricing But it’s not that simple. Here’s where nuance matters: → Currency risk. If you price in Argentine Pesos and the currency collapses, your revenue collapses with it. In volatile markets, peg to USD and apply structured discounts. → Margin protection. You cannot sell the same full-feature product at 70% less without destroying your US margin. Create a “Lite” tier. Remove heavy server-cost features. Protect contribution margin. → VPN arbitrage. Offer 60% off in Brazil and US users will tunnel through a VPN. Lock discounts to local card BIN numbers or require local SMS verification. → B2B vs B2C dynamics. In B2C, PPP is mandatory. In Enterprise, global brands expect global pricing. Local SMBs do not. Segment by buyer size, not just geography. And here’s the strategic layer most miss: Sometimes pricing low in India or Brazil is not discounting. It’s a land grab. You operate at break-even to dominate user volume, data, and network effects. Treat lower pricing as CAC to block future competitors. Global pricing is not about fairness. It’s about: • Elasticity • Marginal cost • Competitive positioning • Long-term strategic control If your global pricing strategy fits on one line, you are underthinking it. Adapt to purchasing power. Or lose entire continents quietly. ──── Want brutal clarity on your startup? Skip years of wasted effort and stop making expensive mistakes. Get direct advice on your deck, valuation, fundraising, GTM, or other challenges. Book a no-BS 1:1 call with me here: https://lnkd.in/gWV8DT56 💬 Drop your most burning question in the comments. ♻ Repost to challenge founders who still use flat global pricing. #Startups #Entrepreneurship #VentureCapital #Markets #Innovation

Set and forget is not a pricing strategy ! Price--> Design--> Build We know that's what everyone says, but thats an oversimplification of what the entire process should look like. The assumption your pricing was correct in the pre-design phase and doesn't need change is dangerous, dangerous, dangerous !! I have seen too many physical and software products change drastically between initial design to final delivery. Product owners will typically assume that pricing still holds. You have to change that philosophy. In the real world we need a lot more iteration in price: Step 1: Initial Price: This stage you quantify the value and set an initial target price. This is a combination of internal/external research, some value quantification and pricing knowledge. Step 2: Design: With that price info, the product team designs a product that hits product and profitability targets. This is also where you need to keep track of the product margins. Often product will go design a better product at the expense of higher cost, and margins suffer before launch. Step 3: Reprice: Now that we know the new design constraints that impact the profitability, this stage gives you the opportunity to reprice the product based on the design. If substantial value has been added, price should go up. Do not fall into the 'lets over deliver on value and keep price same' trap. Step 4: Build: Now with that new price info and product roadmap the product goes through the build stage. Step 5: Pre launch reprice : Now significant time may have passed since last price review. The market for the product, the economy etc may have changed. This stage can assist in making last changes before product goes out. Good time to also establish guardrails for price performance, discount strategy, or sales strategy. Step 6: Launch: Goes without saying the product is out in the real world. Great way to capture feedback. Also a stage where performance is measured against the price guardrails. Step 7: Reprice 3: Based on sales feedback, you start charting next steps. Selling too slow, you may need discount or reprice. Selling too fast, it may be overdelivering on price vs value. Pricing metric may need change. Fx may have changed. This is the price adjustment stage, should be annual or semi annual. You can incorporate these steps into new product introduction framework or annual or semi annual pricing strategy process, either ways it will help establish good pricing principles in the org. I know of many products that once designed were never repriced years into its life.. Surely things must have changed all those years... Think of Pricing as a lifecycle !! -------------------------- We are in #Pricingtribe.

Inflation isn’t just an economic challenge—it’s a test of agility for businesses. As costs rise and purchasing power shifts, companies that rely on gut instinct risk falling behind. The real winners? Those who use data-driven insights to navigate uncertainty. 1️⃣ Understanding Consumer Behavior: What’s Changing? Inflation reshapes spending habits. Some consumers trade down to budget-friendly options, while others delay non-essential purchases. Businesses must analyze: 🔹 Spending patterns: Are customers shifting to smaller pack sizes or private labels? 🔹 Channel preferences: Is there a surge in online shopping due to better deals? 🔹 Regional variations: Inflation doesn’t hit all demographics equally—hyperlocal data matters. 📊 Example: A retail chain used real-time sales data to spot a shift toward economy brands, allowing it to adjust promotions and retain price-sensitive customers. 2️⃣ Pricing Trends: Data-Backed Decision-Making Raising prices isn’t the only response to inflation. Smart pricing strategies, backed by AI and analytics, can help businesses optimize margins without losing customers. 🔹 Dynamic pricing models: Adjust prices based on demand, competitor moves, and seasonality. 🔹 Price elasticity analysis: Determine how much a price hike impacts sales before making a move. 🔹 Personalized discounts: Use customer data to offer targeted promotions that drive loyalty. 📈 Example: An e-commerce platform analyzed customer behavior and found that small, frequent discounts led to better retention than infrequent deep discounts. 3️⃣ Demand Forecasting & Inventory Optimization Stocking the right products at the right time is critical in an inflationary market. Predictive analytics can help businesses: 🔹 Anticipate demand surges—especially in essential goods. 🔹 Optimize supply chains to reduce excess inventory and prevent stockouts. 🔹 Reduce waste in perishable categories like F&B, where price-sensitive demand fluctuates. 📦 Example: A leading FMCG brand leveraged AI-driven demand forecasting to prevent overstocking of premium products while ensuring budget-friendly variants were always available. 💡 The Takeaway Inflation isn’t just about rising costs—it’s about shifting consumer priorities. Companies that embrace data-driven decision-making can optimize pricing, fine-tune inventory, and strengthen customer loyalty. 𝑯𝒐𝒘 𝒊𝒔 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒂𝒅𝒂𝒑𝒕𝒊𝒏𝒈 𝒕𝒐 𝒊𝒏𝒇𝒍𝒂𝒕𝒊𝒐𝒏𝒂𝒓𝒚 𝒑𝒓𝒆𝒔𝒔𝒖𝒓𝒆𝒔? 𝑨𝒓𝒆 𝒚𝒐𝒖 𝒖𝒔𝒊𝒏𝒈 𝒅𝒂𝒕𝒂 𝒕𝒐 𝒓𝒆𝒇𝒊𝒏𝒆 𝒚𝒐𝒖𝒓 𝒔𝒕𝒓𝒂𝒕𝒆𝒈𝒚? 𝑳𝒆𝒕’𝒔 𝒅𝒊𝒔𝒄𝒖𝒔𝒔 𝒊𝒏 𝒕𝒉𝒆 𝒄𝒐𝒎𝒎𝒆𝒏𝒕𝒔! #datadrivendecisionmaking #dataanalytics #inflation #inventoryoptimization #demandforecasting #pricingtrends

Leaders often view price increases as necessary for margin protection. In my experience, the strategic risk is underestimating how consumer dissatisfaction reshapes revenue stability and long-term financial performance. When trust erodes, product demand patterns shift faster than financial models forecasting a bear market. Reality is the best teacher. “PepsiCo announced (February 3rd) that it will reduce the prices of its snack brands, including Lay’s, Doritos, Cheetos, and Tostitos, by up to nearly 15% after receiving feedback from unhappy consumers. The lower retail prices will begin rolling out ahead of the Super Bowl party food shopping. PepsiCo says they did this because consumers have become more price sensitive and have been shifting to store brands or cutting back on snack purchases altogether. The company also agreed to reduce prices and streamline its product lineup as part of an arrangement with activist investor Elliott Investment Management. PepsiCo adjusted its strategy to regain volume and trust because of consumer feedback. “per a recent article from NPR. There are three considerations for leaders in this story: ▶️Even small increases can materially reduce customer lifetime value and disrupt revenue forecasts ▶️Declining sentiment toward your product/service raises customer acquisition costs and slows market expansion ▶️Poorly managed price changes limit strategic flexibility requiring more resources to support later adjustments Before a price increase, obtain a financial analysis that incorporates both economic data and projected customer sentiment. Validate that your organization has a communication strategy designed to maintain trust and protect long term demand. Assess the partnership with marketing, product, and customer experience leaders to stress test the pricing decision across multiple scenarios, including retention impacts and reputational risk. CFOs who treat pricing as both a financial and behavioral inflection point drive sustainable growth. Check out the February 3 , 2026 article on the NPR website, “Pepsi will cut prices on Lay's, Cheetos by as much as 15%” #RiskManagement #CFO #Leaders Inside Edge Risk Advisors LLC 

Uncomfortable Truth for Pricing Strategy: Customer value isn't guesswork. Think pricing is all about costs? Think again. Online value research reveals what customers truly value and are willing to pay for. Here's what happens when companies embrace value-based pricing: → True Value Discovery A vending machine company discovered untapped value in their premium service and better-quality product. Result? $40M additional annual revenue with no loss in sales. → Customer Understanding One dashcam manufacturer found that women had completely different value drivers than men and were willing to pay 25-30% more. Understanding this doubled their projected sales. → Market Segmentation By matching prices to different market segments' willingness to pay, a corporate training provider drove 40% revenue growth. → Consistent Results Our client successes show the power of value-based pricing: - SaaS company raised prices 41% without losing customers - Streaming service doubled revenue through strategic pricing - Industrial components manufacturer grew sales 20% while raising prices 15% The truth? When you understand true customer value, pricing becomes your most powerful growth lever. Are you ready to let data drive your pricing decisions? #PricingStrategy #BusinessGrowth #ValueBasedPricing

Selling to ENT without changing your pricing model is like showing up to a black-tie event in flip flops. MM pricing models don’t survive in enterprise sales. Why? Because selling 1,000 licenses to an enterprise isn’t 20x harder than selling 50 - but if you don’t adjust your pricing strategy, it will be 20x more painful. Enterprise buyers don’t think in per user terms. They think in budgets, forecasts, and cost centers. They want predictability, not a CPQ nightmare where they’re adjusting seat counts every quarter. If you’re moving upmarket, here’s how to avoid looking like a tourist at the grown-ups’ table: 1. Kill per-user pricing for large accounts. Enterprise CFOs see per-user models as a ticking time bomb...every new hire adds cost. Instead, sell in committed tiers, annual volume contracts, or all-you-can-eat licenses. - Instead of “$50 per user, per month,” structure it as, “$X for up to 1,000 users.” - Price for usage, not headcount - think storage, API calls, transactions, etc. 2. Enterprise doesn’t “expand naturally.” Build in expansion from day one. For MM, you can land small and grow. Enterprise doesn’t work that way. - Ramp pricing: Year 1 at 60%, Year 2 at 80%, Year 3 at 100%. Predictable growth, no CFO freak-outs. - Auto-expansion clauses: If usage exceeds X%, licenses auto-scale. Protects you from procurement pulling a “we’ll just add seats later” stunt. 3. Enterprise buyers expect to “win.” Give them a win - without losing. These buyers are trained to negotiate. They want a lower per-unit cost, but they’ll commit bigger dollars to get it. - Introduce an ENT Rate...lower per-unit cost, but higher minimum commit. CFOs love “efficiency,” and you get more ARR locked in. - Structure custom packaging that makes them feel special. Limited access to beta features, priority support, or bundled services. Want to win in enterprise? Stop selling like an SMB rep. Price for scale, control the expansion, and let procurement “win” on terms that make your CFO smile.

I see a lot of PPC’ers talking about bucketing products into different campaigns based on performance as the holy grail. But almost no one mentions this is a reactive strategy. Let me explain. Great minds have developed scripts to segment your product based on historical performance, driven by the number of clicks, achieved ROAS or CPA. I have implemented this strategy in several accounts with great success, but in my opinion, this strategy has one flaw. It is a reactive strategy. You need a proactive strategy to beat the competition. Google Shopping is a platform where people can compare products very easily between different retailers. Therefore, price is the major deciding factor whether people click on your ad or not. What if your products were well-priced in the period your script/tool is getting the data from? This does not have to be the case in the future. So with this strategy, we are always lagging (slightly) behind. → We need to combine price benchmark data with this historical performance data. Also, adding first-party data is very welcome to decide which label a product eventually suits best. Think about: - Margin - Return rate - Stock (if your turnover rate is rapid, and your stock is limited, you may want to take a step back in pushing the product) If you have this data on SKU level you can create new labels with this combined data. How? → Install a script to label your products on historical performance → Install a script to get price benchmark data on SKU level → Create a spreadsheet where you can combine this output on SKU level → Add this first-party data to this sheet → Think about how heavily you want to weigh each factor. → Give the SKUs a final grade. → Upload this sheet as an additional feed → Segment your campaigns based on this final grade.  → Adjust your bidding strategy accordingly For example: - Historical performance = over Index = 3 points - Princebenchmark = below average = 2 points - Margin = High = 1,5 point - Stock = above average = 1,5 point - Return rate = below average = 1 point Total 9 points - Label = Leader - Historical performance = below index = 1 point - Pricebenchmark = above average = 1 point - Margin = low = 0,5 point - Stock = average = 1 point - Returnrate = above average = 0,5 point Total 4 points - label = Bleader These thresholds and the amount of labels you can adjust to your situation. *This advanced strategy may also have some shortcomings. - Not all retailers have price benchmark data available on all SKUs.  You need to have fallback values for those SKU's. - We have to rely on Google Merchants benchmark data to be up to date. - Too much switching between buckets could harm the algorithm. But hey, we need to test new strategies to beat the competition! Keen to hear your thoughts. ---------------- I am Ruben Runneboom I frequently share my insights on Google Ads, E-commerce, Performance max and Productfeed optimization. Stay tuned for more!

Competitive pricing isn't just about matching or undercutting competitors—it's a foundational, phase 2 pricing capability that, when used effectively with advanced analytics, can serve as the basis for dynamic pricing models, new product introduction strategies, and long-term pricing strategies. It's about smart positioning to boost market share, enhance profit margins, and drive sustainable growth. How can competitive pricing fuel your business success? • Penetration Pricing: Want to disrupt the market? Set prices lower than competitors to capture market share rapidly. This approach is particularly effective for emerging brands looking to make an immediate impact. Brands like Netflix and Xiaomi have successfully used penetration pricing to gain market share by offering lower prices initially. Competitors can use consumer research and advanced analytics-based insights to understand price competitiveness versus perceived value and determine the optimal pricing strategy for new product introductions. • Price Skimming: Aiming to maximize early profits? Start with a higher price to target early adopters, then gradually lower it to reach broader audiences. Advanced analytics help forecast demand curves and determine the ideal timing for price adjustments. Brands like Apple and Sony frequently use price skimming when launching new products, such as smartphones or gaming consoles, to maximize early profits from loyal customers. • Premium Pricing: Ready to command a premium? Create a perception of superior quality or exclusivity. Use data to understand customer willingness to pay and to segment markets effectively, allowing your brand's value to justify higher prices. Luxury brands like Rolex, Gucci, and Lululemon use premium pricing to position their products as high-quality or exclusive, justifying higher price points. • Intelligent Price Indexing: Want to stay competitive without sparking a price war? Use smart price indexing to strategically align specific product and customer segments with competitor prices while setting others slightly higher or lower based on segmentation, price elasticity insights, and optimal competitor price gaps. This approach allows you to selectively take the price off the table—indexing higher on certain items while knowing that only a certain percentage of customers will react to price differences. This self-segmentation helps drive profitability while maintaining competitiveness. Analytics can reveal where you can stand out—whether through customer experience, product features, or added services. Crafting an effective competitive pricing strategy goes beyond choosing a tactic. It requires understanding market dynamics and competitor behavior and clearly defining your value proposition. Using advanced analytics empowers smarter pricing decisions and drives growth. Check out our latest article on effectively using competitor pricing intelligence to drive profitable growth in your business.

From 15% to 31% close rate in weeks. One pricing decision changed their business. Here's how to replicate this result... Something I've noticed working with B2B founders: Most are making pricing decisions based on gut feelings… …instead of actual market data. Here's what happens: They launch with pricing that "feels right" or matches what competitors charge. Then they wonder why deals aren't closing or why they're constantly negotiating down. The problem? They're missing the real insights sitting in their own data. For example, I worked with a SaaS founder who was pricing at $99/month because that's what seemed "reasonable." But when we analyzed his deal patterns, we discovered something interesting: Customers who paid $199/month had 3x higher retention rates and generated 40% more referrals. Why? Because higher-paying customers were more committed and saw greater value. We also found that 67% of his lost deals weren't about price - they were about unclear value positioning. So we restructured his pricing strategy based on: - Deal pattern analysis - Competitive context research - Customer feedback extraction - Growth opportunity mapping Result? His average deal size increased by 180% and close rate jumped from 15% to 31%. The lesson? Stop guessing what your product is worth. Start analyzing what your customers actually pay for and why. Your pricing should reflect real market evidence, not assumptions. ________________________________ 👋 I’m Marina Kogan 🌊 Follow for more insights on GTM strategies

People often ask whether pricing can be optimized. The answer is yes... but only if you are optimizing the right thing. It is not the prices themselves that should be optimized. It is the pricing strategy. That may sound like a subtle distinction, but in practice, it changes everything. Retail prices are not static decisions. They are outcomes of a complex environment. Costs shift. Competitors react. Demand fluctuates. A price that works in January may be a mistake by February. Trying to optimize a specific number in that context is like trying to hit a moving target while the wind is changing. But pricing strategies is where we have control. A pricing strategy is a rule. It is a logic that takes the current environment and turns it into an action. It tells you what price to post, given what you know. That is the decision. And that is what we can test, compare, and improve over time. When we run experiments, we are not asking whether $19.99 beats $17.49. We are asking whether Strategy A, which might lean on cost-plus logic, outperforms Strategy B, which might use elasticity estimates and competitor tracking. And we can do that experimentally. If I have 200 products, I can apply Strategy A to half and Strategy B to the other half. Let them run. Prices will change daily, even hourly. But over time, I will see which rule generates more margin, higher conversion, or better sell-through (whatever outcome I care about). This is not about locking in a number. It is about finding the decision logic that learns and adapts with the market. In Sequential Decision Analytics, we do not fixate on the outcome of one decision. We focus on the policy: the mapping from information to action. That is what gives us flexibility. That is what makes experimentation meaningful. And that is what allows us to learn systematically. In pricing, as in most dynamic environments, we do not optimize answers. We optimize policies. And that shift in mindset changes how we build, test, and improve every decision we make. #PricingStrategy #DecisionIntelligence #SequentialDecisionAnalytics #DynamicPricing #PolicyOptimization #RetailAnalytics #ABTesting