Pricing Strategy Formulation

📦 Jobs-Led Pricing: A 10-step framework for transforming feature-led products into monetization-ready, jobs-based pricing models. Built on 4 stages: 1. Product (Discovery Layer) 2. Value (Logic Layer) 3. Customer (Preference Layer) 4. Pricing (Monetization Layer) 🔹 STAGE 1: PRODUCT [Discovery Layer] 🔹 Step 1: Feature Inventory What it is: ▪️ List every feature, tool, and function in the product
▪️ Include hidden, premium, or internal-use features Why it matters: ▪️ Creates a complete picture of what’s being delivered
▪️ Prevents missing monetizable elements 🔹 Step 2: Feature to Plan Mapping What it is: ▪️ Show how features are bundled into pricing plans today
▪️ Expose arbitrary or legacy packaging logic Why it matters: ▪️ Reveals pricing misalignment with value
▪️ Highlights over- or under-incentivized plans 🔹 Step 3: Feature Usage Mapping What it is: ▪️ Track actual customer usage of each feature
▪️ Look for engagement patterns by segment Why it matters: ▪️ Identifies “dead weight” vs “core value” features
▪️ Helps assess ROI per feature 🧠 STAGE 2: VALUE [Logic Layer] 🔹 Step 4: Feature Valuation What it is: ▪️ Qualitatively or quantitatively assign value to each feature
▪️ Use proxies: time saved, revenue unlocked, cost reduced Why it matters: ▪️ Establishes which features are worth monetizing
▪️ Anchors the price-to-value logic 🔹 Step 5: Jobs Identification What it is: ▪️ Identify core Jobs-To-Be-Done (JTBD) your product enables
▪️ Use user interviews, surveys, task analysis Why it matters: ▪️ Shifts the model from features to outcomes
▪️ Connects monetization to customer success 🔹 Step 6: Feature–Jobs Mapping What it is: ▪️ Map each feature to one or more customer Jobs
▪️ Create a logic layer: feature → outcome → value Why it matters: ▪️ Bridges product design with pricing strategy
▪️ Enables bundling and upsell opportunities around outcomes 🎯 STAGE 3: CUSTOMER [Preference Layer] 🔹 Step 7: Rank Jobs What it is: ▪️ Prioritize Jobs by importance and frequency
▪️ Use customer feedback and behavior data Why it matters: ▪️ Surfaces which outcomes matter most
▪️ Enables tiering or segmentation logic 🔹 Step 8: Value Jobs What it is: ▪️ Quantify perceived value of each Job
▪️ Use surveys, conjoint analysis, BWS, or proxies Why it matters: ▪️ Links value perception to potential willingness to pay
▪️ Avoids feature-based pricing traps 💰 STAGE 4: PRICING [Monetization Layer] 🔹 Step 9: Value Capture [%] Analysis What it is: ▪️ Decide what % of value created you can capture
▪️ Compare to industry benchmarks or strategic posture Why it matters: ▪️ Sets pricing defensibility
▪️ Avoids overcharging or leaving money on the table 🔹 Step 10: Pricing Metric / Model What it is: ▪️ Choose pricing metric: per seat, usage, credits, % of revenue, hybrid
▪️ Align it to how value is delivered + Jobs solved Why it matters: ▪️ Ensures pricing scales with value
▪️ Sets the business up for sustainable revenue growth #Pricing #JLP

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.

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.

At $10M+ ARR, You are losing money. Not because of bad product, But because of bad pricing. Why pricing? → Competitor pricing weakens positioning → Pricing doesn’t match customer value → Customers stay on the cheapest plan → No upsells, no expansion revenue → Too few users on annual plans → Enterprise deals lack flexibility → Pricing is never tested Lack of pricing strategy directly affects your revenue. Here are 7 steps to fix it. 1. Audit pricing by revenue segment → Where is pricing suppressing upgrades? 2. Reposition pricing against competitors → Own a category, not just a price point. 3. Expand revenue streams → Upsells, add-ons, usage-based models for high-value users. 4. Charge based on value, not just cost → Align pricing with impact and willingness to pay. 5. Move customers to annual → Build ACV and retention with incentive-based annual pricing. 6. Enable enterprise flexibility → Custom contracts, volume discounts, and deal-based pricing. 7. A/B test pricing regularly → At this scale, small price shifts = millions in ARR gains. At $10M+, pricing isn’t just a strategy, it’s a competitive advantage. P.S. How often are you testing your pricing strategy? ♻️ If you find value, let others benefit too. __________________________________________ Ready for more SaaS pricing insights? Follow me, Marcos Rivera🔔

"We need to update our pricing" Every Product Marketer knows that sinking feeling. You're handed a complex pricing project with zero resources, minimal support, and an aggressive timeline. I teamed up with pricing expert Rob Litterst to create the PMM’s guide to pricing. Here's the playbook 👇 👉 Research: Lost deals tell you more than won ones. Study the patterns in rejections, usage data, and expansion triggers. 👉 Strategic Alignment: Test your assumptions. Map features to value. Find your market fit through evidence, not gut feel. 👉 Stakeholder Collaboration: Finance owns targets. Product owns constraints. Sales owns competitive intel. Blend all three. 👉 Execution: Split your focus - internal metrics and timelines, plus external rollout and sales enablement. 👉 Tools: Templates, competitor databases, and frameworks turn strategy into action. Save this framework for when that pricing project next lands on your desk.

Most startups play defense when discussing pricing with customers. They dance between asking for too little, leaving money on the table, and asking for too much, only to lose the customer’s interest. The very best companies lead their customers in that dance. They use pricing as an offensive tool to reinforce their product’s value and underscore the company’s core marketing message. For many founding teams, pricing is one of the most difficult and complex decisions for the business. Startups operate in newer markets where pricing standards haven’t been set. In addition, these new markets evolve very quickly, and consequently, so must pricing. But throughout this turmoil, startups must adopt a process to craft a good pricing strategy, and re-evaluate prices periodically, at least once per year. The Three Core Pricing Strategies There are only three pricing strategies startups should pursue: Maximization, Penetration and Skimming. They prioritize revenue growth, market share and profit maximization differently. Maximization (Revenue Growth) - maximize revenue growth in the short term. Startups should pursue maximization when there are no clear differences in customer segments’ willingness to pay, and when the optimal short term and long term prices are equal. Many mid-market software companies price with the goal of revenue maximization, negotiating for the highest possible price in each sale. Penetration (Market Share) - price the product at a low price to win dominant market share. A bottoms-up strategy lends itself to penetration pricing. Price low to minimize adoption friction, grow quickly, and then move up-market after developing broad adoption. Penetration pricing leads to land-and-expand sales tactics. Expensify, Netsuite, New Relic, Slack follow this model. Penetration prioritizes market share. Skimming (Profit Maximization) - start with a high price and systematically broaden the product offering to address more of the customer base at lower prices. Skimming is widespread in consumer hardware. Apple sells the latest iPhones at the highest prices, and repackages older models at lower prices to address different customer segments. As Madhavan Ramanujam tells it, Steve Jobs was both a product genius and pricing genius. By pairing the two skills, he led Apple to record-breaking profits quarter after quarter. Skimming is less common in the software world because few startups develop a product at launch that will be accepted by the most sophisticated customers (and those willing to pay prices that generate the greatest margin). There are exceptions: Oracle’s database, Tanium’s security product, Workday’s human capital management software. Read the full post here : https://lnkd.in/g-mxQiV9

When to Let Your Tiers Fall? (Almost wanted to write "tears") Pricing Tiers, like we discussed yesterday, Are best when based on revenue data, Using the Normal Distribution Curve. However, that approach hinges on some assumptions: 1. The market is stable and there is certainty. 2. The number of suppliers is consistent. 3. There is no unanticipated inflation. 4. Production costs are predictable. If any of these assumptions are violated, Pricing strategy should be revisited. Current situation in Market: - SaaS and AI-tool suppliers are increasing. - Market stability is challenged for many reasons. - Inflationary pressure is high, with looming tariffs. - Production costs are fluctuating rapidly everywhere. Typically, the Basic and Premium Tiers Cost more per unit on average than The Middle Tier for producers. This is because costs of production Follow a certain U-shaped curve. (Not going into details here.) If we take the same example from yesterday: 1. Base tier is priced at $20 and costs $22 per unit. ---> This is a $2 loss per unit sold. ---> 14% of 1000 = 140 units sold. ---> Total loss = $280. ---> Demand can grow rapidly during uncertainty. -----> Heavy losses added on. 2. Middle tier is priced at $30 and costs $20 per unit. ---> This is a $10 profit per unit sold. ---> 68% of 1000 = 680 units sold. ---> Total profit= $6,800. ---> Demand can be stable even in uncertainty. -----> Profitability is reliable. 3. Premium tier is priced at $40 and costs $25 per unit. ---> This is a $15 profit per unit sold. ---> 14% of 1000 = 140 units sold. ---> Total profit= $2,100. ---> Demand can decrease rapidly in uncertainty. -----> Profits can shrink quickly. NET PROFIT = $8,620. During uncertainty, if we "let the tiers fall", And switch to offering only Middle Tier: * Priced at $30 and costs $20 per unit. * Caps out at producing 820 units. * Costs more to produce more. NET PROFIT= $8,200. Actionable Insights: 1. Select safer alternative for pricing in uncertainty. 2. Focus on increasing the value provided in one tier. 3. Offer coupons, incentives, & discounts for switching. 4. Keep a close eye on what your competitors are doing. 5. Ensure that you do not damage reputation in your haste. 6. Hire experts to optimize customer satisfaction and strategize. Follow Dr. Kruti Lehenbauer & Analytics TX, LLC for #PostitStatistics #DataScience #AI #Economics tips To grow your business or your career, strategically! P.S.: As a consumer, do you prefer to see tiered pricing or a flat-rate price for your favorite AI/SaaS tools?

Pricing is strategy. Not just math. One thing is clear: most businesses don’t have a pricing problem, they in fact have a value articulation problem. Pricing is not just about costs, competitors, or margins. It’s a direct reflection of your business strategy. The strongest pricing models are built on three core truths: 1️⃣ Customers don’t buy products. They buy perceived value. If your customers are haggling over price, the issue isn’t your pricing—it’s your positioning. The right customers will pay a premium if they see the impact. Price elasticity is not just a demand function; it’s a trust function. 2️⃣ Price is not a number. It’s a narrative. The reason luxury brands, SaaS companies, and airlines charge vastly different prices for essentially the same core offering? Storytelling. Pricing should reinforce your value proposition, not dilute it. 3️⃣ Data-driven pricing wins, but intuition refines it. A/B tests, willingness-to-pay surveys, and revenue models are great, but pricing is ultimately a human decision. Understanding psychological triggers (anchoring, decoy effects, bundling) separates a good pricing strategy from a great one. The best pricing leaders know when to listen to data and when to trust experience. 🚀 Pricing is the single biggest profit lever in any business. A 1% price improvement can yield a 10%+ profit increase, but only if done right. So the real question is: Are you pricing strategically, or are you just playing defense? Would love to hear your thoughts on what’s the most overlooked aspect of pricing in your industry? #PricingStrategy #BusinessGrowth #StrategyMatters #RevenueOptimization #CompetitiveAdvantage #ConsultingLife #BusinessConsulting #MarketStrategy #DataDrivenDecisionMaking #ValueBasedPricing #LeadershipInsights #FutureOfBusiness #SmartThinking #InnovationStrategy #CustomerPsychology