Strategic Pricing Models

12,6 billion euros – BP and Total are paying this record sum to develop 7 GW of offshore wind in Germany. Working in an energy intensive industry and with my background in offshore wind, I am looking at this with very mixed feelings.    Sure, from a political point of view it is a success. For the first time, companies are paying money for the right to develop wind farms in Germany. What was advanced in the form of long-term subsidies in the past is now being paid back. In the long run, however, it is a Pyrrhic victory!   It’s not good news for a low electricity price. Even if only 10% of the bid is to be paid in advance. These immense sums must be earned back. The risk is that this will be to the disadvantage of the customers. Both private and commercial customers will have to deal with higher prices. This poses challenges for energy-intensive industries in particular – and underlines the importance of an industrial electricity price for these industries.   It’s not good news for the supply chain industry. Turbine manufacturers are already under great pressure. At a time when we need a stable European supply chain to shoulder the massive expansion of wind energy, high bids intensify this pressure - especially as qualitative criteria, such as carbon footprint, were not taken into account.   And it’s also not good news for offshore wind in Germany. The cost risks for project developers and operators have become significantly higher than in other (European) countries. It is telling that none of the established offshore wind operators were willing to pay so much money upfront, but instead the projects went to large oil and gas multinationals. Companies that have softened their climate targets one after the other in recent months.

I have spent years in the highs and lows of the consumer goods industry but never seen a pricing climate quite like this. Manufacturers are getting squeezed from every direction-tariffs, skyrocketing raw material costs, and relentless supply chain disruptions. The old playbook of raising prices to cover costs? That’s dead. Why? Because consumers are feeling the pressure too. A 2024 Nielsen report makes it clear: today’s shoppers are scrutinizing every dollar they spend, and brands that aren’t strategic about pricing risk losing market share fast. Here’s what I’m seeing from top CPG brands that get it: 1️⃣ Walmart is investing heavily in AI-driven pricing models to keep costs competitive-e-commerce now makes up 18% of total revenue. 2️⃣ PepsiCo is doubling down on pack-size innovation, offering smaller, affordable options to maintain volume without excessive discounting. 3️⃣ Luxury brands are using price elasticity models, testing demand thresholds before rolling out increases-avoiding consumer pushback. 4️⃣ Supply chain resilience is non-negotiable. Companies are shifting manufacturing away from China, despite short-term cost spikes, to avoid future geopolitical risks. The smartest brands aren’t just reacting. They’re rethinking. They’re moving toward Revenue Growth Management (RGM) frameworks that help them: ✅ Optimize pricing and promotions (because blanket price hikes are a losing game) ✅ Focus on margin-smart growth, not just revenue ✅ Leverage data analytics to make smarter, faster pricing decisions Brands that don’t evolve risk eroding profitability or pricing themselves out of the market. CPG leaders who master strategic pricing, operational efficiency, and consumer-driven value creation will own the future of this industry. Are you adjusting your strategy, or just reacting to rising costs? Because in 2025, only the most adaptable brands will win. #CPG #FMCG #PricingStrategy #RevenueGrowth #ConsumerGoods

Stop inviting clients to shop your offer around. Big branding client. Discovery call. They're excited. Then I show them 3 options. Not one. Three. "Why would you give us choices?" they ask. "Doesn't that complicate things?" Actually, it simplifies everything. Here's what 30 years of running two 7-figure businesses taught me about options: • Option 1: DIY (10% price) Digital course. Templates. Self-paced. For those who aren't ready to invest yet. Infinitely scalable. Zero touch from you. They get value. You get a customer. • Option 2: DWY - Done With You (x price) Finite deliverables. Some customization. You do the work together. Sweet spot for most buyers. • Option 3: DFY - Done For You (10x price) White glove. Bespoke. Custom everything. Training, coaching, custom software if needed. You handle it all. They write the check. The magic isn't in the options. It's in what happens next. When you present one option, they think: "Should I buy this or not?" Binary decision. Easy to say no. When you present three options, they think: "Which one should I buy?" The conversation shifts from IF to WHICH. Psychology 101: People hate missing out more than they love getting a deal. Give them one option? They'll shop around. Give them three? They'll shop your menu. Your 10% option captures future buyers. Your 10x option makes your middle option look reasonable. Your middle option? That's where 80% of sales happen. Price anchoring and why it works. But here's what most people miss: Each option must solve the same problem. Just at different levels of involvement. Not different services. Different depths of the same service. What three options could you offer today? Have you tried options in your offer? What happened? Drop a comment below and share your story. Small Business Builders #pricingstrategy #salesstrategy #businessgrowth

"Is $20/month too much for our product?" Instead of guessing, we used the Van Westendorp method to find our pricing sweet spot. 4 questions revealed exactly what users would pay (and we haven't touched our pricing since). Here's the framework any founder can steal: 1. Send a survey to actual users, not prospects We surveyed people already using Gamma. They understood the real value of our product, not hypothetical value. Too many founders survey their waitlist or randomly select people who have never used their product. That's like asking someone who's never driven about car prices. 2. Ask these 4 specific questions - At what price would this be too expensive for you to consider it? - At what price is it expensive but still delivering value? - At what price does it feel like a bargain? - At what price is it so cheap you'd question if it's reliable? These create bookends for perceived value. You're mapping the entire spectrum of price psychology, not just asking "what would you pay?" 3. Plot the responses and find where the lines intersect Graph responses from lots of users. Where "too expensive" and "too cheap" lines cross: that's your acceptable range. Where "expensive but fair" meets "bargain": this is your optimal price point. 4. Test within the range, don't just pick the middle The intersection gives you a range, not a number. We ran pricing experiments within that range to see actual conversion rates. A survey shows willingness to pay; testing reveals actual behavior. 5. Lean towards generous (especially for product-led growth) We chose to be more generous with AI usage than our "optimal" price suggested. Word-of-mouth growth matters more than maximizing initial revenue. Not everything shows up in the numbers. 6. Lock it in and stop tinkering Once you find the sweet spot through data, stick with it. We haven't changed pricing in 2 years. Every month debating pricing is a month not improving product. Remember: pricing is a signal, not just a number (Image: First Principles)

We're moving away from charging for *access* to software and toward a model of charging for the *work delivered* by a combination of software and AI agents. Let’s dive into what’s happening and what it means for you ⤵️ 1. The rise of disruptive AI pricing models Tech companies are realizing they can't solely rely on seat-based subscriptions in an age of AI, automation and APIs where value is disconnected with how many people are logging in. Perhaps Salesforce going all-in on Agentforce (and charging $2 per conversation) was the push the industry needed. Each product category has its own flavor of disruptive pricing. - Legal AI products might charge for a demand package generated by AI or an AI-generated summary. - Creator AI products might charge for the content that gets produced such as a video generation or amount of video created. - GTM products might charge for specific tasks completed or workflows executed by the AI. 2. Selling work, not necessarily success As a customer, I wish I only had to pay for software when it delivered results. But the reality is that true success-based billing won’t work for the vast majority of today’s products. Most products should charge for work output instead. The issue is attribution. You want the customer to get a fantastic outcome — and you want them to recognize that your product powered that outcome. As soon as you start charging for success, the customer begins to rethink the results. 3. Goodbye ARR as we know it? Shifting to these newer value-based pricing models isn't a simple pricing change you can just announce in a press release. It's a business model evolution that looks a lot like the shift from on-prem to SaaS in the first place. These new AI pricing models might mean greater volatility in both usage and spend. Variable margin profiles across products and customers. Seasonal revenue fluctuations. The potential for project-based, non-recurring use cases. Put simply, annual recurring revenue (ARR) continues to get dethroned. — Full post in today’s Growth Unhinged newsletter: https://lnkd.in/ea5eTrVD Things are about to get interesting 🍿 #ai #pricing #saas

Salesforce just fired the starting gun on a seismic shift in how we pay for software. At Salesforce #Agentforce, they announced they’re moving away from the traditional per-seat SaaS model to a consumption-based pricing for their AI agents. This is huge. Why? Because it signals the end of paying just to have access to technology. Instead, we’re moving toward paying for outcomes—the actual value delivered. Think about it. In a world where AI agents can perform the job functions of entire departments, does it make sense to charge per seat? Probably not. Here’s what’s changing: - From access to outcomes: Companies will pay for what the AI actually accomplishes. - From subscriptions to value: Pricing adjusts based on usage and results. - From Software-as-a-Service to Agent-as-a-Service: Technology that collaborates with you as a partner This isn’t just a tweak in pricing—it’s a radical upending of commercial models for large SaaS companies. What does this mean for businesses? - Budgeting will evolve: Costs align directly with value received. - ROI becomes clearer: Easier to measure the direct impact of technology investments. - Greater flexibility: Scale usage up or down based on needs without worrying about seat counts. It’s an exciting time, but also a challenging one. Is every SaaS company ready to embrace a model where companies pay directly for the value they receive? At Uniti AI, we’ve been thinking along these lines. We price our AI agents based on the amount of work they do, not on how many seats a company has. I believe this is the future. What do you think? Is the per-seat model on its way out?

The question I hear most from founders during Sequoia Capital's Arc program is about #pricing. Pricing is one of the most underutilized levers for startups. Why does it matter so much? It has the most direct impact on revenue, and the moment you establish your pricing, you determine your TAM. Getting the pricing metric right is, by far, the most important one. The key is to imagine the future: when you are a large and successful company, how have you changed the world, and what metric correlates best with your success? Hitch your financial wagon to that metric! If you are Figma, success is all designers using the app; therefore, the pricing metrics is per designer seat. If you are VMware, success is all workloads run in virtual machines; therefore, the right pricing metric would have been a virtual machine. A pricing metric is like the genie in a bottle: once you get it out, it is tough to rein it back or change it. The pricing model is about when and how frequently you charge. Recurrent subscriptions are the predominant model for SaaS apps, and usage-based pricing is the model for infrastructure solutions. Usage-based pricing creates a beautiful alignment of incentives but is less predictable. Upfront credit purchases and commitments are efforts to make usage-based practice more aligned with the rigid corporate budgeting processes. You can be the premium solution or the affordable one. Both are legitimate approaches. But your pricing needs to be consistent with the rest of your strategy: with your product and distribution channels.  You can’t have an affordable solution distributed through an expensive enterprise sales force. In this case, you need to sell either online or through inside sales—the product better be simple and the sales cycle quick. Many technical founders are shy about asking for a lot of money for their product. Don’t be. If customers like the product and it delivers value, they will gladly pay for it. Unless you hear customer complaints that you are expensive, then for sure you are underpricing. Calculate the ROI of your product, and take 20% of that value as your price point. How much it costs you to build the solution should not guide your pricing. But you should do a sanity check that you have a decent gross margin. Most companies start by selling a single package. Over time, they realize that different customer segments have different maturity levels and willingness to pay. To price discriminate between these segments, you need to introduce multiple packages.  Start by creating a customer maturity curve to inform your decisions on how many packages you need. The trick is to have the smallest number of packages to cover the broadest range of customer needs. Your packages will change and evolve quickly as your product matures. 

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.

Stop copying competitor pricing. These 4 questions will tell you exactly what your specific customers will pay. When we first launched Attic salt, we spent n no of weeks trying to figure out a pricing strategy that will work. Attic Salt is democratising the fashion by bringing in value at a sharp price yet we have to maintain fair wages for our artisans and  technicians who bring the garment alive with so much innovation,skill and dedication. Then I found the Van Westendorp Pricing Model, a simple 4 question method helps you understand how customers really see your price. Used by brands like Dropbox, HubSpot, and Mailchimp, the Van Westendorp model was developed by Dutch economist Peter Van Westendorp.    Here's how it works… You ask potential customers four key questions about price: 📍At what price would this product feel too cheap to trust? 📍At what price would it feel like a good deal? 📍At what price would it start to feel expensive but acceptable? 📍At what point would it feel too expensive to buy?     Now plot these answers on a graph. The intersection points reveal your: Indifference Price Point → where people are split between “cheap” and “expensive”Optimal Price Point → where hesitation from both ends is minimal Acceptable Price Range → your sweet spot for maximum traction When we used this model, we realized we were underpricing. Customers thought the product was “too affordable to be good.” We adjusted, and sales went up without changing a single feature. If you’re launching something new or entering an unfamiliar market, don’t guess. Use this model. Gut feelings are great for design. Not for pricing. Are you still trusting yours? #PricingStrategy #ConsumerInsights #D2CBrands #FashionBusiness

Pricing and packaging is, IMO, the most underutilized, highest leverage tactic available to founders to make an impact on sales. At Gigya, we started with $10K ACVs and 5 years later were at $250K ACVs, largely due to improvements in pricing and packaging. Unfortunately, there is not much out there on the right way to approach pricing / packaging. Further, AI-based software, especially AI agents & teammates, are disrupting the old models. Specifically, the usual 'per seat' SaaS pricing model is no longer quite relevant when the software is doing alot of the work humans used to do. To help, I've outlined 5 core pricing & packaging pillars for (AI) startups: 1. Platform Pricing (flat or tiered) 2. Seat-Based Pricing (familiar, but can punish success if AI replaces seats) 3. Consumption-Based (pay-as-you-go, works well with AI compute) 4. Add on Pricing (A la carte features, with big upsell potential) 5. Outcome-Based (ultimate alignment, but hard to measure + forecast) Key takeaway: Think about how your product delivers ROI - then tie your model to that. It's probably going to be using a combination of these pricing strategies. Keep in mind what approaches are most likely to maximize value capture upfront (average contract value) and over time (net dollar retention). As a rule of thumb, aim for net dollar retention in the 120-140% to be best in class. Would love to hear your take - what's working (or not) in pricing, especially in this new AI software world?