Pricing: Capturing the Value You Create
Pricing is the most powerful lever in the P&L — a 1% improvement in price typically has 3-5x the profit impact of a 1% improvement in volume, yet most companies leave significant money on the table.
The Most Neglected Lever
McKinsey's analysis of the Global 1200 found that a 1% improvement in price, holding volume constant, improved operating profit by an average of 11.1%. The same 1% improvement in variable costs improved profit by 7.8%, and a 1% improvement in volume by 3.7%. Pricing is the most powerful profit lever available to most businesses — yet it receives less systematic attention than cost reduction or volume growth.
This is partly because pricing is uncomfortable. Raising prices feels like taking money from customers. Salespeople resist it because it makes their jobs harder. And because customers complain about price increases more loudly than they express appreciation for product improvements, managers under-weight the opportunity.
The result: most businesses are chronically underpriced relative to the value they deliver.
Value-Based Pricing: The Right Framework
There are three approaches to setting prices. Two of them are wrong.
Cost-plus pricing adds a margin percentage to the cost of production. A product that costs $50 to make gets priced at $75 for a 50% gross margin. The problem is that costs have nothing to do with what customers value. If customers would pay $200 for that product, you've left $125 on the table. Cost-plus pricing is internally focused when pricing is fundamentally a customer-facing decision.
Competitive pricing sets prices based on what competitors charge. This is slightly better — it at least acknowledges customer choice — but it still fails to capture differentiation. If your product is meaningfully better than competitors', you should charge more. If you price at parity, you either give away value or signal no differentiation.
Value-based pricing starts from the customer's perspective: what is this worth to them? It requires understanding the economic value of your product to the customer, the next best alternative, and the price differential that reflects your superiority.
Price Elasticity
Price elasticity measures how much demand changes in response to price changes. Elasticity = % Change in Quantity / % Change in Price. An elasticity of -2 means a 10% price increase leads to a 20% volume decline.
Understanding elasticity matters for revenue optimization. For a price increase to improve revenue, elasticity must be less than -1 (inelastic demand). For a price decrease to improve revenue, elasticity must be greater than -1 (elastic demand).
Products with inelastic demand (elasticity between 0 and -1) have characteristics that reduce price sensitivity:
- High switching costs (enterprise software)
- Few substitutes (essential medicines, utilities)
- Small share of buyer's total budget ("pennies per day" framing)
- High emotional involvement (luxury goods, status items)
- High cost of being wrong (safety equipment)
Products with elastic demand are more commoditized, with easy substitution and active price comparison. Airlines, gasoline, and consumer electronics tend toward higher elasticity.
Price Discrimination: Charging Different Prices to Different Buyers
Price discrimination — charging different prices to different customers for the same product — is among the most value-creating pricing strategies available. The goal is to extract more consumer surplus from high-value buyers while still serving price-sensitive buyers.
First-degree price discrimination charges each customer their maximum willingness to pay. Theoretically optimal but practically impossible at scale — you can't know each customer's exact reservation price. Negotiation-based markets (car dealerships, enterprise software deals) approximate this.
Second-degree price discrimination uses product design to let customers self-select into different price tiers. Airlines offer economy, business, and first class — different service levels at different price points. The key is that the product differences must be real enough that high-value customers prefer the premium tier, not merely a price barrier.
Third-degree price discrimination charges different prices to different demographic groups or segments. Student discounts, senior pricing, geographic pricing. This works when the segments have genuinely different price sensitivity and arbitrage between segments is limited.
Airlines are masters of price discrimination. The same seat on the same flight might sell for $200 (booked months in advance, Saturday return, no changes) or $1,200 (business traveler, last-minute booking, flexible ticket). Both seats have near-identical costs for the airline. The price differences exploit the fact that leisure travelers are price-sensitive but plan ahead, while business travelers need flexibility and are price-insensitive. The Saturday stay rule (cheaper if you stay over Saturday) was explicitly designed to separate business from leisure travelers — business travelers rarely want to stay over weekends. Dynamic pricing algorithms now make this real-time, adjusting hundreds of prices per second based on demand signals.
Dynamic Pricing
Dynamic pricing sets prices in real time based on demand, supply, and competitive conditions. Uber's surge pricing is the highest-profile example — prices rise when driver supply is low relative to demand, rationing demand and attracting more drivers.
The economic logic is impeccable: dynamic pricing allocates scarce capacity to its highest-value uses, sends signals that balance supply and demand, and captures more of the value created when demand is high. But it has significant customer backlash risks when implemented clumsily.
The keys to successful dynamic pricing:
- Transparency about how and why prices change
- Maintaining some price predictability for customers who want it
- Ensuring the algorithm doesn't produce "price gouging" optics during emergencies
- Building customer perception that dynamic pricing benefits them (lower prices when demand is low) rather than purely exploiting them (higher prices when they're stuck)
Psychological Pricing
The rational economic model of pricing — customers calculate value, compare to price, and make optimal decisions — is a useful approximation but not an accurate description of how pricing actually works psychologically.
Anchoring: The first price shown affects all subsequent judgments. Williams-Sonoma famously found that adding a premium breadmaker to its catalog increased sales of its standard breadmaker — the premium version made the standard one look like a bargain, even though no one was buying the premium version.
Price-quality inference: Customers often use price as a signal of quality, especially when quality is difficult to evaluate directly. A wine study found that subjects reported higher enjoyment from the same wine when told it cost $90 than when told it cost $10. Premium pricing can actually increase perceived value.
The 9 effect: Prices ending in 9 ($19.99 vs $20.00) consistently outsell round numbers in consumer markets, because people process the left digit first and perceive a category difference between 19 and 20, even though the actual difference is one cent.
Decoy pricing: Adding a third option that makes one of the other two look more attractive. In subscription pricing, adding a $500/year print-only option next to $500/year web+print (when web-only costs $200/year) dramatically increased web+print subscriptions — the print-only option was a decoy that made web+print feel like a deal.
- A SaaS company charges $50/month and has 10,000 customers. Their analysis shows price elasticity of -0.8. Should they raise prices? What additional information would you want before making that call — and what does elasticity alone miss?
- Airlines charge business travelers 5-6x more than leisure travelers for the same seat. Customers know this and largely accept it. But when Wendy's announced dynamic burger pricing in 2024, the backlash was immediate. Why does price discrimination feel fair in some contexts and exploitative in others — and what determines which side of that line a business falls on?
- Value-based pricing requires knowing what customers would pay — but customers routinely understate their willingness to pay in surveys and negotiations. How do you build a credible EVC model when the data you need is systematically biased?
- Many startups deliberately underprice to accelerate adoption, then plan to raise prices later. Under what conditions does this strategy work, and when does it create a "pricing ceiling" that permanently caps the business?