Price Before Product: Madhavan Ramanujam's Masterclass on Monetizing Innovation

Ramanujam, a senior partner at Simon-Kucher, says he stumbled into pricing at Stanford, where a venture capitalist asked how he knew his startup would make money and he admitted the spreadsheet assumptions were made up. Soon after, Simon-Kucher called him. He joined to understand the science behind pricing, not only the art, and has worked with more than 250 companies, including Uber, Asana, DoorDash and LinkedIn.

He wrote Monetizing Innovation out of frustration with companies that spent years building and then wanted a price plan "yesterday". When his firm benchmarked innovations, 72% failed commercially, mainly because nobody checked willingness to pay early enough. Had they done so, he says, they could have pivoted the product or built something more meaningful.

On where pricing should live, he says it is cross-functional, and a decade ago he would have put it in finance as a counterweight to sales. He now argues it belongs on the product side, because products should be designed around what customers need, value and will pay for. The book's subtitle makes the point: how smart companies design their products around the price.

Ramanujam says that asking whether someone likes a product is a very different question from asking whether they like it at $200. If pricing is left out of validation, you hear what you want to hear. Willingness to pay is a proxy for whether people actually value the product and how badly they want it.

He reframes what price is: a measure, like a liter measures volume, price measures value. So the same sales pitch you will use after launch should be tested months earlier, ending with the question of whether the customer would pay. If the answer is no, the most important follow-up is why, and the answers can reshape the product or even the strategy.

Lenny summarizes the advice, and Ramanujam points to First Round's phrase for it: "price before product, period". Founders do not get to choose whether they will have a pricing conversation with customers, only when. And he says there is no such thing as too early; even at the idea stage you can check whether anyone would pay, then keep refining as you go.

Porsche checked whether the market wanted a Porsche SUV before drawing a blueprint, then battle-tested every feature in car clinics. A big cup holder stayed because customers loved it and would pay, while a six-speed manual transmission was dropped. The resulting Cayenne, he says, accounts for more than half of Porsche's profit.

His software example is a two-sided marketplace that already monetized sellers and wanted a product for buyers. After a design-thinking offsite and a shortlist of 40 ideas, the CEO asked how they knew people would pay, and they did not. Testing wireframes revealed that the team's favorite idea, showing which Facebook connections had bought from a seller, drew hostility or indifference from every customer group.

His headline lesson for product people is that you cannot prioritize a roadmap without a willingness-to-pay conversation. Across hundreds of companies, he says, about 20% of what you build drives 80% of willingness to pay. The danger is that this 20% is often the easiest part, which teams ship free as an MVP, and then they chase the other 80% that drives little value.

Lenny notes that Porsche worked from a target price to a product while the marketplace used willingness to pay to prioritize features. Ramanujam agrees that either approach works: productize to a price point, or use willingness to pay to rank what to build.

Ramanujam says that asking customers what you should charge produces garbage, since that is the seller's job. His first technique is relative framing: people are "absolutely meaningless, relatively super smart". Ask a customer to index your value against a known product such as Salesforce at 100, then ask where your price should sit against it.

The second is a threshold exercise: after pitching the value, ask what price is acceptable, expensive and prohibitively expensive. Acceptable means they love product and price, expensive means a neutral reaction, and prohibitive means being laughed out of the room. Across many respondents you can spot cliffs, such as a jump in objections between $99 and $101, and he says Superhuman's Rahul Vohra used this to reach a $30 price.

Third are purchase probability questions on a one-to-five scale, where even a five means only 30 to 50% certainty and a four means 10 to 20%. Fourth are most-and-least questions, which ask people to pick the must-have and the don't-need from small feature sets, because people are good at extremes and poor at ranking the middle. The most advanced are trade-off exercises that simulate shopping scenarios to reveal people's decision rules and price elasticity.

Which method fits depends on stage: at idea stage simply ask whether they would pay and why, mid-stage use purchase-probability questions, and later use trade-offs and most-least for packaging precision. He points readers to chapter four of the book for details.

Early on, the conversation is a one-on-one between founder and customer; later it becomes cross-functional, with sales and product together. Ramanujam cites LinkedIn, where teams must secure a credit card or a budget commitment for pilots before productizing an innovation. Quantitative versions include controlled surveys and A/B tests.

He positions willingness-to-pay discussion as a step before user research: it tests whether people buy the idea, see the ROI and have the need, not how they will use the product. Asked how many people to talk to, he says "please talk to one", since most companies talk to none. Beyond that, B2C teams can get statistical significance from one to two thousand survey responses, while B2B companies with 20 to 30 accounts driving most revenue should talk to as many as possible.

Once you have a price, he suggests pausing every six months to consider changes and revisiting within 12 to 18 months. New plans or features are natural trigger points. For a founder starting on Monday, his first step is to accept there is a science here and read chapter four.

Ramanujam says about 60% of companies claim to have a segmentation strategy but perhaps 10% have a meaningful one. Most treat it as a demographic or persona exercise, which he illustrates by noting that a wealthy 70-year-old British man living in a castle could be either Prince Charles or Ozzy Osbourne, two people with very different tastes. Segments should be based on needs, value and willingness to pay.

The key is to productize to segments rather than position one product at many. Water is free from a fountain, $2 in a bottle, $2.50 with gas, and $5 from a hotel minibar; same water, different packaging for different needs. He has never found a vertical with homogeneous needs, and says "one size fits none".

Lenny asks how to tell if segmentation is right, and Ramanujam stresses the words "act differently": product, sales, marketing and finance should all treat segments differently, from what is built to the business case and the messaging. Founders often claim they have no time, but he says if you do the willingness-to-pay conversation first, you can pick the first segment, size it, and add products for others later.

Ramanujam points to Apple's range of iPhones from $299 to $1,499 and recalls choosing a cheaper model at the Apple store when the iPhone X launched because he did not want the extra features. Apple, he says, productizes to price points and willingness to pay rather than just pricing a single phone. Lenny jokes that he should have mentioned Liquid Death, the $8 canned water.

At Eventbrite, one product served everyone until the team defined segments and built three plans. The entry plan allows only a single ticket type, the middle plan unlimited types, and there is an enterprise tier, which makes sense because a local wine-club meetup only needs general admission. Uber's Black, X, Pool and Comfort tiers, including the quiet-preferred option he pays for when working in a ride, show the same logic.

His current focus with clients is dynamic segmentation, because the same person switches segments by situation: pizza on a Friday night, a different cuisine at a Tuesday office lunch, or a pool ride one day and a quiet ride the next. He says technology now lets companies adapt offers to these shifts, and describes it as the next frontier after static segmentation.

Ramanujam says there are only three pricing strategies: skimming, penetration and maximization. Apple's iPhone skims, launching high and lowering prices over time; Amazon penetrates, playing a high-volume, thin-margin game that needs a cost structure to match; and Microsoft is his example of maximization. The three most valuable companies have very different strategies, and the point is to execute whichever one you choose. He warns that founders who simply "price low to gain growth" without a supporting business model are falling for a fallacy.

Packaging and bundling are how you unlock segments, and he offers the leaders, fillers and killers framework. In a Happy Meal, the burger is the leader, the fries and Coke are fillers that customers accept for a little more, and coffee would be a killer because it spoils the bundle for most people. Coffee drinkers like him would pay for it as an add-on.

His rule of thumb is that if 10 to 20% of customers want something badly, it is an add-on, and if more than 50% want it, it is a leader. Lenny notes that the most-and-least ranking maps neatly onto this: must-haves are leaders, nice-to-haves are fillers and the don't-needs are killers, meaning features that would kill the deal if included.

Michelin created a tire that lasted 20% longer, but in a price-sensitive market a 20% premium would not stick, while not charging it would cannibalize sales. The company switched to charging by the mile driven, which truckers liked because they could pass the variable cost on to their own clients. Segment, before joining Twilio, replaced API-based pricing with monthly tracked users, a metric customers saw as fairer.

Lenny observes that both examples are usage-based and asks if that is the future. Ramanujam says companies follow whatever is in vogue, and the choice should depend on the business. Subscriptions suit predictable or highly variable usage, and ongoing value with episodic use, as with LifeLock. Usage pricing suits low-commitment onboarding, fairness demands, intermittent value like movie tickets, or underlying costs that scale, provided there is a clear metric.

Hybrids can work well, as HubSpot's fixed base with overage shows. He also describes a value matrix that charges less per user as both seats and departments grow, which builds an incentive for wall-to-wall adoption into the price. To test models, he suggests break-even questions in which several structures cost the same, and says people never choose the indifferent option, which reveals their preference.

Ramanujam defines features as what product teams build and benefits as what customers get from them. A telltale sign of feature-speak is being passionate about every detail of the product, since that means you are showcasing bells and whistles. Lack of traction can also mean customers do not understand what they are getting.

SmugMug's pricing page once made visitors scroll through pages of features before seeing a price. After rewriting it around benefits, such as the ability to sell photos online, which sits atop about 15 features, the company saw a double-digit revenue improvement with no product changes. He says the before-and-after is shown in the book.

For positive examples he cites Porsche's Taycan message, which admits it is not the most affordable electric car because the goal was a car that is first and foremost a Porsche. He also likes Shopify's plans, which emphasize benefits such as the number of inventory locations, and its tagline "Fair pricing, unfair advantage". Lenny's takeaway is to audit your own site for features versus benefits.

Behavioral pricing taps the irrational side of decision making, building on ideas from Dan Ariely's Predictably Irrational. Ramanujam describes a company with $49, $79 and $149 plans that gave too much away in the entry tier, so 60 to 70% of customers took it. After testing, it moved prices to $99 and $199, added a $299 decoy plan, and saw a 30%-plus increase in MRR and ARPU with no product changes.

He lists other tactics: the compromise effect, where most people avoid extremes; the pennies-a-day effect, such as presenting an annual plan as a monthly price; and the razor-blade model of a cheap base plus consumables. His more advanced one is the Panini effect, named for sticker albums, where showing a puzzle of products people have and have not completed raised attach rates by 40 to 50% in tests.

On thresholds, he says some recur, like $30 a month or 9.99 price points, but you still need to test, since add-ons and structures change them. This is not about deceiving customers, he stresses, but framing products to appeal to both sides of the brain.

For slow markets, Ramanujam offers three tactics. First, keep a de-featured cheaper alternative in your back pocket so customers who cannot afford your product stay instead of churning, because discounts tend to become the new price within six months. Second, use non-pricing actions such as extra product, longer contract terms or looser payment terms.

Third, a downturn is a good time to shift to usage-based or outcome-based pricing, since customers using less will welcome it and will stay on it when they use more. He gives the example of a hair-salon software company that moved from per seat to per haircut during the pandemic. He summarizes the three as changing the model, using non-pricing actions and keeping a cheaper alternative ready.

His next book, Unlocking Growth, picks up where Monetizing Innovation ends, covering acquisition, monetization and retention and the interactions among them. He says 90% of companies claiming a land-and-expand strategy are only landing because they gave the farm away. He also recommends Hermann Simon's Confessions of the Pricing Man, work by Kyle Poyar of OpenView and content from First Round.