Last pod shot of the year and we're going back to December 2023 (time flies!).

Naomi Ionita is a partner at Menlo Ventures focusing on early-stage SaaS from seed to Series B. Before venture, she pioneered product-led growth and monetisation over a decade ago—before PLG was even a term. At Evernote (2011-2017), she scaled the product from 10M to 100M users and built the growth team from scratch. At Invoice2go, she led product, data, growth engineering, design, and research. She's also an early Reforge contributor who helped create their programmes.

Speaking on Lenny's Podcast, Naomi dropped a jaw-dropping stat from OpenView research: roughly half of companies that changed pricing saw at least a 25% increase in ARR. Meanwhile, Profit Well's research across 500+ SaaS companies found that a 1% improvement in monetisation had 4x the bottom-line impact of a 1% improvement in acquisition.

💡 Top tip — Don't read this linearly if you're in crisis mode. Jump to "The Van Westendorp Method" if you need pricing research tactics today, or "10x the Price in One Meeting" if you need courage to charge more.

Naomi Ionita, "How to Price Your Product" | Lenny's Podcast

Why this matters now: Yes this is 2 years old, but these fundamentals haven't changed - and most companies still aren't doing them. If you've never run pricing research or haven't revisited your pricing in 12+ months, this is your playbook.

Naomi identifies three patterns she sees founders repeat across hundreds of companies—mistakes that compound over time.

"The beginning of a startup journey is all about creating something of value," Naomi explains. "But the other side is being properly compensated for that value as a business."

She understands the vulnerability—you're new, you want adoption. But companies wait way too long to shift from building a product to building a business.

The real signal of product-market fit? People opening their wallets.

When you delay monetisation, you leave money on the table, inadvertently cheapen your product, miss critical feedback loops about willingness to pay, and create backlash when you eventually start charging.

Her advice for B2B: Start charging immediately. Define where the paywall sits and package a paid version early—even if you offer freemium.

This isn't just setting prices too low—it's failing to offer different plans for different segments.

The framework: match price to value. Pick the right value metric (seats, API calls, storage, usage) that creates a natural escalator: as people use it more, you get paid more.

The single-tier trap: One premium tier leaves money on the table at both ends—low-value users find you too expensive, high-value users would happily pay 5x more.

"I see companies labour over designs and features. They build this perfect product. And then pricing is plucked out of thin air and they don't revisit it."

At Evernote, "It was many, many years before we overhauled the pricing."

Her mantra: "Think about pricing just like your roadmap. Every six to 12 months, treat new launches as an opportunity to revisit your monetisation strategy."

Evernote's pricing research uncovered an uncomfortable truth.

The setup: Evernote charged $45/year for premium from day one, generating tens of millions. But something felt off.

The bombshell: When Naomi's team surveyed why users converted, the top answer was: "I just feel guilty. I use it so much, I feel obligated to pay."

"Take that in for a second," Naomi says. "If guilt is one of the main reasons people are paying you, your free version is too good and you're leaving money on the table."

Research revealed two polar opposite segments:

Segment 1: Brand-new users—Compared Evernote to Apple Notes (free). Couldn't justify $45. Never converted.

Segment 2: Power users—Cross-device, OCR, Web Clipper, true "second brain." Floored they only paid $45/year. Said they got hundreds of dollars of value.

The problem: One $45 tier meant losing Segment 1 entirely (too expensive) and massively undercharging Segment 2 (10x value, 1x price).

The solution: Bifurcated plans matching different personas' value and willingness to pay.

This pattern is everywhere—single-tier pricing leaves money on the table at both ends.

Invoice2go achieved a seemingly impossible result: doubled their upgrade rate from starter to pro while increasing the pro price by 30%.

How do you get twice as many people to upgrade whilst paying more?

The insight: Day 1 vs Day 100 features

Day 1 premium features:

Day 100 features:

The mistake: Putting all premium features in one tier forces users to parse advanced functionality they don't need yet. This cognitive load kills conversion.

Invoice2go's approach: Rebalanced so Day 1 features lived in accessible starter plan, Day 100 features in higher-priced pro. Result: lower barrier to first upgrade (2x conversion) + higher ceiling for power users (30% price increase) = 2.6x revenue impact.

Naomi's principle: "Think about the journey for a user and how they're going to continue to increase value with your product over time, and map your pricing and packaging against that journey."

Naomi walks through a complete pricing research process.

For PLG: Product, growth, data science. For enterprise: Add sales, finance, rev ops.

This committee owns pricing over time—not a one-off project.

A. Feature Prioritisation—Understand which features actually drive conversion.

Two tactics:

B. Willingness to Pay (Van Westendorp's Price Sensitivity Meter)

Bundle the "must-have" and "nice-to-have" features, then ask four questions:

"By plotting those four curves, you start to get a sense of how to inform your pricing," Naomi explains.

This method finds the range where pricing should sit—not a single number, but a band that surfaces psychological price points where users' perceptions shift.

Larry, founder of Envoy (visitor registration tool), was in a meeting with a big hospitality company. The conversation was going well. When pricing came up, feeling good vibes, he decided to 10x his typical price on the spot.

The response: "OK, sure. Sounds good." Zero hesitation.

What Larry learned: He was wildly underpriced and probably could have pushed even further.

Naomi's advice: "Continue to ask for more, to understand where the upper bound might be. It's OK to lose 20-30% of deals due to price so you can get a sense for where the limit is."

The principle: Most companies underprice, especially in enterprise contexts where perceived value can be orders of magnitude higher than SMB.

The caveat: Don't literally 10x every prospect—systematically test 2x, 3x, 5x with different segments. Losing 20-30% of deals to price means you're in the right zone.

Invoice2go invested in experimentation infrastructure: metering, SKU management, consumption tracking, in-product nudges. They tested different value metrics, quota limits, price points, and promotions.

Result: "Huge revenue gains by being able to iterate in a way that was more streamlined."

Landmine #1: Inconsistent experiences—Bring consistent pricing across your pricing page, in-product experience, app stores, and lifecycle emails. Mismatched prices break trust and contaminate experiments.

Landmine #2: Short-term thinking—"You really have to think about the long-term nature of pricing experimentation. Knowing if you succeeded often requires understanding implications on churn." Testing a year-one discount? Wait until year two to declare victory.

Landmine #3: Optimising one metric in isolation—You're balancing acquisition, retention, ARPU, and LTV. Optimising one can tank another. Need holistic view.

Invoice2go's geo-segmentation trick: Test in Canada or Australia before the US to reduce blast radius.

OpenView: ~50% of companies changing pricing saw 25%+ ARR increase.

ProfitWell (500+ SaaS companies): 1% monetisation improvement had 4x the bottom-line impact of 1% acquisition improvement.

Naomi's seen 10x revenue lifts, though it's rarely just price—it's holistic rebalancing of pricing, packaging, and positioning mapped to the user journey.

Should you optimise for growth or revenue? Naomi's answer: It depends on whether you can bridge from single-player to multiplayer to enterprise.

Strategy: Give up long-tail individual revenue to drive insane community adoption.

Why it worked: Design is inherently collaborative. Multiplayer was the product—over half of Figma users weren't designers once embedded in enterprises. Compounded growth loops: acquisition (organic referrals), retention (shared workflows = accountability), monetisation (usage scales revenue).

Figma's bet: Free individual usage → wall-to-wall enterprise adoption → massive contracts.

Evernote was "philosophically antisocial"—your personal "second brain," not collaborative.

"You can't retrofit collaboration," Naomi observes. "You have to be collaboration-first."

This capped growth potential. Employees used it wall-to-wall, but companies never signed high-ACV contracts.

Optimise for growth if: inherently multiplayer, clear path individual → team → enterprise, willing to trade year-one revenue for year-three ACV.

Optimise for revenue if: single-player by nature, enterprise buyers with predictable budgets, sales-led GTM, no virality.

Naomi's nuanced take: "It's not that you should optimise for revenue on day one. It's a journey. But I see companies take too long."

Naomi's current thesis at Menlo Ventures: the "Modern Growth Stack"—tools that help PLG and revenue teams operate more efficiently.

The setup: Like the Modern Data Stack (cloud-native data tools), the Modern Growth Stack is "the evolution of what you do with the data—workflows that drive the business forward."

1. Data—Breaking down siloed data through reverse ETL (Hightouch, Census). Business teams self-serve without engineers.

2. Workflow—Purpose-built software for cross-functional growth work teams historically built in-house.

3. Impact—Cost reduction (automation) + revenue generation (engagement, monetisation). "I'm compelled by companies that drive hard ROI both ways."

Product-Led Sales: Pocus, Endgame—Harness usage data to find upgradeable accounts. "It's really free money when you shine a light on an account nobody was paying attention to."

Experimentation: EPPO—Ties experiments to warehouse metrics (subscriptions, revenue, margins)—"board-level metrics." Amplitude—Behavioural analysis + experimentation for companies without warehouses.

Billing: Metronome, Orb—Usage-based billing. Orb marries billing with data infrastructure to inform pricing iteration. Incumbents (Chargebee, Zuora) serve seat-based; new entrants handle usage-based.

Generative AI: Images, text, code, audio, video for marketing and sales. "If AI tells you what's going to be more performant, that's hard ROI—save time and improve performance."

Naomi's closing message: Treat pricing like your product roadmap.

"Every six to 12 months, there's probably something meaningful you're launching. Treat that as an opportunity to revisit your monetisation strategy."

The three deadly mistakes:

The research process:

The impact potential:

And finally: If guilt is your #1 conversion driver, your free version is too good. If prospects accept your price with zero hesitation, you're leaving money on the table.

Pricing isn't a one-time decision—it's a continuous optimisation lever that compounds over time.

🔗 Links Referenced:

That’s a wrap.

As always, the journey doesn't end here!

Please share and let us know what you liked or want changing! 🚀👋

Alastair 🍽️.