Why pricing research matters for PMMs
Pricing is the most underleveraged lever in B2B SaaS. You can spend months perfecting your positioning, build beautiful campaigns, and nail your sales enablement. But if your pricing doesn't reflect the value buyers perceive, you'll leave revenue on the table or lose deals you should've won.
PMMs are uniquely positioned to own pricing research because they sit at the intersection of buyer insight, competitive intelligence, and product value. Finance can model the margins. Sales can report what they're hearing in deals. But PMM is the function that understands why buyers pay what they pay and what trade-offs they're willing to make.
The problem is that most PMMs don't have a repeatable process for pricing research. They inherit a price list when they join the company and treat it as fixed. Or they get pulled into a pricing conversation two weeks before launch and scramble to provide input without a structured approach.
Price isn't what your product costs. It's what your buyer believes your product is worth relative to the alternatives they're already considering.
This framework gives you a repeatable four-phase process: qualitative discovery, quantitative validation, competitive benchmarking, and packaging design. You don't need to run all four phases for every pricing decision. But you should understand what each phase tells you so you can pick the right tool for the job.
The four phases of pricing research
Each phase answers a different question. Used together, they give you a complete picture of how to price and package your product. Used individually, they still move you forward from wherever you're starting.
Phase 1: Qualitative willingness-to-pay discovery
This is where most PMMs should start. Before you survey hundreds of people or build pricing models, you need to understand how your buyers think about value and money in the context of the problem you solve.
Run 12 to 15 semi-structured interviews with a mix of current customers, prospects who evaluated but didn't buy, and prospects in active deals. You're not asking "what would you pay?" directly. That question produces unreliable answers because buyers anchor to whatever number they think you want to hear.
Instead, focus on understanding their value stack. Ask questions like: "Walk me through how you justified this purchase internally. What was the business case?" or "If this product disappeared tomorrow, what would you do instead and what would that cost you?" or "Which capabilities drive the most value for your team, and which ones are nice-to-haves?"
The goal is to understand the buyer's frame of reference. What are they comparing your price to? Is it the cost of the alternative tool? The cost of hiring someone to do the job manually? The revenue they'd lose without it? This frame determines what price feels reasonable to them.
Interview guide: five questions that surface willingness to pay
1. "What problem were you trying to solve when you started looking for a solution like this, and what was that problem costing you?"
2. "Walk me through how the purchase decision was made. Who was involved and what did they need to see?"
3. "Which capabilities matter most to your team's daily workflow? Which ones could you live without?"
4. "If you couldn't use this product, what would you do instead? What would that cost in time, money, or headcount?"
5. "When you think about the price you're paying, does it feel proportionate to the value you're getting? What would change your answer?"
After 12 to 15 interviews, you'll start hearing the same themes. You'll know which capabilities drive the most perceived value, what reference points buyers use when evaluating price, and where the current pricing feels misaligned. That's your foundation for everything that follows.
Phase 2: Quantitative price sensitivity analysis
Once you've got qualitative hypotheses, you can validate them at scale. The most accessible method for B2B SaaS PMMs is the Van Westendorp Price Sensitivity Meter. It's not perfect, but it's practical, fast to deploy, and produces actionable output.
Van Westendorp asks four questions about a clearly described product or tier. At what price would you consider it so cheap you'd question the quality? At what price would you consider it a bargain? At what price does it start to get expensive but you'd still consider it? At what price is it too expensive to consider?
Plot the cumulative response curves and you'll find four intersection points that define your acceptable price range. The range between "too cheap" and "too expensive" is your pricing corridor. The intersection of "bargain" and "getting expensive" gives you an optimal price point.
You'll need at least 100 responses per segment for the data to be meaningful. Survey your customer base, trial users, and engaged prospects. Be precise about what product or tier you're describing. Vague descriptions produce vague data.
If the stakes are high enough (a full pricing overhaul, a new product launch into an established market), consider conjoint analysis instead. Conjoint forces respondents to make trade-offs between features, brands, and price points, which more closely mirrors real buying behaviour. It's more expensive and complex to run, but the output is significantly richer.
Phase 3: Competitive pricing benchmarking
Your price doesn't exist in a vacuum. Buyers will compare it to alternatives, and you need to know what those comparisons look like. Competitive benchmarking isn't about matching competitor prices. It's about understanding the pricing context your buyer operates in.
Start with what's publicly available. Most B2B SaaS companies publish their pricing, and even those that don't will often reveal it in G2 reviews, analyst reports, or sales conversations your team has documented. Build a matrix that captures each competitor's pricing model (per seat, usage-based, flat rate), their tier structure, and what capabilities sit in each tier.
Pay special attention to how competitors package their product. Where do they draw the line between tiers? Which features do they gate behind enterprise plans? This tells you what the market considers premium versus table stakes. It also reveals gaps where you could differentiate through packaging rather than price.
Don't forget non-software alternatives. If your buyer's status quo is a spreadsheet maintained by a junior analyst, the competitive benchmark isn't another SaaS tool's price. It's the loaded cost of that analyst's time. Understanding the full range of alternatives gives you a more accurate picture of your pricing power.
Phase 4: Packaging and tier validation
Pricing and packaging are inseparable. You can have the right price point but the wrong package structure and still lose deals. This phase tests how you bundle capabilities into tiers and which packaging model fits your buyer's mental model.
The most common B2B SaaS packaging models are per-seat pricing, usage-based pricing, flat-rate pricing, and hybrid models that combine elements. Each has trade-offs. Per-seat is predictable and easy to understand, but it penalises adoption. Usage-based aligns cost with value, but creates budgeting uncertainty for buyers. Flat-rate is simple, but makes it hard to capture more value from larger customers.
To test packaging, create two to three tier concepts and put them in front of buyers. You can do this as part of your qualitative interviews or through a dedicated concept test. Show each buyer the tier options and ask: "Which of these would you choose for your team, and why? What would need to change for you to choose a higher tier? Is there anything in a tier you'd never use?"
The answers reveal whether your packaging maps to how buyers think about their needs. If buyers consistently say "I need features from two different tiers", your tier boundaries are wrong. If buyers can't articulate the difference between tiers, your packaging isn't clear enough.
Worked example: DataPulse (fictional)
Context: DataPulse is a B2B SaaS analytics platform for marketing teams. The PMM is researching pricing ahead of a packaging refresh.
Phase 1 finding: Interviews revealed that buyers value real-time dashboards and attribution modelling above all else. Data export and API access are expected but not differentiated. Buyers compare DataPulse's price to the cost of their previous BI tool plus the analyst headcount needed to maintain it.
Phase 2 finding: Van Westendorp with 140 responses placed the optimal price at $89 per seat per month, with an acceptable range of $59 to $129. The current price of $49 sits below the "too cheap" threshold for mid-market buyers.
Phase 3 finding: Two direct competitors price at $79 and $99 per seat. The incumbent BI tool most buyers are replacing costs $120 per seat but requires a dedicated analyst ($75,000 per year) to maintain.
Phase 4 finding: Buyers wanted attribution modelling in the mid-tier, not gated behind enterprise. Moving it down increased mid-tier preference from 31% to 58% in concept testing. The PMM recommended repricing at $89 per seat with attribution in the Growth tier.
How to run pricing research without derailing your roadmap
The biggest objection PMMs face when proposing pricing research is time. Leadership wants answers quickly, and a multi-phase research programme sounds like a six-month project. It doesn't have to be.
Start with what you already have. You've probably got win/loss data, customer interviews from other research, and sales call recordings that contain pricing signals. Before you run a single new interview, mine your existing data for patterns. You'll often find that 60 to 70 per cent of your qualitative insights are already sitting in tools you use daily.
Run the phases in parallel where you can. Competitive benchmarking can happen while you're scheduling interviews. Van Westendorp surveys can go out while you're analysing interview transcripts. The four phases are sequential in logic but don't have to be sequential in execution.
Scope to the decision you're actually making. If you're adjusting price by 10 to 15 per cent, you probably need Phase 1 and Phase 3 only. If you're launching a new tier or overhauling your packaging model, you'll want all four phases. Match the rigour of your research to the scale of the decision.
Time-box aggressively. Set a two-week sprint for the research, with a clear output: a pricing recommendation document that covers your findings, your recommendation, and the evidence behind it. Two weeks of focused work beats two months of sporadic effort.
Turning research into a pricing recommendation
Build the evidence pyramid. Start with your qualitative findings (the "why" behind buyer behaviour), layer on quantitative validation (the "what" in terms of price ranges and sensitivity), add competitive context (the "where" relative to the market), and finish with packaging validation (the "how" in terms of structure). Each layer should reinforce the others.
Define the rollout plan. Pricing changes affect existing customers, sales compensation, marketing collateral, and billing systems. Your recommendation should include a transition plan that addresses grandfathering, communication timing, and how sales should handle the conversation. A great price with a bad rollout will create more problems than it solves.
Your messaging framework will also need updating. When prices change, the value narrative around those prices needs to change with it. Make sure your pricing recommendation includes guidance on how to talk about the new pricing, not just what the new numbers are.
Frequently asked questions
How many interviews do I need for reliable pricing research?
For qualitative willingness-to-pay interviews, 12 to 15 conversations per buyer segment will surface the major patterns. For Van Westendorp or conjoint analysis, you'll want at least 100 responses per segment to get statistically meaningful results. Start with qualitative interviews to shape your hypotheses, then validate with quantitative methods if the stakes are high enough to justify the investment.
Should product marketing own pricing research or does it belong to finance?
Product marketing should own the research process because pricing is fundamentally a positioning decision, not just a financial one. Finance owns the margin analysis and revenue modelling, but PMM owns the buyer insight that determines what customers value and what they'll pay for it. The best outcomes happen when PMM runs the research and collaborates with finance on the commercial model.
How often should we revisit our pricing research?
Run a full pricing research cycle whenever you launch a new product tier, enter a new market segment, or notice meaningful shifts in win/loss data tied to price. Outside of those triggers, a lightweight review every six to twelve months is usually sufficient. Revisit sooner if a well-funded competitor enters your space with aggressive pricing or if your product's value proposition has changed materially.
What is the Van Westendorp price sensitivity method?
Van Westendorp is a survey-based technique that asks four questions: at what price would you consider the product too cheap (suspect quality), a bargain, getting expensive, and too expensive to consider? Plotting the response curves gives you an acceptable price range and an optimal price point. It works well for B2B SaaS when you survey actual buyers who understand the problem your product solves.
How do I research pricing without tipping off competitors?
Use your existing customer and prospect relationships for interviews rather than public surveys. Frame the conversation around value and willingness to pay rather than specific price points you're considering. For competitive benchmarking, rely on published pricing pages, analyst reports, and intelligence gathered through win/loss interviews rather than mystery shopping, which can backfire if discovered.