How to Price a Product

Pricing is the highest-leverage decision most founders touch least. A 10% price increase, all else equal, routes directly to the bottom line and compounds forever. A 10% acquisition improvement saves you the CAC but leaves margin unchanged. Yet pricing conversations tend to happen once at launch and then never again.

This guide walks the three standard pricing approaches, their honest trade-offs, and the minimum evidence each requires. The framework follows the Nagle/Müller standard treatment^[1], grounded in 2024 SaaS data where the empirical evidence has moved on^[3].

1. Pick a pricing model that fits the evidence

Three decision points narrow the choice quickly:

• Do I have direct-variable-cost visibility? If yes, cost-plus gives you a useful floor. If no (SaaS with mostly fixed costs), cost-plus is close to useless.
• Are there three or more direct competitors I can benchmark? If yes, competitive pricing gives you a ceiling signal. If no, you are probably in a nascent category and benchmarks will mislead.
• Can I measure the quantified outcome my product produces for the buyer? If yes, value-based pricing is both defensible and profitable. If no, it degenerates into storytelling.

Most products should use at least two of the three — cost-plus as a floor, competitive as a sanity check, value-based as the aspiration. Using only one is the common mistake.

2. Cost-plus: the floor, not the answer

Cost-plus pricing is Total Unit Cost × (1 + markup). For a product with $30 variable cost and a target 60% gross margin, price = $30 / (1 − 0.60) = $75.

This gets you a price. It does not get you the right price. Cost-plus ignores what the buyer will pay, which in most markets exceeds what the seller calculated from the cost stack. Nagle calls cost-plus "the most common error in pricing decision making"^[1] precisely because it treats cost as the anchor when the buyer's willingness to pay should be.

Use cost-plus to answer one question: what is the minimum price below which I am operating at a loss? Never set the selling price there. Add the willingness-to-pay signal and competitive benchmark on top.

3. Competitive: benchmark the ceiling

Competitive pricing means setting price relative to direct substitutes. The method is simple: identify 3–5 genuinely comparable products, tabulate their public pricing, and decide whether you are premium, parity, or discount. Each position requires supporting evidence.

Two failure modes:

• Picking the wrong comparison set. If your product is meaningfully differentiated, pricing against the nearest competitor strips out the premium your differentiation should command.
• Public pricing is not actual pricing. Especially in B2B, the published list price and the average realised price diverge by 15–30% once discounts, negotiated terms, and enterprise concessions are included^[3]. Factor this in when benchmarking.

Competitive pricing as the primary model works for commoditised categories. For differentiated products, it should constrain your pricing but not determine it.

4. Value-based: what it's worth to the buyer

Value-based pricing anchors on the economic value created for the buyer, minus a fair share retained. If your product saves a buyer $100k annually, pricing it at $20k captures 20% of the created value — a reasonable split in most B2B markets.

The challenge is measurement. You need (a) a quantified outcome model, (b) evidence that your product causes the outcome, and (c) a way to communicate the value to buyers. Without all three, value-based pricing becomes storytelling.

The Van Westendorp Price Sensitivity Meter is the cheapest way to get willingness-to-pay data from a small sample^[2]. Four questions to 30–100 prospects:

1. At what price would this be so expensive you would not consider buying?
2. At what price would this be expensive but you might still consider it?
3. At what price would this be a bargain?
4. At what price would this be so cheap you would question the quality?

Plot the four curves; the intersection of "too expensive" and "bargain" is the Optimal Price Point, and the intersection of "too cheap" and "expensive" is the Indifference Price Point. The acceptable price range lies between them. Sample size of 100+ is recommended for stable estimates; 30 gets you a directional signal.

5. Test, price, revisit

For SaaS, packaging matters as much as price. OpenView's 2024 benchmarks show that products using a value metric (seats, API calls, revenue processed) for pricing grew expansion revenue at 1.5–2x the rate of flat-fee products^[3]. The packaging decision is: what metric does the customer scale on, and how do I tie price to that metric.

Three packaging principles that hold up:

• Three tiers, not five. Too many tiers introduce decision paralysis. Three — typically Starter, Growth, Enterprise — map to buyer segments cleanly.
• Anchor high, not low. Show the premium tier first visually. Anchoring effects are empirically robust^[5]; the perceived value of the middle tier rises when it is visually compared to a higher one.
• One clear upgrade trigger per tier. Each tier should have one feature or limit the buyer crosses that forces the next tier. Vague value differences cost expansion revenue.

Revisit pricing annually at minimum. US CPI has grown 2–4% in most recent years^[4]; holding prices flat means a real-terms price cut. Grandfathering existing customers is common and defensible; raising new-customer pricing is not a breach of trust.

The worst pricing decision is the one that never gets revisited. Roughly, most bootstrapped founders could raise prices 20–30% today with minimal churn impact and do not, because changing pricing feels riskier than leaving it alone. The data says the opposite^[3].

6. Price by segment when the data supports it

Different buyer segments often have different willingness-to-pay. Segment-based pricing captures more value if segmentation can be operationalised:

• Volume discounts. Standard in B2B. Larger customers pay lower unit prices in exchange for higher total commitment. Structure tiers by seat count, usage bands, or revenue bands.
• Geographic pricing. Common in international software — emerging markets pay 30–60% less for parity offerings. Works when markets can be separated (e.g., separate purchase channels); breaks when arbitrage is easy.
• Industry-specific pricing. Regulated industries (healthcare, finance, government) often pay premiums for compliance features. Unregulated segments get base pricing.
• Academic / non-profit pricing. Common discount tier, usually 30–70% below commercial. Builds goodwill and early-career exposure to the product.

Segment-based pricing risks: arbitrage (customers buy through the cheaper channel), transparency concerns (buyers discovering peers pay less), and administrative overhead (validating segment eligibility). Run the cost-benefit before introducing multi-tier segment pricing.

7. Discounts and promotional discipline

Discounting is widely over-used. Four rules that help:

• Discounts should cost less than they save. A 20% discount that accelerates a deal close by 30 days is usually positive-value. A 20% discount that closes a deal that would have closed anyway is pure margin erosion.
• Time-bound discounts out-perform permanent discounts. "25% off if you close by end of quarter" creates urgency and ends. Permanent discounts become the baseline price.
• Multi-year prepayment trades cash for margin. Annual prepayment at 10–15% discount is usually worth it because the cash is operationally valuable. Three-year prepayment at 25% discount is sometimes not, depending on your cost of capital.
• Authority to discount is a cost. Every rep with broad discount authority discounts more than reps with narrow authority. Structure approval levels to match the margin at stake — small discounts at rep level, larger at manager, material at executive level.

In the typical case, sustained discounting of 20%+ off list price is a signal that list price is aspirational rather than realistic. Raise the list price less, or discount less — mixing both is the pattern that produces the worst price realisation.

8. Numeric worked example — Van Westendorp on a micro-SaaS

A bootstrapped SaaS with 300 active trial users runs the four Van Westendorp questions through in-app surveys with an 18% response rate (54 respondents). The raw curves intersect at roughly:

Question                              Median  P25    P75
──────────────────────────────────────────────────────────
Too expensive (won't consider)        $89     $65    $120
Expensive but still consider          $59     $42     $75
Bargain                               $29     $22     $39
Too cheap (quality doubt)             $15     $10     $19

Acceptable price range    (too-cheap × too-expensive crossover)  $19–$89
Indifference Price Point  (expensive × bargain)                  ≈ $42
Optimal Price Point       (too-expensive × bargain)              ≈ $48

Current list price: $29. The analysis suggests an OPP around $48 — a 65% price increase is inside the "bargain-to-expensive" acceptable band for the majority of respondents. Phase the change: new customers at $39 immediately (+35%), $49 at the 90-day mark if churn on trial-to-paid holds; grandfather existing customers for 12 months at current rate. In practice, bootstrapped founders running this exercise typically discover their price sits in the P25–P50 "bargain" band^[2] — confirming the 20–50% undercharging pattern Nagle documents^[1].

9. Failure modes worth naming

• Reading Van Westendorp with fewer than 30 responses. The four curves are noisy below a meaningful sample. With 12 responses, the crossovers wander by $20+ on re-runs; with 100 responses, they stabilise within ±$5. Don't make a repricing decision off a 12-person survey.
• Pricing off competitor list, ignoring discount reality. Enterprise SaaS discounts often run 15–30% off list^[3]. Pricing at competitor list means your realised price is 15–30% above competitor realised price — an unintentional premium position that gets flagged in every buyer comparison.
• Grandfather period too generous. Three-year grandfathering on a 50% price increase is effectively a permanent two-cohort pricing system with operational complexity for years. Cap grandfathering at 12 months unless the customer relationship genuinely warrants longer.

As of 2026-Q2, OpenView 2024 shows roughly 65% of surveyed SaaS companies raised list prices in the preceding 12 months, with a median increase of 7–12%^[3]. Companies that held nominal prices flat through 2022–2024 CPI have taken a meaningful real-terms pay cut; catching up requires a deliberate price event, not a gradual creep.