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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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How to Design Pricing Around a North Star Metric - A Strategic Guide for SaaS Executives
A North Star Metric can focus an entire company. It gives product, marketing, customer success, and finance a shared view of the customer behavior that creates durable value. For a collaboration product, that behavior may be active teams completing work. For an observability platform, it may be monitored services delivering reliable performance. For a communications platform, it may be messages delivered or conversations completed.
The mistake begins when executives assume that the number on the operating dashboard should also become the number on the invoice. An internal metric can be highly useful for managing adoption while remaining too volatile, too hard to audit, or too distant from a buyer’s budget to support pricing. Monetizely’s position is firm: price around the North Star Metric, but do not bill the North Star Metric by default. Select one primary meter that rises when the North Star rises, sits closer to the customer’s budget, and can be forecast and verified without a dispute.
The North Star Metric answers a product question: “What customer behavior signals that our product is creating repeatable value?” The pricing metric answers a commercial question: “What will the customer pay more for as that value expands?” Those questions are related, but they are not identical.
Consider a workflow platform whose North Star Metric is “verified workflows completed each month.” Billing for every completed workflow may look elegant. Yet a customer may run the same workflow repeatedly while testing, rerunning failed processes, or training new staff. The buyer sees activity; the vendor sees revenue; neither side necessarily sees added value.
A direct translation from North Star to invoice usually fails for one of three reasons:
- The metric moves for reasons the buyer does not control. Weekly active users may fall during a holiday period even when the customer remains committed to the product.
- The metric is difficult to reconcile. A “successful resolution” may sound clear until a customer asks whether a reopened ticket counts as one resolution or two.
- The metric has no clear budget owner. A finance leader can approve spending on 1,000 protected endpoints or 500 users. “Engagement score” is much harder to defend in an annual plan.
The commercial task is to find the customer-controlled unit that enables the North Star behavior. That unit may be a seat, a managed asset, a message, a transaction, or a unit of compute. It should be close enough to value that expansion feels fair, but stable enough that a procurement team can approve a three-year commitment.
The pricing models of established B2B SaaS companies make that distinction visible.
The pattern is consistent: durable SaaS businesses do not charge for every internal product signal. They charge for a unit the buyer recognizes, can influence, and can connect to growing use.
Monetizely’s 5-Step Pricing Framework, developed in Monetizing Agentic AI, puts pricing decisions in the order executives need to make them. Goals and Segmentation establishes what the company is trying to accomplish and which buyers it serves. Packaging then defines the offers those buyers can actually purchase. Choosing the Right Pricing Metric identifies what expands commercially as value expands. Finding the Right Price Points sets the rate only after those choices are settled. Operationalizing Pricing makes the model work in product telemetry, billing, sales compensation, contracts, and customer reporting. The sequence matters because a price cannot repair a metric that does not fit the customer or the product.
Start with the business goal. A company entering a crowded category may favor rapid adoption, short sales cycles, and a simple pricing page. A company serving regulated enterprises may place more weight on committed revenue, predictable spend, controls, and a contract structure that procurement can approve. Those choices shape what a workable meter must do.
Segmentation comes next because a meter that works for a 20-person startup can fail at a 20,000-person enterprise. Smaller buyers often want low entry cost and simple self-service. Enterprise buyers usually need governance, procurement certainty, and visibility into expansion. A single package for both groups often produces either shelfware for small customers or aggressive discounting from large ones.
Pricing teams should therefore write a short statement before debating any rate:
“For our priority segment, the customer receives more value when ___ grows. The customer can forecast that growth by tracking ___. Our cost rises materially when ___ grows.”
If the three blanks produce three unrelated answers, the company is not ready to set a metric.
A primary meter should pass five tests. It should move with customer value, remain under reasonable customer control, support a credible budget forecast, produce a bill that both sides can audit, and avoid creating loss-making heavy users.
The following scoring table shows how that test works for a security SaaS company whose North Star Metric is “verified policy checks passed.” The company has four plausible ways to charge.
Protected assets win even though verified checks are closer to the North Star Metric. A customer can inventory assets before signing, identify the budget owner, and reconcile the count each month. Verified checks should remain a product-health measure and a proof point in value reviews, not necessarily the primary invoice line.
The same reasoning explains why outcome pricing should be used sparingly. A vendor may claim it sells “resolved tickets,” “recovered revenue,” or “incidents prevented.” Buyers will accept that model only when the outcome is objectively defined, measured by trusted data, and largely under the vendor’s control. Otherwise, revenue turns into a recurring debate about attribution.
A good metric makes the customer more successful as it grows. A great metric also makes the customer more willing to grow it.
Packages should preserve one expansion logic across segments
Packaging should change what customers receive, how much certainty they need, and how they buy. It should not force the company to invent a new billing logic for every segment. Monetizely’s view is that one primary meter should normally carry through the portfolio, while packages set included capacity, controls, service levels, and commitment terms around it.
For the security SaaS example, protected assets should remain the primary meter across segments. The offer changes, but the commercial logic stays intact.
The table points to a practical discipline: do not turn enterprise packaging into a pile of features that customers may never use. Build packages around a distinct buying need, then let the primary meter capture the scale of the customer’s use.
A fixed platform or access fee can have a legitimate role when the product delivers value simply by remaining available. Datadog’s commitment structures and Snowflake’s consumption controls both show that enterprise software can combine predictability with measured use. Yet the access fee must remain secondary when the customer’s expanding value comes from a measurable managed object or workload. Otherwise, the company risks returning to flat pricing just as customers are receiving more value.
A buyer’s three-year forecast is the practical test of rate design
Rate setting comes after segment, package, and metric choices because the number only makes sense in that context. Monetizely’s guidance is direct: price points must reflect the company’s goal, customer willingness to pay, competitive alternatives, internal usage data, and cost to serve.
Buyers do not evaluate a $4 monthly rate in isolation. They ask what they will actually pay over three years, what happens if their use doubles, and whether a budget overrun can be prevented. The commercial model must answer those questions without requiring a custom spreadsheet from a sales representative.
Consider a protected-asset model with a $10,000 annual access fee and a $4 monthly rate per protected asset.
Contract year Average protected assets Annual access fee Asset-based charge Annual spend Year 1 500 $10,000 $24,000 $34,000 Year 2 750 $10,000 $36,000 $46,000 Year 3 1,000 $10,000 $48,000 $58,000 Three-year total — $30,000 $108,000 $138,000 The meaning of the table is not that $4 is the correct rate. The point is that both parties can see the growth path. Finance can plan for it, sales can explain it, and the customer can decide whether the added value from 500 more protected assets justifies the added $24,000 in annual spend.
Rate cards should also avoid cliffs that create strange customer behavior. A customer should not have an incentive to delay onboarding its 501st asset because a threshold triggers a disproportionate jump in price. Graduated tiers, clear overages, and annual true-ups are often more effective than forcing customers into a larger package before they are ready.
Pricing becomes real only when the product, billing system, contract, and customer dashboard count the same thing. Monetizely estimates that operationalizing a pricing model can require three to five times the effort of designing it, and that a serious rollout commonly takes at least a quarter.
Executives should require evidence that the meter can survive normal customer scrutiny before taking it to market.
Operating requirement Evidence the company should require Commercial risk if missing Clear event definition A written definition of what counts, what does not count, and how retries or reversals are handled Billing disputes and sales exceptions Single source of truth Product telemetry reconciles to the billing ledger Finance and customer success report different usage totals Customer-facing visibility Customers can see current use, remaining included capacity, and projected charges Surprise invoices and renewal friction Contract treatment Order forms define measurement period, true-up timing, overages, and credits Revenue leakage or uncollectible charges Sales readiness Reps have a three-year spend example and a plain-language explanation of the meter Discounting replaces value-based selling Snowflake’s documented cost controls show why visibility matters in a variable model: customers can set budgets and resource monitors, receive notifications, and suspend warehouses at defined thresholds. SaaS executives need not copy Snowflake’s model, but they should copy the underlying discipline. Customers should never learn how a meter works from an invoice.
North Star alignment creates disciplined expansion rather than billing noise
The strongest pricing model does more than capture revenue. It gives product teams a clear incentive to help customers expand in ways that increase real value. It gives sales teams a credible story about what customers are buying. It gives finance a revenue model that can be forecast without pretending that all usage is equal.
Monetizely’s position is therefore not to price every product around seats, usage, or outcomes. The position is more demanding: choose the one customer-controlled unit that makes the North Star Metric grow, then make that unit the primary commercial engine. Keep product engagement metrics in the operating review. Put buyer-recognized value units on the invoice.
Write the causal chain from product action to customer value before reviewing any rate card. Identify the exact customer-controlled unit that enables the North Star Metric to rise.
Choose one primary meter for the next commercial cycle and reject secondary meters that cannot be explained in one sentence to procurement.
Run a three-year spend forecast for a low-growth, expected-growth, and high-growth customer before launch. Review the forecast with customer success, not only finance.
Treat the billing event definition as a product requirement. Do not approve a pricing change until customers can view the same usage record that generates their invoice.
Use the North Star Metric in quarterly business reviews as proof of value, even when it is not the billed unit. That separation protects pricing discipline while keeping the customer conversation focused on outcomes.
Footnotes
- https://www.amazon.com/Monetizing-Agentic-AI-Handbook-Transformation/dp/B0H7Z13VKJ/
- Atlassian, “Jira Pricing: Free, Standard, Premium, Enterprise,” accessed September 8, 2026. (atlassian.com)
- Datadog, “Pricing” and “Pricing Comparison,” accessed September 8, 2026. (docs.datadoghq.com)
- Twilio, “Messaging Pricing” and “SMS Pricing in the United States,” accessed September 8, 2026. (twilio.com)
- Snowflake, “Understanding Compute Cost,” “Overview of Warehouses,” and “Controlling Cost,” accessed September 8, 2026. (docs.snowflake.com)