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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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In the world of SaaS, pricing isn’t just about picking numbers – it’s a fundamental growth lever that can make or break your business. In fact, experts have shown that even a tiny 1% increase in price can drive an 11% boost in profits, a far greater impact than equal improvements in customer acquisition or retention. This outsized effect means monetization strategy deserves as much attention as your product and growth strategy. Yet many SaaS founders and product leaders default to simplistic pricing models without fully examining their fit. It’s like driving a sports car but never shifting out of first gear, you’re leaving money on the table.
One common default is the classic “Good-Better-Best” (GBB) tiered pricing model. On the surface, GBB seems like a no-brainer: offer three packages (basic, mid, premium) to capture different willingness-to-pay, and let customers self-select. It’s simple, familiar, and many successful companies use it. But when applied without careful thought, GBB can quietly undermine your growth: “killing” your company’s potential softly, over time, through missed revenue and mis-served customers. Before you slap three tiers on your pricing page and call it a day, it’s worth exploring where this approach can go wrong and how to get it right.
The Temptation of the Good-Better-Best Model
It’s easy to see why the Good-Better-Best (GBB) model is appealing. The approach offers 2–3 tiered packages, e.g., Basic, Pro, Enterprise, each priced to match the willingness-to-pay of a broad customer segment. It’s simple, familiar, and efficient for products that serve homogeneous user bases, such as SMBs with similar needs and budgets.
When used in the right context, GBB can:
- Maximize revenue by offering more value to power users (“Best”) while accommodating price-sensitive users (“Good”)
- Simplify decision-making with a clean, predictable structure
- Prioritize scale and speed of sale over hyper-personalization
This model works especially well in markets where:
- Customer needs are relatively uniform
- Willingness-to-pay doesn’t vary dramatically
- The product doesn’t require industry- or use-case-specific packaging
But here’s the catch: not all products or markets are that simple.
Many SaaS companies serve diverse segments or use cases where needs and willingness-to-pay vary significantly. In these cases, GBB can misfire:
- It assumes a neat “small–medium–large” progression of value, which often doesn’t reflect reality
- Customers in different verticals, industries, or company sizes may not fit cleanly into one of three predefined tiers
- You risk creating friction by forcing misaligned buyers into ill-fitting packages—or leaving them out entirely
Worse, a rigid GBB structure can limit your revenue ceiling by:
- Oversimplifying offers, which fails to reflect the real diversity of your customer base
- Creating shelfware, where customers overpay for features they don’t need
- Leaving out mid-market or hybrid customers who fall between tiers
It’s no coincidence that less than half of SaaS companies publish pricing pages at all. And among those that do, many with GBB structures still end up customizing deals behind the scenes, especially for enterprise buyers.
So, even though Good-Better-Best is a helpful framework, it is not a one-size-fits-all solution. When blindly applied to complex markets, it can stall growth, alienate customers, and leave money on the table.
In the next section, we’ll look at a real-world example of a GBB misstep, and the costly lesson it delivered.
When Good-Better-Best Goes Wrong: A SaaS Cautionary Tale
A few years ago, Customer Success software provider Gainsight found itself in a pricing predicament that perfectly exemplifies the hidden dangers of a misapplied GBB model. Gainsight primarily served mid-market companies with its platform – this was its ideal customer profile. Yet, ironically, this core segment was where its pricing was most “broken”. What happened?
For a long time, Gainsight offered a three-tier “good-better-best” pricing lineup to mid-market customers, with packages (let’s say) around $1k, $2k, and $3k per month. In theory, these tiers were meant to provide options for smaller vs. larger mid-market clients. But in reality, it failed on multiple fronts:
- Everyone landed on the middle tier. The value difference between the "Better" and "Best" tiers wasn’t strong enough to justify upsell. Most deals defaulted to the mid-tier, and the top-tier was rarely chosen, certainly not at full price.
- The "Best" tier didn’t monetize power users. Even when customers showed interest in the top tier, sales reps had to discount it heavily, often bringing the final price down to mid-tier levels. This nullified the revenue upside of a premium plan.
- Over-bundling led to shelfware. Higher tiers unlocked more features, but mid-market customers had diverse needs. Many bought bundles full of unused features, value that went unutilized. Upsell potential was lost because customers already had everything bundled upfront.
- Pressure to downgrade. Since customers weren’t using all the features they paid for, many began to question the ROI and downgraded to lower tiers. Instead of driving expansion, the tiering model drove churn and discounts.
- Enterprise pricing lacked structure. Larger clients were handled via one-off, custom quotes. While flexible, this led to inconsistencies, with similar deployments priced very differently, hurting fairness, predictability, and revenue planning.
- Smaller customers were priced out. Gainsight’s lowest tier was still too expensive for many small firms. The company ignored the low-end of the market, leaving potential revenue on the table.
Meanwhile, Gainsight’s approach to larger enterprise deals was to completely custom-price each one (essentially one-off quotes for each enterprise client). That gave the sales team flexibility at the high end, but it introduced inconsistency, some enterprise customers were paying vastly different prices for similar deployments, and the lack of a structured offering made it hard to predict revenue or ensure fairness. Smaller customers, on the other hand, were essentially ignored by the packaging; the lowest tier was still too expensive for many small firms, meaning Gainsight had unintentionally priced itself out of the lower end of its potential market.
In summary, Gainsight’s misaligned Good-Better-Best strategy was slowly stifling its growth in the very market it should have owned. The company was leaving money on the table (no effective premium upsell for higher-paying customers), frustrating mid-sized clients with all-or-nothing bundles, and missing out on smaller customers altogether. Gainsight’s story is a cautionary tale: a GBB model, applied by default without tailoring to a product’s specific market dynamics, can do more harm than good.
What Was Missing? Context and Segmentation
So, what went wrong and how did Gainsight fix it? The root issue was treating all mid-market customers as one monolithic segment that could be served with a fixed ladder of packages. In reality, different customers valued different aspects of the Gainsight platform. Gainsight belatedly realized that even within a target segment (mid-market), there was significant heterogeneity in needs. The “one-size-fits-all” tiered packages weren’t fitting anyone particularly well.
To correct the course, Johnny Cheng, Head of Pricing & Packaging at Gainsight, took a more nuanced approach. He shifted the company toward a modular packaging strategy, essentially breaking the product into components or “Lego pieces” that could be recombined to suit each client’s needs. Instead of forcing every customer down one preset path (good/better/best), the sales team could now mix and match modules to create custom bundles with transparent pricing for each module. This is known as a packaged-plus-à-la-carte hybrid model, and it gave Gainsight much more flexibility to align price with value on a per-customer basis.
Crucially, this new approach was grounded in customer segmentation and use cases. The team literally listed out every feature and capability of the product (hundreds of line items) and grouped them into logical modules based on different use cases. Some clients might need Module A + B, others B + C, etc., depending on what outcomes they were after. By pricing each module, Gainsight could charge for the specific value a customer needed, rather than a bloated bundle. This modular strategy acknowledged that for their product, customers didn’t progress along a single axis of “small to big”; they had varied paths and priorities. It traded the simplicity of GBB for a more segmented approach that ultimately drove better monetization.
The Gainsight case highlights a few key mistakes to avoid with Good-Better-Best, as well as principles to embrace:
- Don’t ignore true segmentation. You must understand the distinct segments or personas in your customer base before locking in a tiered model. If Gainsight had recognized that mid-market customers fell into multiple profiles with different core needs, they might have avoided bundling everything into one linear set of tiers. Segmentation is the first step in Monetizely’s pricing framework for a reason, pricing should map to customer profiles and their specific value drivers.
- Avoid one-size-fits-all bundles that cap your upside. If your “Best” tier isn’t delivering proportionally higher value (or if customers who choose it end up paying roughly the same as the mid tier due to discounts), then your tier design is broken. Each step up should unlock meaningful additional value that the target segment truly wants. If instead you overload tiers with features you think are valuable but the customer doesn’t need, you’ll either force them to overpay (and they’ll resist or churn) or you’ll have to discount, defeating the purpose. Gainsight’s experience shows the danger of over-bundling: once a customer has “everything,” you have nowhere to go but down.
- Don’t neglect smaller or larger segments in your packaging strategy. A GBB page often targets a sweet spot (e.g. mid-market), but you may also have enterprise customers who need custom deals or small customers who need a lighter offering. Plan for this. It might mean having a fourth “Enterprise – contact us” tier, or a hidden freemium/entry plan, or using add-ons. The key is to design packages as part of an overall segmentation strategy, not in isolation. Gainsight’s initial three tiers left it blind to an entire segment (smaller customers) and ill-equipped for enterprises – an imbalance that hurt growth.
Now, let’s generalize these lessons and tie them into a clear framework for pricing done right. We’ll walk through the four pillars of Monetizely’s pricing framework: Segmentation, Packaging, Metrics, and Operationalization, and show how applying them can steer you away from Good-Better-Best bad practices.
Segmentation: One Size Rarely Fits All
The first and most critical step is knowing your customer segments and their differing needs. Before deciding how many tiers or what goes into each, ask: Who are my distinct customer groups, and what does each value most? Your segments might be based on company size, industry, use case, user persona, or any combination of these. The goal is to cluster customers who have similar problems and willingness-to-pay, so you can design offerings tailored to each cluster.
Why Segmentation Matters
Skipping segmentation often leads to mispricing. For example:
- Gainsight once lumped all "mid-market" clients into a single segment—only to discover that a fintech customer and a healthcare customer had drastically different workflows and feature needs.
- Many SaaS products serve multiple personas, such as engineers, product managers, and marketers. If you flatten them into one tiered plan, you risk overloading some users or under-serving others.
A great example of segmentation in action is Mixpanel’s pricing overhaul. Mixpanel, a product analytics SaaS, realized that its customers ranged from early-stage startups to large enterprises, and within those were different functional teams (engineering, data, marketing) using the product differently.
In their pricing redesign, Mixpanel’s team first identified the big customer segments and use cases they were serving: for instance, startups with lean teams versus enterprises with strict governance needs; or data engineers looking for pipeline integrations versus marketers focused on messaging campaigns. By understanding these distinctions, Mixpanel could see that a single linear pricing model would never fit all. What a 10-person startup values in analytics is not the same as what a Fortune 500 analytics team values. This insight drove Mixpanel to segment its offering (more on how in a moment).
The takeaway is clear: do your homework on customer segmentation. Talk to users, look at usage patterns, and discern clusters of needs. Your pricing (whether GBB or otherwise) should start with the customer, not with an arbitrary “good/better/best” template. If your segments truly are homogenous (e.g. a pure SMB self-serve tool), GBB might work out-of-the-box. But if you have diverse segments, you may need more creativity, perhaps multiple tier structures, tailored messaging for each segment, or modular add-ons. Simply put, good-better-best works best when you have a “large ‘n’” of customers with relatively homogenous needs and a similar willingness-to-pay. Outside of that scenario, it’s time to consider alternatives or hybrids.
Packaging: Designing Tiers (or Modules) That Align with Value
Once you've clearly defined your customer segments, the next step is packaging, structuring your product into offerings that map to how different customers derive value.
At the heart of good packaging is alignment: the way you bundle features, usage, and access should reflect real differences in customer needs and willingness to pay.
When Tiered Models Work (Good-Better-Best)
If your segments are fairly uniform and value scales with volume, like usage, seats, or projects, a classic Good-Better-Best (GBB) model can be highly effective.
- Each tier expands on the previous one with higher usage limits or broader feature access.
- This is common in developer tools, where pricing scales with API calls or active projects.
- Example: A startup may only need the entry-level tier, while a larger company pays for more capacity in the higher tiers.
The key is ensuring these tiers reflect actual customer usage patterns, not just arbitrary upsells.
When to Go Modular or Hybrid
If your segments have qualitatively different needs, a modular or hybrid packaging strategy may be more appropriate.
- Modular packaging lets customers buy a core platform and add optional modules based on specific needs.
- This approach gives flexibility, especially in markets where different user types value different capabilities.
Examples:
- Gainsight adopted a Lego-style modular design, allowing customers to build packages based on their use case.
- Mixpanel shifted from a one-size-fits-all pricing (based on event volume) to a core Analytics platform + optional modules:
- Data Pipelines for heavy data ingestion
- Messaging for A/B testing and push notifications
- Groups for complex enterprise tracking
This model let startups stick with just core analytics (keeping costs low) while enabling enterprises to add high-value modules, paying more for what they actually use.
Effectively, Mixpanel reinvented “Good-Better-Best” into a build-your-own-bundle approach. Customers still got “good” fits upfront, and could graduate to “better” setups by adding what they needed over time.
Avoid Cramming: Focus on Value Themes
Even if you choose a tiered model, poor design can backfire. One common pitfall: stuffing higher tiers with every feature, just to justify the price.
- This can lead to “shelfware” unused features that frustrate buyers and erode trust.
- Instead, group features around value themes or personas:
- A Standard plan for SMBs with core functionality.
- A Professional plan for power users or mid-market teams with advanced needs.
- An Enterprise package (or sales-led bundle) with compliance, custom integrations, or premium support.
If only a subset of customers needs a feature, like SOC2 reports or API rate limiting, don’t bury it in every tier. Offer it as an add-on or custom bundle.
There's No “Right Number” of Tiers
Ajit Ghuman puts it well: Good-Better-Best is not one-size-fits-all.
- Some companies thrive with just two tiers (“Standard” and “Premium”).
- Others succeed with four or five tiers or modules.
The point isn’t to hit a number, it’s to match packaging to your market reality.
If you’re using public tiers, make sure:
- Each tier serves a distinct customer profile.
- You can clearly justify the price and feature mix.
- Your team can explain why it exists and who it’s for.
If not, you likely need to rethink the structure.
Bottom Line: Design your packaging to fit your customers, not the other way around. Whether you choose tiers, modules, or a hybrid model:
- Align with real customer needs and value delivery.
- Avoid overwhelming users with bloated tiers.
- Offer room to expand with relevant upsells and add-ons.
A well-structured packaging strategy doesn’t just improve monetization, it simplifies the buying experience and signals product maturity to investors and customers alike.
Metrics: Align Price to Customer Value (and Ability to Pay)
An often-overlooked aspect of SaaS pricing is the pricing metric, the unit by which you charge. This could be per user, per 1,000 events, per GB of data, per customer managed, or another usage-based measure. Choosing the right metric is just as critical as setting the right price.
A strong pricing metric has three qualities:
- It grows with the customer’s usage or success.
- It’s easy to understand and predict.
- It aligns with how customers perceive and extract value from your product.
The Metric Trap Behind Good-Better-Best
Too often, teams rely on tiered packaging (“Good-Better-Best”) and assume the pricing problem is solved. But if these tiers are built on a flawed or misaligned metric, customers will still struggle. Poor metric alignment quietly erodes value perception, customers can’t predict bills or connect price to outcomes. As a result, they hesitate to adopt, expand, or fully engage.
Case Study: Mixpanel’s Metric Misstep
Mixpanel’s story provides a clear example. Their original pricing was events-based; clients were charged based on the number of events (user actions) tracked in their product analytics. This made sense to Mixpanel internally (more events meant more load on their servers, i.e. higher cost to serve), but it didn’t work well for customers, as:
- New users couldn’t predict how many events they'd trigger.
- Unexpected spikes in activity caused surprise overages.
- Customers avoided full adoption to “save budget,” ironically reducing the product’s value.
In short, the pricing metric was at odds with customer success. Mixpanel recognized this friction and as part of their pricing revamp, they changed the metric (alongside packaging).
Mixpanel revamped its model:
- Introduced a “Mixpanel People” plan priced by the number of known users (easier to count and predict).
- Offered add-ons for heavy data movers (event overages, pipelines).
This shift made Mixpanel’s value metric more intuitive and user-aligned. When defining your pricing, ask: What usage metric best captures the value a customer gets? And also: What metric scales with a customer’s ability to pay (as they grow or use more) without becoming unpredictable or punitive?
For many SaaS, per-seat (per user) is popular because it ties to company size and is straightforward. But per-seat doesn’t fit all products (consider a data analytics platform used by a small data team to process massive amounts of data, per-seat would undercharge relative to value).
Alternatives might be per consumption unit (API calls, transactions, data volume), per feature/module (charging more for access to certain functionality), or tiered thresholds of a key value metric (e.g. pricing bands for number of customer records, or for revenue processed through your system).
The trap to avoid is picking a metric that is either too far from the customer’s perceived value or too hard for them to predict/control.
Case Insight: Gainsight’s Enterprise Confusion
Gainsight’s case involved a feature-based tiering, which is slightly different (gating features by tier rather than usage quantity).
Gainsight’s challenge wasn’t the usage metric per se, but a lack of consistency:
- In some enterprise deals, pricing worked out to $5/user, in others $1,000/user.
- This variance confused both customers and internal teams.
- A better metric (e.g., based on number of accounts managed or CS team size) could have aligned pricing more consistently to value delivered.
Segment-Specific Metric Options
Don’t assume one metric fits all. Use segmentation to inform metric design:
- High-volume, low-seat segments may prefer usage-based pricing.
- Low-volume, high-seat segments may prefer per-user or per-team pricing.
- Some companies offer hybrid models, letting customers choose or blend (e.g. Mixpanel’s new plans combine per-user and usage add-ons).
Takeaway: The right pricing metric grows with value, not just with cost, and customers see it as fair and tied to outcomes. It makes tiered packaging intuitive (“up to X users or Y projects”) rather than arbitrary. When metric and packaging are both aligned to customer success, pricing becomes a growth enabler, not a friction point.
Operationalization: Rolling Out Pricing Changes Smoothly
Even the best pricing strategy can fall flat without effective execution. Pricing isn’t a “set-and-forget” task, it cuts across product, sales, marketing, billing, and customer success. Operationalization is about rolling out pricing changes in-market with clarity, coordination, and care. It means communicating updates, enabling teams to sell the new model, and managing customer transitions, without causing churn or confusion.
Here are five best practices to operationalize pricing changes effectively:
1. Test and Iterate in Low-Risk Ways
Don’t rip the Band-Aid off for everyone at once. If your current pricing or tiers aren’t working, experiment with smaller segments before a broad rollout.
- Pilot with a subset of new customers to gather feedback and validate the new model.
- Example: Gainsight could have tested its modular pricing with a handful of prospects before going live company-wide.
- Focus on confirming that:
- Customers understand and perceive value in the new structure.
- Sales teams can explain and sell it confidently.
2. Equip and Incentivize Your Sales Team
Complex pricing models like modular packages or add-ons, require more than just internal buy-in. Your sales team must be ready to navigate and sell them smoothly.
- Invest in tools and training: sales playbooks, pricing calculators, and deal configurators.
- Build clear schemas: Gainsight, for example, designed a pricing “menu” of modules, giving reps flexibility and control without improvising numbers.
- Align sales incentives with strategy:
- If your model relies on expansion revenue, make sure reps are rewarded for upsells, not just initial ACV.
3. Manage Legacy Customers With Care
Transitioning existing customers off legacy plans is one of the hardest parts of pricing change, and a common place where companies stumble.
- Avoid blunt-force migrations that trigger churn or backlash.
- Instead, consider:
- Grandfathering current customers on old plans for a limited time.
- Special upgrade bundles that offer real value in the new system.
- Letting legacy customers buy a la carte add-ons without jumping to the top-tier plan.
- E.g., if a new add-on only appears in the “Elite” tier, allow existing customers to purchase it separately.
The goal: make legacy customers feel upgraded, not squeezed.
4. Guard Against Self-Cannibalization
New pricing creates risk: what if your new “Better” tier is cheaper, or perceived as better, than what current customers already pay for “Good”?
- Avoid unintentional downgrades by:
- Clearly differentiating plans, not just on features but on positioning.
- Framing lower-priced plans as serving different use cases or segments.
- Adjusting feature mix and naming to discourage apples-to-apples comparisons.
The aim is to grow revenue through innovation, not create an unintended race to the bottom.
5. Monitor and Refine Continuously
Operationalizing pricing isn’t a one-time event, it’s a living process.
- Track adoption data: Which tiers are customers clustering in? Are upgrade rates healthy?
- Watch sales behavior: Are reps relying on custom discounts? That might signal mispriced tiers or misunderstood value.
- Collect feedback: Combine data (conversion, churn, upsell rates) with qualitative insights (sales notes, customer interviews) to refine your approach.
Even with a strong launch, pricing must evolve alongside your product and market.
Final Thought: Great pricing isn’t just about theory, it’s about execution. A simple model can succeed if rolled out thoughtfully, while even the most elegant strategy can fail if poorly implemented. The true lever lies in the combination of strategic design and disciplined operationalization.
Conclusion: Turning Pricing Missteps into Growth Opportunities
Pricing is too fundamental to be an afterthought. Copy-paste tactics, like slapping on a generic Good-Better-Best page, may look standard, but they often mask deeper misalignments that quietly stifle growth. The good news? Most pricing issues are fixable, and fixing them often delivers faster results than shipping new features or ramping up marketing.
If you’re a SaaS founder or product leader, now is the time to ask:
- Are your pricing tiers aligned to clear customer segments and real needs?
- Do customers experience meaningful value as they move up-market, or do your tiers blur together?
- Are you offering modular add-ons where a single pricing ladder falls short?
- Is your pricing metric helping customers adopt, or quietly turning them away?
These questions reveal whether your monetization strategy is fueling your expansion or quietly slowing it down.
The power of pricing lies in working smarter, monetizing what you already have, but with sharper focus and stronger alignment. A disciplined approach to segmentation, packaging, pricing metrics, and execution can expose and patch the leaks in your growth engine.
When done right, pricing does more than boost revenue, it aligns your product with the right customers, builds trust, and scales value.
So don’t let outdated or misaligned pricing slowly choke your momentum. Treat pricing like a product: something to design, test, and optimize with the same rigor you apply to UX or code.
Because in SaaS, monetization isn’t just a financial detail, it’s a growth system. Make it count.
FAQs: Common SaaS Pricing Challenges and Strategies
1. When should we use a Good-Better-Best model versus a modular pricing approach?
Use Good-Better-Best (GBB) when:
- You serve a large, relatively uniform market (e.g. SMBs with similar needs).
- You want to simplify buying decisions and accelerate deal cycles.
- You can bundle features into 2–3 clear tiers tied to customer value.
Use a modular approach when:
- Your customers vary widely by industry, size, or use case.
- Customization is key to winning deals (e.g. large or enterprise clients).
- You want to maximize account-level revenue through flexible packaging.
Most SaaS companies blend both: GBB for simplicity, with add-ons or bespoke options for larger or more complex customers.
2. How do we manage legacy customers when we roll out a pricing change?
Pricing changes can be sensitive. Balance fairness, clarity, and operational ease:
- Communicate early and transparently: Explain why pricing is changing and what value customers will receive.
- Grandfather selectively: You can honor existing plans for a period (e.g. 12 months) or only for early adopters to reward loyalty.
- Offer migration incentives: Provide discounts, bonus features, or support upgrades to encourage switching to new plans.
- Ensure systems readiness: Billing, support, and finance tools must handle both old and new pricing if run in parallel.
Successful transitions are gradual and transparent. Respect existing relationships while steadily guiding customers to your new model.
3. How can we enable our sales team to sell effectively when pricing isn’t one-size-fits-all?
Non-standard pricing requires structured sales enablement. Focus on:
- Tools: Use CPQ software or pricing calculators to generate accurate, flexible quotes.
- Playbooks: Create clear guides for mapping customer profiles to packages and knowing where flexibility is allowed.
- Guardrails: Define discount bands, rules for customization, and approval workflows to avoid unnecessary escalations.
- Value communication: Train reps to connect features to business outcomes. Provide ROI calculators or TCO models to justify pricing.
- Simplification: Don’t overload reps or customers with choices. Highlight recommended offers per segment.
- Ongoing training: Treat pricing changes like internal product launches, update CRM systems, run workshops, and circulate cheat-sheets.
When sales is aligned and equipped, pricing becomes a confident lever, not a blocker.
4. How do we evaluate if our SaaS pricing is actually working?
You should continuously measure the performance of your pricing strategy. Start by defining what “working” means for your business – typically it’s driving healthy growth and retention without leaving money on the table. There are a few signals to watch:
- Conversion rates: Track how prospects move through your funnel under the current pricing. For self-serve models, what percentage of free trials or freemium users convert to paid? For sales-led, how often do deals progress once pricing is revealed? If a lot of potential customers balk at the pricing page or during negotiation, that’s a red flag.
- Deal economics: Look at the average selling price or ARPU for each segment or tier. Are you seeing the distribution you expected (e.g. a good mix of customers on each tier)? If 90% of customers only buy the cheapest tier, perhaps the higher tiers aren’t justified or clearly differentiated. Also monitor discounting – if every deal requires a heavy discount to close, your list prices might be misaligned with market value.
- Retention and expansion: Arguably the biggest test of pricing is what happens after the initial sale. Check your net retention rate (NRR), churn percentages, and expansion revenue. If customers are succeeding and finding ongoing value, a well-designed pricing model should enable upgrades and upsells (in a Good-Better-Best model, think customers growing into higher tiers). On the flip side, high churn or downgrade rates could indicate customers aren’t seeing enough value for the price.
- Customer and sales feedback: Qualitative input is valuable alongside the metrics. Solicit feedback from customers, do they find the pricing reasonable relative to the value? Any features they wish were in a different tier? Also ask your sales and success teams what objections or hurdles they hear regarding pricing. Frequent complaints like “too expensive” or “too complicated” are smoke that may indicate a real fire in your model.
Importantly, bake these evaluations into a regular review cadence. Remember, pricing is a powerful growth lever – you want to constantly ensure it’s calibrated correctly, based on data. If the data shows suboptimal results, don’t be afraid to iterate on your packaging or price levels.
5. What internal systems need to change when we evolve our pricing?
Pricing changes impact multiple internal systems. Ensure alignment across:
- Product instrumentation: Make sure the product is tracking any new usage or entitlement limits if your pricing model changed (e.g. a new usage-based metric). The usage data needs to be reliable for billing and analysis.
- Billing and ERP systems: Update your billing platform to handle the new price logic, whether that’s tier limits, metered usage, or proration for upgrades/downgrades. The finance systems (ERP, revenue recognition tools) should align with the new pricing terms to accurately book revenue. Integrating the new pricing model into billing may take significant effort but is non-negotiable for smooth operations.
- CRM and CPQ: Configure your CRM (or CPQ software) with the new pricing SKUs, discounts, and quote structures. Sales reps should be able to pull up the latest pricing options when creating opportunities or quotes. If you introduced new tiers or packages, add them into quoting tools with correct pricing rules. A basic spreadsheet might suffice for early-stage, but as pricing complexity grows, a proper CPQ system becomes vital.
- Contracts and legal: Revise order forms, MSA/terms, and sales contracts to reflect the new pricing structure (e.g. new plan names, billing terms, overage policies). This avoids legal confusion and makes sure what Sales sells can be enforced in writing.
- Reporting and KPIs: Adapt your analytics dashboards to the new metrics. For example, if you switch to usage-based pricing, track usage per account internally so you can forecast revenue and identify outlier customers.
Before launch, run simulations (e.g., upgrade from Tier A to Tier B) to ensure systems handle transitions smoothly. Coordinate early across engineering, ops, finance, and legal to avoid costly errors post-rollout.
6. How do we align pricing and packaging with our customer segmentation?
Start with clear segmentation, by company size, industry, or use case:
- SMBs typically need simple, self-serve tiers with fast ROI and per-user pricing.
- Enterprises require advanced features, integrations, custom terms, and often prefer flat-rate or bespoke pricing.
Align pricing to the perceived value in each segment:
- Offer core functionality for lower tiers and full suite plus services for top-end customers.
- Match pricing models to buying behavior (e.g., monthly vs. annual, usage vs. seat).
Segment-driven pricing ensures:
- You don’t under-monetize high-value customers.
- Price-sensitive users still have a clear path to adoption.
Done right, segmentation enhances both growth and satisfaction.
7. How often should we revisit or change our SaaS pricing strategy?
Pricing isn’t a “set and forget” decision, it requires regular tuning as your product and market evolve. Top SaaS companies often form pricing committees and revisit strategy quarterly, adjusting pricing every 6 months. That cadence may seem aggressive, but it reflects the reality: pricing is a living system.
There’s no universal rule, but you should watch for signs it’s time to revisit:
- It’s been 18–24 months since your last update.
- Your product has materially improved or expanded.
- The market has shifted, new competitors, customer expectations, or macroeconomic pressures.
- A new module or feature launch warrants re-bundling or re-pricing.
- Your top-tier customers consistently max out their plan, suggesting demand for a premium tier.
Even without clear triggers, a yearly pricing audit is healthy. Review metrics to assess if pricing is helping or holding back growth (see FAQ #4).
When making changes, go methodically:
- Pilot new pricing in one region or segment.
- Align cross-functional teams (sales, ops, finance).
- Use small, frequent experiments (e.g., tweaking discount policies) to learn without disrupting.
Avoid knee-jerk changes that confuse customers. Instead, treat pricing as a strategic growth lever that evolves with your business. Regular check-ins and data-driven iterations ensure your monetization keeps pace, not falls behind.