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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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Introduction: The Unrecognized Crisis in Software
We're standing at the edge of a fundamental transformation in the software industry, one that most executives, investors, and even seasoned operators haven't fully grasped yet. While we've all been focused on the AI revolution and its promise of unprecedented productivity gains, we've missed a crucial paradox: the very innovations that are supposed to propel software forward are simultaneously undermining the economic foundations that made the SaaS model so attractive in the first place.
This isn't just another market cycle or temporary adjustment. We're witnessing what can only be described as a regime change, a complete restructuring of how software companies create, deliver, and capture value. The implications are profound, affecting everything from unit economics to go-to-market strategies, from company valuations to the very definition of what constitutes a software company.
Part I: The Perfect Storm - Understanding the Triple Threat to Software Economics
The Hidden Deflation Bomb in Software
Here's a shocking truth that should keep every software executive awake at night: while the cost of everything around us seems to be spiraling upward, from your morning coffee to your children's college tuition, software is experiencing one of the most dramatic deflationary spirals in economic history.
Let's put this in stark perspective. According to meticulously updated data from the Bureau of Labor Statistics, software that commanded $100 in value in 2015 is worth approximately $60 today in real terms. This isn't a temporary dip or a market correction, it's a sustained, accelerating trend that mirrors the deflation we see in consumer electronics and toys, but with far more serious implications for business models built on the assumption of pricing power.
But wait, it gets more intense. Just when we thought we understood the deflationary pressures on software, artificial intelligence has arrived like a wrecking ball to the pricing structure.
The latest data from Mary Meeker's AI trend report reveals something unprecedented: models like GPT-3.5 and GPT-4 have seen their costs plummet by an astounding 99.7% in just a few years. This rate of cost reduction doesn't just beat Moore's Law, it obliterates it.
The Vibe Shift in Software Development
The implications of this deflation bomb are already manifesting in ways that would have seemed like science fiction just two years ago. We're now in the era of "weekend coding", where applications that once required months of development by entire teams can be prototyped and launched by a single developer over a weekend. This isn't hyperbole; it's happening right now across thousands of garages, dorm rooms, and coffee shops worldwide.
Consider the numbers for a moment: there are already over 10,000 MarTech software solutions and another 10,000 in sales tech. With the barrier to entry dropping to nearly zero, we're about to see these numbers explode exponentially. Every business problem that once justified a $50,000 annual software contract can now be solved with a weekend project and a few dollars worth of AI compute time.
The Macro-Economic Squeeze
While software deflation would be challenging enough on its own, it's happening against a backdrop of broader economic pressures that compound the problem:
The Interest Rate Reality Check: After more than a decade of essentially free money, where capital was so cheap that profitability was almost seen as a lack of ambition, we've entered a new era. Interest rates have climbed dramatically, and while there's constant speculation about when they'll come down, the structural factors suggest we're not returning to the ZIRP (Zero Interest Rate Policy) era anytime soon.
The Valuation Compression: Public market valuations for software companies have compressed dramatically. Companies that once traded at 20-30x revenue multiples are now lucky to get 5-7x. This isn't just a paper loss for founders and investors, it fundamentally changes the math on everything from employee compensation (those options aren't worth what they used to be) to M&A strategies to the viability of growth-at-all-costs approaches.
The Free Cash Flow Imperative: In response to these pressures, we've seen a dramatic shift in focus. Free cash flow margins, once an afterthought in the growth-obsessed SaaS world, have become the north star metric. Companies are cutting costs, reducing headcount, and scrutinizing every expense in ways that would have been unthinkable during the go-go years.
The Debt Time Bomb
Lurking beneath these immediate pressures is an even more ominous threat, the massive debt overhang that permeates every level of the economy:
- Federal Reserve debt: $37 trillion and climbing
- Private debt in America: A staggering $150 trillion
- Housing market valuation: Even adjusted for inflation, we're now beyond 2008 bubble territory
This debt mountain isn't just an abstract macroeconomic concern. It directly impacts software companies through:
- Customer budgets: Your enterprise clients are dealing with their own debt servicing costs
- Funding availability: VCs and PE firms face higher costs of capital
- Exit opportunities: The IPO and M&A markets remain largely frozen
- Currency stability: International customers face exchange rate pressures
The Human Cost: 40% on the Bench
Perhaps the most telling indicator of this regime change comes from the human side of the equation. At a recent Chief Revenue Officer summit, insider reports revealed a shocking statistic: approximately 40% of senior sales and revenue leaders are effectively "on the bench." Many are calling themselves "fractional consultants" or "advisors" while they search for their next full-time role, but the reality is stark, there simply aren't enough seats for everyone who was playing the game two years ago.
This isn't just about individual careers; it's about the loss of institutional knowledge, the disruption of customer relationships, and the challenge of building and maintaining high-performing go-to-market teams in an environment where the playbook is being rewritten in real-time.
Part II: The Regime Change - From SaaS 1.0 to SaaS 2.0
Understanding the Old World: The Golden Age of SaaS (2010-2022)
To appreciate the magnitude of the current transformation, we need to first understand what we're leaving behind. The "SaaS 1.0" era was characterized by a set of assumptions that seemed immutable:
The Unit Economics Paradise:
- Gross Margins of 80-95%+: Once you built the software, the cost of serving each additional customer was essentially zero. I personally witnessed this at Twilio's contact center product line, where we consistently achieved 95%+ gross margins. The beauty of this model was its scalability, whether you served 100 customers or 10,000, your cost base remained largely fixed.
- The Land and Expand Dream: Customer acquisition costs could be high because lifetime values were essentially infinite. Once a customer was integrated into your software, switching costs created natural moats that protected your revenue base.
- Predictable Revenue Growth: The subscription model created beautiful, predictable revenue streams that investors loved. ARR (Annual Recurring Revenue) became the lingua franca of valuation discussions.
The Growth Environment:
- Cheap Capital Everywhere: With interest rates near zero, the cost of capital was essentially free. This meant companies could raise massive rounds at eye-watering valuations with the promise of eventual profitability.
- Multiple Expansion: Software companies routinely traded at 10-20x revenue multiples, with the highest flyers reaching 30-40x during peak euphoria.
- Blitzscaling as Strategy: The winner-take-all narrative justified burning billions to capture market share, with the assumption that profitability would come later.
The Operating Model:
- R&D as the Core: Engineering and product teams were the heroes, with sales and marketing playing supporting roles
- Services as a Necessary Evil: Professional services, implementation, and customer success were seen as unfortunate requirements, not profit centers
- The Platform Play: Everyone wanted to be a platform, creating ecosystems that would lock in customers and partners alike
The New World Order: SaaS 2.0 (2023 and Beyond)
The regime we're entering is fundamentally different, and the changes go far deeper than just "growth to profitability" pivot that many assume:
The New Unit Economics Reality:
- Gross Margins of 30-50%: Especially for AI-first companies, the cost structure has completely changed. Every query, every computation, every generated response costs real money. OpenAI's admission that they lose money on their $200/month ChatGPT plan should be a wake-up call for anyone building AI-powered products.
- Infrastructure Costs That Scale: Unlike traditional SaaS where infrastructure costs were minimal, AI companies face costs that scale linearly (or worse) with usage. GPU compute, data storage, model training, and inference all add up to create a cost structure more reminiscent of manufacturing than software.
- Data Acquisition as a Major Expense: Training and maintaining competitive AI models requires massive amounts of data, which isn't free. Whether you're purchasing datasets, paying for labeling, or investing in synthetic data generation, data has become a significant line item.
The New Growth Reality:
- Expensive Capital: With interest rates normalized, the cost of capital matters again. Every dollar burned needs justification, and the path to profitability needs to be clear and credible.
- Compressed Multiples: Valuation multiples have compressed to levels not seen since the early 2000s. A 5x revenue multiple is now considered good, not disappointing.
- Efficient Growth: The new mantra is "efficient growth", growing at 50% year-over-year while burning cash is no longer celebrated. The Rule of 40 (growth rate + profit margin ≥ 40%) has become the Rule of 50 or even 60 for many investors.
The Hybrid Operating Model:
- Software + Services: Pure software plays are increasingly rare. The future belongs to companies that can seamlessly blend software capabilities with high-value services that customers can't or won't do themselves.
- Outcome-Based Value Delivery: Customers no longer buy features; they buy outcomes. This shift requires companies to take more responsibility for customer success, often through managed services or success-based pricing models.
- The Transformation Partner: Instead of selling tools, successful companies position themselves as transformation partners, helping customers navigate their own digital evolution.
Part III: Why Pricing Has Become Your Most Critical Strategic Lever
The Power of Pricing: Evidence from the Field
In this new regime, pricing isn't just about revenue optimization, it's about survival. Research from OpenView Partners provides compelling evidence of pricing's impact:
But these numbers only tell part of the story. Let me share what we're seeing in the trenches:
Case Study 1: The SaaS Transformation A late-stage SaaS company we worked with discovered something counterintuitive: while their software entry point was around $30,000 in ARR, their real money was being made on $300,000-$500,000 service deals. These weren't traditional implementation services, they were ongoing managed security services where the company provided specialized analysts that their enterprise clients couldn't (or wouldn't) hire internally.
The key insight? In a world where security threats evolve daily and expertise is scarce, customers valued the outcome (being secure) far more than the tool (security software). By restructuring their pricing to lead with services and position software as an enabler, they increased average deal sizes by 3x while actually improving customer satisfaction.
Case Study 2: The Agent Revolution Another client, an early-stage company building AI agent software, learned quickly that pure software wasn't enough. Their customers didn't just want agents; they wanted transformation. The company had to build a team of "forward deployed engineers", essentially consultants who could help customers redesign their workflows around AI agents.
The pricing implication? The software became almost a loss leader at $50,000 per year, while transformation services commanded $500,000+ engagements. The software created stickiness; the services created revenue.
Case Study 3: The Hidden Willingness to Pay A seed-stage cybersecurity startup discovered through customer research that a subset of their market had 4-5x higher willingness to pay for specific capabilities they hadn't even considered building. These weren't complex features, they were narrow, specific solutions to acute problems that these customers faced.
In the old regime, the company might have ignored these niches as "too small" or "not scalable enough." In the new regime, these high-willingness-to-pay segments became their path to profitability.
Pricing as a System, Not a Number
One of the biggest misconceptions about pricing is that it's primarily about finding the right number, $99 vs. $199 vs. $299. This fundamental misunderstanding leads companies to make catastrophic errors that ripple through their entire business.
Pricing is actually a complex system that affects:
Cash Flow Architecture:
- Timing of Revenue Recognition: When do you book the revenue? When do you collect the cash?
- Variability Management: How predictable is your revenue stream? Can you forecast accurately?
- Working Capital Requirements: Do you need to finance customer acquisition? How long is your cash conversion cycle?
Organizational Alignment:
- Sales Compensation: How do you pay reps on usage-based deals? What about multi-year contracts with ramp-ups?
- Customer Success Metrics: What does "success" mean when pricing is outcome-based?
- Product Development Priorities: Which features justify premium pricing? Which should be table stakes?
Financial Reporting and Valuation:
- Investor Communications: How do you explain your model to investors accustomed to simple SaaS metrics?
- Valuation Methodology: Usage-based companies are valued differently than subscription companies
- Audit and Compliance: Complex pricing models create complex accounting requirements
Let me give you a concrete example of how this plays out. A company I advised decided to switch from subscription to usage-based pricing because "that's what Snowflake does." They didn't consider:
- Their sales team had no idea how to forecast usage-based deals
- Their commission structure incentivized large upfront commitments, not ongoing usage
- Their financial systems couldn't handle real-time usage tracking and billing
- Their investors valued them on ARR, which became meaningless with pure usage pricing
The result? Chaos. Sales productivity plummeted, customer complaints skyrocketed, and the company had to essentially stop selling for three months while they rebuilt their entire go-to-market motion.
Part IV: The Five-Step Framework for Strategic Pricing in the New Regime
Step 1: Context Setting and Market Segmentation - The Foundation of Everything
Before you touch a single price point or packaging decision, you must understand three critical dimensions:
Your Economic Reality: Are you operating in a high-growth regime where you can still prioritize land-grab over margins? Or are you in the new reality where every deal needs to contribute to profitability? This isn't about what you wish were true, it's about honest assessment of your situation.
Questions to ask:
- What is our current burn rate and runway?
- What are our investors' expectations for growth vs. profitability?
- How commoditized is our market becoming?
- What is our true differentiation, and how long will it last?
Step 2: Packaging Architecture
Packaging is where pricing strategy becomes tangible. It's not just about good-better-best; it's about creating a choice architecture that guides customers to the right solution while maximizing value capture.
The Spectrum of Packaging Strategies:
High Velocity Packaging (The Figma Model):
When Figma designed their packaging, they didn't just create three arbitrary tiers. They deeply understood their three core segments:
- Free Users: Individual designers exploring and learning
- Professional Designers: People whose livelihood depends on design tools
- Organizations: Teams that need collaboration, governance, and enterprise features
Each package was crafted to meet the specific needs of these segments, not just stuffed with random features. The free tier wasn't just a trial, it was a fully functional product for individual use. The professional tier included the features that working designers actually needed, not artificial limitations. The organization tier focused on control, security, and collaboration at scale.
Key principles for high-velocity packaging:
- Clear Differentiation: Each tier should map to a distinct use case or customer segment
- Natural Upgrade Paths: Customers should hit clear walls that make upgrading obvious
- Self-Service Friendly: Customers should be able to understand and choose without talking to sales
- Minimal Customization: What you see is what you get, no special deals
Low Velocity, High Touch Packaging (The ServiceNow Model):
ServiceNow takes the opposite approach, with good reason. Their deals range from $100,000 to $10 million+, and no two customers have identical needs. Their packaging strategy includes:
- Core Platform Modules: IT Service Management, IT Operations Management, HR Service Delivery, etc.
- AI and Automation Add-Ons: Priced as a percentage of base license value to scale with deal size
- Professional Services: Retainers, implementation packages, and ongoing consulting
- Training and Certification: Education services that create stickiness and expand wallet share
- Custom Integrations: Bespoke connectors and workflows for enterprise systems
This isn't inefficiency, it's sophistication. When your average deal size is seven figures, the ROI on customization is massive.
Key principles for high-touch packaging:
- Modular Architecture: Build with Lego blocks that can be combined in countless ways
- Value-Based Pricing: Every component should have clear ROI justification
- Services Integration: Don't treat services as an afterthought, they're part of the core value
- Expansion Readiness: Always have something else to sell to existing customers
The Hidden Complexity: Separate Price Books
Here's something most companies don't realize until it's too late: you need different packaging strategies for new vs. existing customers.
New Business Price Book:
- Simplified options to accelerate initial sales
- Aggressive entry pricing to win deals
- Focus on land, with clear paths to expand
- Standardized terms and minimal negotiation
Existing Business Price Book:
- Granular add-ons and upgrades
- Loyalty pricing and retention incentives
- Usage-based expansion options
- Flexibility to prevent churn
One client we worked with discovered they were losing 30% of expansion revenue opportunity because they forced existing customers into new business packages that didn't fit their evolved needs. By creating a separate expansion price book with more granular options, they increased net revenue retention from 95% to 115% in one year.
Step 3: Pricing Metric Selection - The Alignment Engine
Your pricing metric is perhaps the most consequential decision you'll make. It determines not just how you charge, but how customers perceive value, how sales sells, and how your business scales.
The Spectrum of Pricing Metrics:
Fixed Metrics (The Predictability Play):
- Per User/Seat: Classic SaaS, works when value scales with users
- Per Entity: Customers, properties, assets, whatever core object drives value
- Flat Fee: Simplest but hardest to scale
- Platform Fee: Base charge regardless of usage
Advantages:
- Predictable revenue for you and costs for customers
- Simple to understand and budget for
- Easier sales compensation and forecasting
- Traditional SaaS valuation multiples apply
Disadvantages:
- Doesn't align with AI-reduced headcounts
- Can create "shelfware" where paid seats go unused
- Limits expansion within accounts
- May not align with customer value perception
Variable Metrics (The Alignment Play):
- Pure Usage: Pay only for what you use
- Transaction-Based: Per API call, per document, per query
- Outcome-Based: Per lead generated, per issue resolved
- Hybrid Models: Base fee plus usage
Advantages:
- Perfect alignment with customer value
- Scales naturally with customer growth
- No shelfware or perceived waste
- Lower barrier to initial adoption
Disadvantages:
- Unpredictable revenue streams
- Complex billing and metering requirements
- Difficult sales forecasting and compensation
- Customer bill shock risk
- Different (often lower) valuation multiples
The Three-Part Tariff Solution:
Most successful AI companies have converged on what's essentially the cell phone plan model:
Here's how it works:
- Commitment Tier: Customer prepays for a bundle of usage at a discount
- Included Usage: The bundle includes X units of usage per month
- Overage Pricing: Additional usage is charged at a premium rate
- Tier Jumping: At certain usage levels, it becomes economical to upgrade tiers
This model brilliantly balances multiple needs:
- Predictability: Both parties know the baseline spend
- Flexibility: Customers can burst when needed
- Natural Expansion: Usage growth drives tier upgrades
- Risk Mitigation: Overage rates protect against cost overruns
Example from a client implementation:
- Starter: $500/month includes 10,000 API calls (5¢ each), overage at 7¢
- Professional: $2,000/month includes 50,000 API calls (4¢ each), overage at 6¢
- Enterprise: $8,000/month includes 250,000 API calls (3.2¢ each), overage at 5¢
The key is setting the ratios right so customers naturally graduate to higher tiers as they grow.
Step 4: Price Point Optimization - The Value-Cost Balancing Act
Setting the actual price points is where science meets art meets market reality. In the new regime, this balance has become far more delicate.
The Value-Based Pricing Imperative:
Value-based pricing remains the north star, but the calculation has become more complex:
Traditional formula:
Price = Customer Value Created × Value Capture Rate (typically 10-20%)
New regime formula:
Price = (Customer Value Created × Value Capture Rate) - Commoditization Discount + Service Premium
Let me break this down:
Customer Value Created: This hasn't changed conceptually, but the bar has risen. With AI tools enabling rapid development, your product needs to create dramatic value to justify any price. We're talking 10x ROI, not 3x.
Value Capture Rate: In competitive markets, this has compressed from 20% to more like 5-10%. Customers know they have options.
Commoditization Discount: This is new. If a competent developer can build your core feature in a weekend, you need to price accordingly. We've seen companies forced to cut prices 50-70% as their moats evaporated.
Service Premium: Also new. The value-added services, expertise, and outcomes you deliver can command premium pricing even as software commoditizes.
The COGS Reality Check:
In traditional SaaS, we could largely ignore COGS in pricing decisions. With gross margins of 90%+, the math was simple. In AI SaaS, ignoring COGS is fatal:
Real example from a client:
- Customer Query Cost: $0.03 in GPU compute
- Average Queries per User per Month: 1,000
- Monthly COGS per User: $30
- Original Price Point: $29/month
- Result: Lost $1 on every user
They had to completely restructure their pricing:
- Raised base price to $99/month
- Included 500 queries
- Charged $0.10 per additional query
- Added a $299/month unlimited tier for power users
The lesson: In the AI era, you must model unit economics at the individual customer level.
Step 5: Operationalization - Where Strategy Meets Reality
The best pricing strategy in the world fails if it can't be implemented. This is where most companies stumble, underestimating the complexity of making pricing changes operational.
Systems and Infrastructure Requirements:
Billing and Metering:
- Can your system handle your chosen pricing model?
- Real-time usage tracking for usage-based pricing
- Complex discount and contract term management
- Multi-currency and tax compliance
- Revenue recognition compliance (ASC 606)
Horror story from the field: A company switched to usage-based pricing but their billing system could only process data monthly. Customers would use massive amounts in week 1, get a huge bill in week 5, and immediately churn. They lost 40% of their customer base before fixing the issue.
Sales Enablement:
The transition to new pricing models often breaks sales teams. You need:
New Compensation Models:
- Usage-based deals: How do you pay commission on uncertain revenue?
- Service-attached deals: Do services count toward quota?
- Multi-year contracts: Accelerators for longer commitments?
- Expansion incentives: SPIFFs for upsells vs. new logos?
ROI Calculators and Value Selling Tools:
- Detailed TCO comparisons with alternatives
- ROI models that include service value
- Usage estimators for usage-based pricing
- Competitive battle cards with pricing intelligence
Training and Certification:
- Value selling methodology training
- Objection handling for new pricing models
- Negotiation boundaries and escalation paths
- Regular reinforcement and role-playing
Customer Success Transformation:
In the new regime, Customer Success becomes even more critical:
Usage Optimization:
- Proactively help customers manage usage-based costs
- Identify and address underutilization before renewal
- Guide customers to appropriate tiers as they grow
- Create usage dashboards and alerts
Value Realization Tracking:
- Quantify and document delivered value
- Regular business reviews with ROI metrics
- Success stories for expansion conversations
- Churn prediction and prevention programs
The Change Management Challenge:
Changing pricing for existing customers is one of the hardest things you'll ever do. Here's the reality:
Grandfathering Decisions:
- Full grandfathering: Existing customers keep old pricing forever
- Time-limited grandfathering: Protection for 12-24 months
- Feature grandfathering: Old price but no new features
- No grandfathering: Everyone moves (highest risk)
Our recommendation: Segment your customer base:
- Strategic accounts: Grandfather or negotiate individually
- Profitable customers: Gradual migration with incentives
- Unprofitable customers: Aggressive migration or accept churn
- At-risk accounts: Handle with white gloves
Communication Strategy:
- Start communication 6-12 months before changes
- Lead with value, not price
- Provide migration paths and options
- Executive involvement for key accounts
- Clear documentation and FAQ resources
Part V: The Services Revolution - Embracing the $10 Trillion Opportunity
The Sequoia Thesis: Why Services Matter More Than Ever
Sequoia Capital's analysis reveals a stunning opportunity: while the entire software market totals $650 billion (with SaaS at $400 billion), the services market is $10 TRILLION. Of this massive services market, they estimate only $20 billion has been truly automated or digitized.
This isn't just about adding professional services to your software company. It's about reimagining your entire business model around delivering outcomes, not tools.
Three Models for the Software-Services Convergence
Model 1: Software-Enabled Services
Example: The cybersecurity company mentioned earlier
Structure:
- Core Software: $30K-50K ARR entry point
- Managed Services: $300K-500K recurring contracts
- Margin Profile: 60-70% gross margins (blended)
- Value Proposition: "We keep you secure" not "Here's security software"
Why it works:
- Customers can't hire and retain specialized talent
- Threats evolve faster than internal teams can adapt
- Compliance requirements create non-negotiable needs
- Outcomes matter more than tools
Customer quote from our research: "I don't care about your dashboard. I care about not ending up in the Wall Street Journal for a breach."
Model 2: Transformation-as-a-Service
Example: AI agent implementation company
Structure:
- Platform License: $50K-100K annual
- Transformation Services: $500K-2M engagements
- Ongoing Success Services: $100K-200K annual
- Margin Profile: 50-60% gross margins
Why it works:
- AI implementation requires fundamental process redesign
- Internal teams lack expertise and bandwidth
- Change management is as important as technology
- Success requires ongoing optimization and iteration
The key insight: Customers aren't buying AI; they're buying transformation. The AI is just an enabler.
Model 3: Outcome-Based Partnerships
Example: Revenue optimization platform
Structure:
- Base Platform Fee: $10K monthly minimum
- Success Fee: 10-20% of incremental revenue generated
- Optimization Services: Included in success fee
- Margin Profile: 40-70% depending on outcomes
Why it works:
- Perfect alignment of incentives
- Unlimited upside for both parties
- Deepens partnership beyond vendor relationship
- Creates massive switching costs
This model requires:
- Robust attribution and measurement
- Legal structures for revenue sharing
- Deep integration with customer systems
- Patience for longer sales cycles
Conclusion: Embracing the New Reality
The Unchangeable Truth
The software industry as we knew it is gone. The comfortable world of 90% gross margins, predictable subscription revenue, and ever-expanding multiples has given way to a new reality, one where software deflates rapidly, AI accelerates commoditization, and services become essential to value delivery.
This isn't a temporary adjustment that we'll recover from when interest rates drop or the economy improves. This is a fundamental restructuring of how software companies create and capture value. The sooner you accept this reality, the sooner you can begin building a business that thrives in it.
The Strategic Imperatives
To succeed in this new regime, you must:
- Recognize Your Regime: Be honest about whether you're in a high-growth or high-margin environment, and design accordingly.
- Master Pricing as a System: Stop thinking about pricing as a number and start thinking about it as an integrated system that touches every part of your business.
- Embrace Services: The future belongs to companies that seamlessly blend software and services to deliver outcomes, not tools.
- Segment Ruthlessly: Not all customers are worth serving. Focus on those where you can deliver differentiated value profitably.
- Operationalize Excellence: The best strategy fails without execution. Invest in the systems, processes, and people to make your pricing strategy real.
- Iterate Constantly: The market is moving too fast for set-and-forget pricing. Build a culture of continuous pricing optimization.
The Opportunity Ahead
While this new reality is challenging, it also presents enormous opportunity. The $10 trillion services market is largely untapped. Customers are desperate for partners who can help them navigate digital transformation. The companies that successfully blend software innovation with service excellence will build deeper moats and stronger businesses than pure software plays ever could.
The winners in this new regime won't be those who cling to the old playbook, hoping for a return to the glory days. The winners will be those who embrace the new reality, adapt their models accordingly, and execute with precision.
Your Next Steps
- Audit Your Current State: Where do you stand today? Are you operating with yesterday's playbook in today's market?
- Gather Your Data: What do you actually know about your unit economics, customer segments, and competitive position?
- Start Customer Conversations: Your customers will tell you what they value, but only if you ask the right questions.
- Build Your Coalition: Pricing transformation requires cross-functional alignment. Start building support now.
- Take Action: Perfect pricing doesn't exist. Start with direction-ally correct moves and iterate from there.
The regime change is here. The question isn't whether you'll adapt, it's whether you'll adapt fast enough to survive and thrive. The companies that master pricing as a strategic capability in this new environment won't just survive the transformation; they'll define the next era of software.
Remember: In the old world, software ate the world. In the new world, AI eats software, and services eat everything. Position yourself accordingly.
This comprehensive analysis is based on insights from Ajit Ghuman, Co-founder and CEO of Monetizely, a specialized pricing strategy consulting firm. With 16 years of deep experience in software and SaaS, including leadership roles at Medallia and Twilio, Ajit has guided numerous companies through pricing transformations that have generated millions in incremental revenue.
Ghuman is the author of "Price to Scale" (Second Edition), available on Amazon, and teaches the highly-rated course "The Art of SaaS Pricing and Monetization" on Maven. His firm has worked with companies ranging from seed-stage startups to public companies, across categories including cybersecurity, AI/ML, developer tools, and enterprise software.
To explore how pricing strategy could transform your business, connect with the Monetizely team for a consultation. https://cal.com/ajitmonetizely/30min