At this stage, Google Docs, Notion, and messy Excel sheets will do the job.

You’re not scaling you’re discovering.

But once you’ve found your ICP, honed your messaging, and had enough meaningful conversations to sense real intent, it’s time to build a system that can help you accelerate. That’s where your GTM stack comes in. But figuring out where and when to start can be a headache especially with so much noise out there.

Enter the C.A.R.E. Framework.

What is the C.A.R.E. Framework?

Whenever you’re adding a new tool to your GTM stack, you’re essentially doing one of two things: amplifying what already works or removing friction from the sales process. That's it.

In fact, if you map your entire GTM workflow, it all breaks down into four core functions

1. Collect – Identify the right prospects at the right time

2. Activate – Reach out with relevant, timely messaging

3. Remove Barriers – Make it easy for prospects to say yes

4. Eliminate Friction – Automate the busywork to stay efficient

And if your tool doesn’t push the needle in one of those four areas, then it’s just noise — adding complexity without impact.

Let's break it down further👇

Stage 1: COLLECT – Build Your Targeting Muscle

Your job: Find the right people, at the right moment. The “spray and pray” era is over. You need intent. You need intelligence.

Your toolkit:

• ICP Databases: Apollo, Lusha, LinkedIn Sales Navigator

• Intent Signals: Bombora, Clearbit Reveal, Albacross

• AI Boost: Use Clay or Apollo’s AI filters to auto-build prospect lists based on hiring signals, tech stack, funding, and more.

This stage is your radar. The better your radar, the fewer wasted shots.

Stage 2: ACTIVATE – Reach Out with Relevance

Your job: Start real conversations that don’t feel like templates.

Relevance wins. It always has. But now, you’ve got tools that help you scale it without sacrificing authenticity.

Your toolkit:

• Outbound Automation: Instantly, Apollo, Salesloft

• Warm Intro Signals: Clay + LinkedIn activity, Warmly

• Personalization Layer: Lavender, Revenoid

These tools help you show up with context, not just contact info.

Stage 3: REMOVE BARRIERS – Make It Easy to Say Yes

Your job: Remove the friction. Remove the “let me get back to you.” Deals don’t die from lack of interest. They die from lack of clarity.

Your toolkit:

• Sales Enablement (internal): Notion battle cards, Loom demos, Gong

• Buyer Enablement (external): Accord, Recapped, Dock (shared deal rooms with decks, ROI calculators, next steps)

Stage 4: ELIMINATE FRICTION – Automate the Busy Work

Your job: Keep your team selling — not stuck in data entry or tool-hopping hell.

Your toolkit:

• Automation Layers: Zapier, Make, N8N

• Enrichment: Clay, 6sense

• Follow-Up Automation: Outreach, Mixmax

• Meeting note takers: Fireflies or tl;dv

The C.A.R.E. Framework isn’t just a nice acronym — it’s a practical lens to make smart decisions about your GTM stack.

The Final Thought

SaaS is noisy.

GTM is chaos — unless you tame it.

With the right amount of C.A.R.E., you’re not duct-taping tools. You’re designing and scaling what works and removing friction in the entire GTM process.

Start small. Start smart. But once you’re ready to scale — don’t guess. Systemize. Because your GTM deserves better than burnout and spreadsheets.

In fact, AI hasn't just changed pricing models but it’s rewritten the entire concept of value. If you're an AI startup founder, traditional SaaS pricing models probably feel outdated already.

Here’s why it's time to think differently, and why outcome-based pricing might just work for you.

The Old Way: Seats and Usage

Seat-based pricing has long been the default model. Investors love it for its predictability, and it’s simple for customers—one seat, one price. While tiered plans added some flexibility by unlocking more features at higher levels, they were still detached from actual usage. The downside? If you buy ten licenses but only three people actively use them, it’s like paying rent for empty office space—inefficient and wasteful.

Usage-Based Pricing came along to fix that. Pay only for what you use—no waste. It worked wonders for APIs, cloud infrastructure, and developer tools. But it also introduced uncertainty. Bills fluctuated wildly, scaring budget-conscious enterprises. Plus, usage-based billing systems could become an operational nightmare for young startups.

There are two common types of usage-based pricing: a) pay-as-you-go and b) credit-based. Both models are based on actual consumption, but they differ in how billing is handled.

In a pay-as-you-go model, usage is tracked throughout a billing cycle—typically monthly—and users are charged based on what they consume during that period. This approach is popular among infrastructure providers like AWS.

In contrast, credit-based pricing involves purchasing a set amount of usage credits upfront, which can be drawn down over time. This model is more common in data and workflow-focused tools such as Mailchimp, Apollo, and others.

Faced with the limits of pure seat-based or usage-based pricing, SaaS companies started doing something smarter. They mixed both models—Hybrid pricing.

Hybrid Pricing had a simple idea behind it: offer a predictable starting point and then let customers pay more only as they extracted more value with increased usage. Hybrid pricing wasn’t just about protecting revenue. It became a "land and expand" motion in disguise. Customers could start small, see value quickly, and then grow their spending naturally as their needs deepened.

AI Changed Everything (Again)

AI tools supercharge productivity. Suddenly, fewer users can achieve more output. Imagine one marketing analyst completing the work of an entire team, thanks to AI-driven insights. That scenario isn't hypothetical—it’s happening today.

This poses a big question: if fewer people generate the same (or more) value, why keep pricing by seats or usage? AI shifts the focus from "how many" or "how often," to something far more related to value: outcomes.

Outcome-Based Pricing: The New Normal for AI Startups?

Instead of counting heads or API calls, outcome-based pricing asks one simple question: "What measurable result did your customer achieve?"

Here’s how it could look in practice:

• An AI platform might charge based on how much time it saves customers per month.

• A predictive analytics startup could price based on increased customer revenue driven by their insights.

• AI-driven automation tools might set pricing around reduced operational costs or faster task completion.

In each case, the customer pays only when they see tangible results. No waste, no guesswork.

Why Outcomes Work

Pricing based on outcomes naturally aligns incentives. Customers feel safer—no results, no bill shock. For startups, successful customers grow naturally, becoming loyal, long-term partners without aggressive upsells.

It’s like being paid based on the harvest you deliver, rather than charging upfront for seeds. You thrive when customers do.

But Is It All Sunshine and Roses?

Outcome-based pricing isn't without challenges. You need robust ways to measure results, clearly and transparently. You’ll need to invest in analytics, tracking systems, and billing infrastructure. And yes, revenue predictability might feel shaky at first.

But these are solvable problems and founders who tackle them early could unlock significant growth.

So, What Should AI Founders Do Now?

Think about the real-world outcomes your product delivers. Define measurable metrics that your customers genuinely care about. And experiment with this model early, refining as you learn.

Investors pay attention here too. Outcome-based pricing signals startups that understand their customers deeply and align their success with tangible results. That’s the hallmark of truly innovative companies.

The Bottom Line for AI Founders

AI has changed the rules. Pricing on outcomes isn’t just the next step, it’s an entirely new game. It’s challenging but filled with potential.

After all, would you rather pay for seats or success?

Suddenly you're sweating. You've mastered your product roadmap, you've pitched to investors successfully, but figuring out how to pay salespeople? That's a whole new language.

Let's break down this complex topic into something actually useful for you as a first-time founder.

The Secret Sauce of Sales Compensation

Here's a truth bomb: How you structure your sales compensation doesn't just affect your budget—it shapes your entire sales culture. Get it right, and you'll have a motivated team bringing in quality customers. Get it wrong, and you might find yourself with high turnover and bad-fit clients that churn quickly.

When to Hire Your First Sales Person

DEFINITION: Founder Saturation Point - That moment when you're drowning in sales calls and your product development is suffering because of it.

Don't rush to hire sales people. Wait until you (the founders) can no longer handle the sales pipeline yourselves. By this point, you'll have crucial data about:

• How realistic your sales targets are

• What a reasonable pipeline looks like

This gives you the foundation for setting compensation that's both motivating and sustainable.

The Magic 5X Formula

DEFINITION: OTE (On-Target Earnings) - The total compensation a salesperson can expect when they hit 100% of their quota. That includes both their base salary and any commissions.

Here's the golden rule: A salesperson should bring in at least 5X their total compensation in revenue. For example, If you pay someone $100,000 OTE (base + commission), they should generate at least $500,000 in sales.

This isn’t a one size fits all rule, though. For SMB deals, the multiplier might be closer to 4X. And if you're selling big enterprise contracts, you should expect at least 6X or higher.

Test Your Knowledge: The Complex Cases Quiz

Before we dive deeper, let's see if you can solve some real-world compensation challenges. These scenarios will test your understanding and prepare you for the complexities you might face:

Scenario 1: The Long Sales Cycle

Your enterprise SaaS product has a 9-month sales cycle. Your sales rep has been nurturing deals for 6 months but hasn't closed anything yet. How do you compensate them fairly while maintaining motivation?

Scenario 2: The Expansion Revenue Challenge

Your product has significant expansion potential after initial purchase. You want to incentivize sales reps to not just land deals but also set them up for future expansion.

Scenario 3: The Multi-Player Sale

Your sales process involves multiple team members: SDRs who generate leads, AEs who close deals, and CSMs who implement and expand accounts. How do you split commissions?

Scenario 4: The Seasonal Business

Your business is highly seasonal, with 60% of revenue coming in Q4. How do you structure compensation to maintain consistent performance and retain sales talent year-round?

Scenario 5: The New Market Entry

You're entering a completely new geographic market where your product is unknown. The first sales hire will need to build presence from scratch.

(We'll reveal our recommended approaches to these scenarios at the end of this article!)

Splitting the Paycheck: Base vs. Variable

DEFINITION: Base-Variable Split - How you divide total compensation between guaranteed salary and performance-based pay.

The Base Salary, should be comfortable enough for the sales person to cover their living expenses in the location. While the Variable is the one incentivising great sales performance.

This split isn't fixed and tends to shift depending on where your company is in its journey. Early-stage startups often offer a higher base because it takes time to build pipeline. As things mature and the sales process becomes more repeatable, the variable can play a bigger role.

Think of this like the ratio of vegetables to dessert on your plate:

Setting Commission Rates

DEFINITION: Commission Rate - The percentage of revenue a salesperson earns from each deal.

Two common approaches:

1. From Dollar One: Pay commission on all sales

2. Post-threshold – You set a baseline quota of the person’s base salary, and once they hit that, they start earning higher commissions. This motivates the sales rep to push past the threshold. And from the company’s side, you’ve already made back the cost of their fixed salary by that point, so everything after is upside.

Pro tip: NEVER cap commissions! That's like telling someone to stop making you money. 🤦‍♂️

The Payout Timeline

DEFINITION: Commission Deployment - When and how you actually pay the commissions earned.

Most startups pay commissions quarterly after the customer pays their invoice.

Example:

• Customer signs $12,000/year deal (billed monthly at $1,000)

• Each quarter, $3,000 is realized

• Commission is calculated and paid on that $3,000 quarterly

This approach:

• Protects your cash flow

• Keeps sales people focused on quality deals

• Reduces turnover since reps see consistent payouts

• Motivates reps to find customers less likely to churn

The Sales Comp Cheat Sheet

1. Wait until founders can't handle sales anymore

2. Set quota at 5X the total compensation

3. Start with 60/40 or 70/30 base/variable split

4. Pay commissions on actual revenue collected

5. Never cap commissions

Remember: Your compensation plan isn't just about paying people—it's a strategic tool to drive the right sales behaviors and outcomes. The right plan motivates your team to find high-quality customers who will stick around and grow with you.

Quiz Answers: Handling Complex Cases

Here are recommended approaches to the scenarios we presented earlier:

Scenario 1: The Long Sales Cycle

Answer: Implement milestone-based bonuses throughout the sales cycle

Why? This keeps motivation high during lengthy sales processes by rewarding progress, not just closed deals. Examples include bonuses for first meetings with C-level, completed proof-of-concepts, or signed LOIs.

Scenario 2: The Expansion Revenue Challenge

Answer: Pay normal commission on initial deal and reduced commission on expansion

Why? This incentivizes both landing new clients and setting them up for growth. The salesperson gets immediate reward for the initial sale but stays invested in the customer's success.

Scenario 3: The Multi-Player Sale

Answer: Tiered commission structure with different percentages for each role

Why? This clearly defines responsibilities while acknowledging each contributor's role in the customer journey. For example, SDRs might get 10% of commission, AEs 70%, and CSMs 20% on first-year expansions.

Scenario 4: The Seasonal Business

Answer: Quarterly quotas that reflect seasonal differences

Why? This acknowledges business reality while maintaining consistent performance standards. Q4 quota might be 60% of annual targets, while other quarters share the remaining 40%.

Scenario 5: The New Market Entry

Answer: 80/20 base-to-variable ratio for year one, moving to 60/40 in year two

Why? This provides security while the market develops but creates a path toward standard compensation as the territory matures.

If all this still feels overwhelming, remember: even experienced founders revisit and adjust their sales compensation regularly.

The goal is progress, not perfection!

In 2025, the SaaS and AI landscapes are undeniably intertwined. From hyper-personalized CRM platforms to autonomous supply chain agents, AI-driven tools promise transformative efficiency gains. Yet, a paradox persists: while 92% of enterprises plan to increase AI investments, only 1% describe their deployments as "mature". Source. 

The bottleneck isn’t a lack of innovation—it’s the last-mile problem of integrating AI into core workflows without friction.  

This article argues that the next wave of SaaS winners will not merely build better AI models but will architect solutions that dissolve adoption barriers for enterprises. These startups will focus on frictionless integration, bridging the gap between AI’s theoretical potential and its practical, scalable utility.  

The Last-Mile Challenge

Data Silos and the "Garbage In, Gospel Out" Problem  

AI’s effectiveness hinges on high-quality, accessible data. However, enterprises often operate with fragmented systems: legacy databases, spreadsheets, and departmental tools that resist interoperability. For example, a healthcare provider may struggle to unify electronic health records (EHRs), insurance claims, and patient-generated data from wearables—a prerequisite for AI-driven diagnostics.  

AI adoption "hinges on better data," yet most enterprises lack the infrastructure to cleanse, label, and contextualize their data at scale. Startups addressing this—such as those building universal data connectors or AI-native data lakes—will unlock value trapped in silos.  

Time-to-First-Value (TTFV) as a Make-or-Break Metric  

Enterprises are impatient. A 2025 survey found that 67% of CIOs abandon AI pilots if they don’t demonstrate ROI within six months. Source. Therefore, TTFV—the time it takes for a tool to deliver measurable impact—will become a critical differentiator.  

Consider AI-powered legal tech platforms: instead of requiring months of integration, startups like Insync AI (a FortyTwo Portfolio Co.), which uses no-code interfaces, integration and automations to analyse your knowledge base and create Chatbots in hours without customer overhead.  The lesson? Frictionless onboarding = faster adoption.  

Trust Deficits and the "Black Box" Dilemma  

Even when AI works, enterprises fear its opacity. A McKinsey study notes that 50% of employees distrust AI outputs due to concerns about accuracy, bias, or security. Source. Regulatory scrutiny compounds this: the EU’s AI Act and U.S. liability proposals demand transparency in high-risk applications. Source.

Startups like Arthur AI are tackling this by embedding observability layers into AI workflows. 

The Frictionless AI Stack: Key Investment Themes  

 Theme 1: Vertical SaaS with Embedded AI  

Generic AI tools often fail to address industry-specific pain points. Vertical SaaS—software tailored to niche sectors—is poised to dominate. For instance: 

• Healthcare: AI platforms like Iterative Health (backed by Obvious Ventures) combine computer vision and EHR data to optimize colonoscopy screenings .  

• Carbon Accounting: Tools like CarbonBright, (a FortyTwo Portfolio Co.), use AI to automate Life Cycle Assessments in minutes, replacing a process that previously took days. This enables companies to gain granular insights into the carbon footprint of their entire SKU portfolio, offering a level of visibility that was previously unattainable.

Vertical AI startups that solve for business-specific workflows with deep domain expertise will outcompete horizontal players .  

Theme 2: AI Agents as Autonomous Workforce Multipliers  

The shift from generative AI to agentic AI—systems that act autonomously—is accelerating. Jensen Huang (NVIDIA) describes this as the transition to "Physical AI," where agents manage tasks like customer support, fraud detection, and inventory replenishment.  

For example:  

• Salesforce’s Agentforce enables marketers to simulate product launches autonomously .  

• AI-powered accounting SaaS can reconcile transactions, flag anomalies, and generate compliance reports without human intervention .  

The key here is orchestration. Startups that are building platforms to manage fleets of AI agents, ensuring they collaborate seamlessly across departments.  

Theme 3: Compliance-as-Code for Regulated Industries  

As AI permeates sectors like finance and healthcare, compliance becomes non-negotiable. Startups that bake regulatory adherence into their DNA will thrive. Examples include:  

• Data sovereignty solutions: Tools like Protecto, (a FortyTwo Portfolio Co.), encrypt sensitive data while enforcing GDPR and CCPA rules across clouds .  

• AI audit trails: Platforms like SecureFrame automate SOC 2 and HIPAA compliance for AI deployments.  

It is important to note that enterprise resilience as a top priority, especially after incidents like the CrowdStrike outage exposed systemic fragility.  

The Founder’s Playbook: Building Frictionless AI Startups  

 Prioritize Day-One Utility

Avoid the trap of over-engineering. Early adopters care about solving immediate problems, not futuristic visions. For example:  

• TTFV Optimization: Offer a free tier that delivers value in under 10 minutes (e.g., Grammarly’s real-time editing).  

• Pre-Trained Industry Models: Supply chain startups can leverage existing LLMs fine-tuned on logistics data to accelerate deployment .  

Leverage Open Source and Partnerships  

Proprietary data is a moat, but collaboration accelerates adoption. Consider:  

• Open-source AI frameworks like Hugging Face’s Transformers, which reduce development costs.  

• Strategic alliances with hyperscalers (AWS, Google Cloud) to access scalable infrastructure.  

Design for the "AI-Human Handoff"  

Even autonomous systems need human oversight. Startups should:  

• Build feedback loops: Let users correct AI outputs (e.g., Cresta’s real-time coaching for sales calls).  

• Offer hybrid workflows: Tools like Jasper AI allow marketers to edit AI-generated content before publishing .  

The VC Perspective: What We’re Looking For  

At FortyTwo.VC, we prioritize startups that:  

1. Solve a Hair-On-Fire Problem: Focus on pain points where inefficiencies cost enterprises millions (e.g., manual data entry in insurance claims).  

2. Demonstrate Early Traction: Aim for $1.5M ARR and 3x YoY growth before Series A. But meet us before that, we are backers of startups right from the get go.  

3. Leverage Proprietary Data: Unique datasets (e.g., clinical trial data for drug discovery) create defensibility .  

4. Embrace Verticalization: Avoid "AI for everyone"—niche down to industries like construction or pharma .  

5. Architect for Global Scalability: Use multi-tenant cloud architectures and comply with regional regulations upfront .  

Conclusion: The Road to Frictionless AI  

The next decade belongs to startups that treat AI not as a feature but as an invisible enabler—one that integrates so seamlessly into workflows that users forget it’s there. By focusing on the last-mile challenges of data, trust, and speed, founders can unlock AI’s trillion-dollar potential while avoiding the graveyard of "innovative but impractical" tools.  

For VCs, the opportunity is clear: back teams that combine technical prowess with deep industry empathy. The future of SaaS isn’t just smarter software—it’s software that works smarter for us.  

Ready to Build the Future of Frictionless AI?

At FortyTwo.VC, we back founders solving the hardest challenges in AI adoption. If you're building:
✅ AI-native SaaS that integrates effortlessly into enterprise workflows
✅ Vertical AI solutions that tackle industry-specific pain points
✅ Autonomous AI agents that drive measurable ROI from Day 1

We want to hear from you.

📩 Reach out to us at deepthought@fortytwo.vc

The New Marketing Paradigm: Why It Matters Now

For CMOs, this evolution isn't just another digital transformation initiative—it's a fundamental reimagining of how marketing organizations operate, scale, and deliver value. Traditional marketing teams often pride themselves on perfection: the perfect campaign, the perfect timing, the perfect message. But in today's AI-first world, the advantage lies in cultivating environments where thousands of personalized experiences can flourish simultaneously.

The Gardener's Framework: Five Principles for Modern Marketing Leadership

1. Plant Seeds with Purpose: The Power of Core Insights

The most impactful AI marketing initiatives still begin with human insight. Consider Cadbury's groundbreaking "Not Just a Cadbury Ad" campaign in India.

The core insight—”supporting local businesses during COVID-19—came from human empathy”.

AI transformed this seed into thousands of personalized ads featuring Bollywood star Shah Rukh Khan promoting local shops across India.

The result? A masterclass in scaling authentic community connection through technology.

• Core Human Idea: During COVID-19 lockdowns, Cadbury supported small businesses by spotlighting them in ads, fostering community and empathy.

• Putting AI at work :

  • Personalized Ads: AI dynamically inserted local shop details into ads, featuring Shah Rukh Khan endorsing small businesses.

  • Dynamic Scalability: AI-generated custom ads tailored to thousands of regions.

  • Engagement: Users input locations to view ads promoting nearby stores, creating a sense of personal connection

2. Embrace Emergence: Let Data Guide Growth

Modern marketing leaders must become comfortable with emergence—allowing unexpected insights and opportunities to surface through AI analysis.

Spotify's "Discover Weekly" and annual "Wrapped" campaigns exemplify this approach. What began as simple data aggregation evolved into a cultural phenomenon, driving millions of social shares and becoming a year-end tradition.

• What It Did: Spotify curated weekly playlists personalized for users and recapped annual listening habits in shareable formats.

• Why It Worked: Combining personalization with shareability turned users into brand ambassadors.

• Impact: Millions of social posts each year, making “Wrapped” a cultural phenomenon.

And if you want to read more about it .

Club Incentify

Discover Weekly: Spotify's Accidental Home Run

Read more

5 years ago · 4 likes · Club Incentify

3. Orchestrate the Ecosystem: Think Gardens, Not Campaigns

Today's marketing landscape demands orchestration across dozens of channels. Platforms like Google Performance Max and Meta Advantage+ are transforming how we manage this complexity.

Virgin Voyages' collaboration with Jennifer Lopez demonstrates this principle in action—using generative AI to create personalized cruise invitations that maintain brand consistency while adapting to individual preferences.

4. Build Adaptive Systems: Response Over Rigidity

The most successful modern marketing organizations operate like living systems, not mechanical ones.

Coca-Cola's "Masterpiece" campaign showcases this adaptivity, using AI to bridge classical art with contemporary culture, creating resonance across different audiences and contexts.

5. Practice Strategic Pruning: Focus on High-Impact Activities

Just as skilled gardeners know what to remove, AI helps marketing teams identify and eliminate under performing initiatives quickly. This isn't about cost-cutting—it's about rapidly reallocating resources to opportunities with proven impact.

The Call to Action: For CMOs and Marketing Leaders

1. Audit Your Marketing Stack

• How much of your technology enables adaptation versus static execution?

• Are your tools connected in ways that allow insights to flow freely?

2. Reassess Your Team Structure

• Consider creating "garden teams" focused on nurturing ongoing customer relationships rather than just campaign execution

• Invest in upskilling programs that help your team leverage AI effectively

3. Redefine Success Metrics

• Move beyond traditional campaign metrics to measure ecosystem health

• Track adaptability metrics: How quickly can your team test and iterate?

4. Start Small, Scale Smart

• Choose one key marketing initiative to transition to this new model

• Document learnings and build internal case studies for broader transformation

The Bigger Picture: Why This Matters for the Ecosystem

For venture capitalists and founders, this evolution signals where marketing technology investment opportunities lie. The next generation of marketing tools won't just automate existing processes—they'll enable new ways of working that weren't possible before.

The future belongs to marketing leaders who can cultivate thriving digital ecosystems where AI and human creativity work in harmony. The question isn't whether to make this transition, but how quickly you can adapt your organization to thrive in this new reality.

Your garden awaits. What will you grow?

Want to discuss how your organization can evolve its marketing approach for the AI age?
Connect over on LinkedIn or reply to this newsletter with your thoughts.

About our Co-Author

Ankit Rawal | Linkedin Profile

With over 18+ years of experience across unicorns like InMobi and Affle to giants like Microsoft , Ankit specializes in driving international growth,P&L management, and building high-performing teams.

Currently as Vice President of International Sales & Marketing at Affle (NSE:Affle) he focuses on Emerging Markets.

Outside of work, he is a digital marketing professor, mindfulness practitioner, poker player, and history enthusiast.

The Cycle of Technology Predictions

Every few years, a new technology emerges that's supposed to fundamentally disrupt how we build and sell software:

• 2016: Containers promised to make SaaS obsolete

• 2018: No-code platforms were going to democratize software

• 2020: API-first companies would replace traditional SaaS

• 2023: AI would automate away the need for software

Each time, something interesting happened instead: these technologies strengthened SaaS rather than replacing it. Why? Because they addressed the technical challenges of software, but not the human ones.

The Human Side of Software

• The average enterprise uses nearly 300 SaaS applications

• 78% of digital transformation initiatives struggle or fail

• Successful software switches typically take 12-18 months

But these aren't just numbers. Behind each statistic is a story about people trying to get their work done.

Why Software Is Sticky

The real strength of SaaS comes from four deeply human elements:

1. Organizational Memory

Every successful company has its own way of working – its own language, processes, and shortcuts. Software becomes the vessel for this organizational memory. When a sales team has spent years customizing their CRM, they're not just using a tool; they're building their collective knowledge base.

2. Data as Story

Companies don't just collect data – they create their narrative through it. A marketing team's campaign history, a product team's development cycles, a support team's ticket resolutions – these aren't just records, they're the company's story told through numbers.

3. Human Investment

When people spend months or years mastering a tool, it becomes part of their professional identity. I recently met a Salesforce administrator who told me, "This isn't just software I use – it's a career I've built."

4. Community Trust

The most successful SaaS companies don't just build products; they build communities. These communities become support networks, learning environments, and professional development platforms.

The AI Question

Every so often, someone claims SaaS is on its way out. Now, with AI riding high, the chatter’s back: "Will AI replace SaaS?" The answer is simple—nope. SaaS isn’t going anywhere, and AI is only making it better.

AI will undoubtedly transform software, but not by replacing it. Here's why:

1. AI needs structure

AI may sound fancy, but it needs structure—SaaS provides that.

• Reliable processes: Businesses need systems they can count on. AI works best when paired with consistent workflows.

• Clean data: AI relies on good data, and SaaS platforms keep it clean, structured, and usable.

• Accountability matters: When something goes wrong, SaaS provides the audit trails and governance AI can’t handle alone.

2. Human oversight remains critical

AI is smart, but it’s no substitute for human judgment.

• Augments, not replaces: AI is great at pattern matching at scale. But it still lacks the complete context and understanding to make nuanced decisions. Why? Business rules are rarely black-and-white. Humans handle the gray areas.

• High-stakes decisions: Compliance, ethics, risk—these aren’t things you want to leave to a robot. People bring judgment, empathy, and accountability to the table, and that’s irreplaceable.

3.The Investment Perspective

From an investment perspective, I’m drawn to SaaS companies that truly understand these dynamics. The ones that succeed don’t just layer AI on top like a shiny new coat of paint – they weave it into their offerings in a way that respects the human side of software.

What sets these companies apart?

• They prioritize user education, ensuring customers understand not just what AI can do but how it integrates into their workflows.

• They cultivate vibrant communities, fostering spaces where users can share insights, learn from peers, and grow professionally.

• They focus on smooth transitions for customers, offering clear paths for migration and onboarding.

• They respect the existing workflows their users rely on, making gradual enhancements instead of forcing disruptive changes.

And it’s not just feel-good principles – the metrics prove this approach works:

• Net revenue retention above 120%.

• Customer churn rates below 5%.

• A healthy pipeline of expansion revenue growth.

But beyond the metrics, I look for companies that understand they're not just building software – they're supporting human workflows and relationships.

The future of SaaS isn't about surviving new technologies – it's about evolving with human needs. The most successful software companies will be those that:

• Build with empathy for human workflows

• Respect the complexity of organizational change

• Support genuine community building

• Understand that technology serves people, not the other way around

Closing Thoughts

After years of investing in and working with SaaS companies, I've learned that software's resilience comes from its humanity. Every time we predict its death, we're forgetting that software isn't just code – it's the crystallization of human knowledge, relationships, and ways of working.

The next time someone predicts the end of SaaS, remember: technologies change quickly, but humans and organizations evolve thoughtfully and intentionally. That's not a bug in the system – it's the feature that keeps our digital world human.

Traditional onboarding and training methods have remained unchanged for decades. Coupled with the need to continually learn new tools and keep up with industry trends, this creates significant challenges for both new hires and management.

Managers  are responsible for effectively onboarding new hires, ensuring they quickly become productive members of the team. This includes not only delivering training but also providing ongoing support and resources. The inefficiencies in traditional methods can lead to increased managerial workload, slower onboarding times, and potential gaps in knowledge transfer, ultimately affecting team performance and productivity.

Even after the initial training, employees, especially knowledge workers, face difficulties in accessing information due to it being scattered across various platforms or stored in outdated systems. The sheer volume of data makes it challenging to filter through and find relevant information when needed. Incorrect or outdated information can have detrimental effects, making it unreliable for critical decision-making. Even if employees detect inaccuracies, they may increasingly depend on colleagues, resulting in a cascading effect of productivity loss.

Goodgist aims to transform these outdated processes with their AI platform that provides personalised training and enables access to information as per the user’s needs, use cases, and proficiency levels.

Let's delve deeper into the problem at hand:

1. Information Retrieval: Over a quarter of an employee's time is spent searching for relevant information. Employees may also experience information overload, where the sheer volume of data is challenging to filter through to find relevant information especially for time bound tasks. This inefficiency costs the Fortune 500 companies over $12 billion per year. Source.

2. Scattered Knowledge: Employees often face difficulties in accessing information due to it being scattered across various platforms or stored in outdated systems. An average worker in the US has to use 11 different apps in their day to day work. Only 16% of business content is easily accessible to other workers. Source.

3. Training Deficit: Most knowledge workers lack training in knowledge management and don't fully understand how to utilise data sources and analytical tools. Less than 40% of employees apply the learned skills, indicating a poor ROI on L&D initiatives. Source.

Goodgist aims to become the one-stop solution to all such problems that hinders employees from turning into a highly skilled workforce.

Focus & Solution

Goodgist aims to address these challenges faced by employees across industries.  Their initial market focus would be software companies to enhance the capabilities of sales and Support Partners.

Goodgist streamlines the onboarding process and improves day-to-day workflows in the following ways :

• The platform provides personalised training tailored to each partner’s needs, use cases, and proficiency levels, ensuring higher efficacy of their onboarding and training.  

• Then the AI improves information retrieval by aggregating answers from various sources such as software documentation, support tickets, knowledge bases, and online forums. 

• It also generates step-by-step implementation guidelines based on the context of the particular partner heading the implementation.

This approach reduces the load on support teams, allowing partners to provide quicker, more effective implementations to end-users. The result is improved performance, enhanced customer satisfaction, and increased revenue, enabling the scaling of the partner network without additional support costs.

Product Features

• Contextual & Precise: The Goodgist platform integrates with existing Knowledge Management Systems and to any other approved content sources to maintain the integrity of information. This directly addresses the challenge of untrustworthy sources and inaccessible information.

• Content Intelligence: GoodGist’s content intelligence system tailors information not just based on the query but also considers the professional context of the user, whether they are a partner, engineer, or executive. This personalised approach helps mitigate information overload by delivering precise, role-specific data that is directly applicable to the user’s needs.

• Unified Interface: By presenting information in manageable chunks through a conversational and interactive interface, GoodGist promotes easier assimilation of complex data.  

• Microlearning Courses: Tailored for quick and focused learning sessions, these courses enable partners and employees to continuously upgrade their skills without significant downtime.

• AI Research Assistant: This tool automates the search, summarization, and visualisation of information, producing concise and accurate research reports. For partners, this means faster access to critical information and reduced time spent on gathering intelligence, allowing more focus on implementation and customer engagement.

Opportunity

The eLearning market is currently valued at $350 billion, with major players like LinkedIn Learning, Coursera, and Udemy leading the way. By 2028, the TAM for eLearning is expected to surge to $1 trillion. 

The enterprise search market is projected to grow from $5.6 billion in 2023 to $23 billion by 2028, with a CAGR of 9.6%. Source , Source 2. Source 3. Source 4. 

The Founding Team

Our decision to invest in GoodGist is anchored in our belief in its founding team's unparalleled capabilities and proven track record building and scaling global companies. 

Ruban, the CEO of GoodGist, has been involved in the Data and AI industry since its early days, beginning his career as a Data Researcher/Scientist at Yahoo! Search. He then founded Bixee, a specialized search engine that was later acquired by Naspers (JSE: NPN). Continuing his entrepreneurial journey, Ruban created DataRPM, which was successfully acquired by Progress (NASDAQ: PRGS). Now, GoodGist marks his third business venture, and we eagerly anticipate its future under his leadership!

He’s joined by a team of seasoned co-founders who have been with him in previous ventures.. This talented team includes Shyamantak as COO, Vinay as VP of AI and ML Engineering, Vishal as CTO, Fayyaz as CRO, and Chandan Goswamy as CPO. Together, they form a dynamic team poised to elevate GoodGist to new heights.

Vertical Gen AI as a Focus

At FortyTwo, we see enormous potential in the vertical focus of Gen AI.

The right to succeed in AI stems from deep domain expertise. One approach is to focus on a specific vertical; with more industry-specific data, the AI becomes more effective for the respective use case!

So if you're a vertical focused AI company, we'd love to talk. Reach out to us at deepthought@fortytwo.vc.

The journey toward an IPO is structured into three critical phases, each distinctly linked with specific revenue milestones and funding stages. Historical data reveals that for most companies, including B2B SaaS firms, this journey generally takes 8 to 12 years post-founding. This timeframe underlines the long-term commitment and strategic planning required to navigate each phase successfully.

Thread with caution

Before delving into the phases, it's important to highlight a critical aspect: the potentiality of failure inherent in each phase. As each year passes, the percentage of startups that fail increases. The average failure rate for year one is 10%, but in years two through five, a staggering 70% of new businesses will fail.

While this might seem daunting, it is a normal part of the startup ecosystem. Why? Because you are attempting to build a highly scalable company with numerous challenges. More about these challenges down below ⬇️.1

The Three Phases

To access the above table, please click here → link

Phase 1: Establishment and Early Growth

In the initial stage of a SaaS startup, the primary focus is on establishing a firm foundation and initiating growth. This phase is characterized by several key activities and benchmarks that set the stage for future success.

Developing a MVP

• The core objective in this phase is to develop a product (MVP) that effectively addresses a market need. This involves extensive research and development, iterating on feedback, and achieving a product-market fit.

Securing Early-Stage Funding

• Funding is typically obtained through seed rounds or Series A financing. These funds are essential for supporting product development, initial marketing efforts, and building a team.

• Investors at this stage are often angel investors or venture capitalists who specialize in early-stage startups and are willing to take risks on high-potential ideas.

Acquiring Initial Customers and Establishing Market Presence

• The startup focuses on acquiring its first customers, which is critical for validating the business model and establishing a presence in the market.

• Early customer acquisition strategies might include targeted marketing campaigns, network outreach, and leveraging early adopters.

Setting Revenue Benchmarks

• Revenue benchmarks in this phase are typically modest, with the focus being on proving the product’s market fit and laying the groundwork for scalability.

• However, achieving these early revenue goals is crucial for demonstrating potential to investors and for the startup's own confidence in scaling up operations.

Phase 2: Scaling and Expansion

Once a SaaS startup has established its product and initial market presence, it enters the second phase, which is centered on scaling and expansion.

Rapid Growth and Scaling Operations

• This stage is characterized by a significant expansion of the customer base and scaling up of operations. The startup evolves its product offerings based on customer feedback and market demands.

• Scaling often involves enhancing the product, expanding the team, and streamlining operations for efficiency and increased productivity.

Middle-Stage Funding Rounds

• Funding in this phase comes through Series B to D rounds. These investments are crucial for supporting the accelerated growth, market expansion, and operational scaling.

• Investors in these rounds typically include venture capital firms looking for businesses that have shown market traction and are ready for rapid growth.

Aggressive Revenue Targets

• The revenue benchmarks in this phase are more aggressive. The startup aims to significantly grow its customer base and revenue streams, establishing a strong market position.

• Meeting these revenue targets is essential for proving the startup's long-term viability and setting the stage for the maturity and exit options phase.

Expanding Market Reach

• Expansion into new markets, both geographically and demographically, is a key focus. This could involve localizing the product for different regions or targeting new customer segments.

• Market expansion strategies are backed by data-driven insights and a deep understanding of the new markets being targeted.

Phase 3: Maturity and Exit Options

In the lifecycle of a SaaS startup, the third phase, 'Maturity and Exit Options', is a critical juncture. This phase is typically characterized by a significant increase in revenue, a solidified customer base, and a well-established place in the market. It is during this phase that SaaS startups often become attractive targets for acquisition or consider going public through an IPO.

Late-Stage Funding Rounds

• By this stage, startups usually have a clear, viable product and a proven business model.

• Investments in this phase are often focused on scaling the business, international expansion, or preparing for a public offering.

• Late-stage investors are generally more risk-averse, seeking startups with strong, predictable revenue streams.

Exploring Exit Options

• Initial Public Offering : This is often the most publicized exit strategy. An IPO represents a significant milestone, offering liquidity to investors and founders, and raising capital for further growth. The target for an IPO in the SaaS industry typically revolves around reaching an ARR of $150-$200 million.

• Acquisition: Many SaaS startups are acquired by larger companies. This route offers a quicker exit strategy and can be beneficial for startups needing resources and infrastructure to scale further.

• Mergers: In some cases, merging with or forming strategic partnerships with other companies can provide the necessary impetus for growth and market expansion.

Evaluating Market Conditions

• The decision between pursuing an IPO or being acquired depends heavily on market conditions. In a bullish market, IPOs can be more lucrative, while in slower economic times, acquisition can provide a safer, more immediate return.

Post-Exit Growth and Challenges

• The journey doesn't end with an exit. Post-IPO or acquisition, companies often face new challenges in sustaining growth, managing public perception, and meeting shareholder expectations.

Reach out to us

We hope you found this article insightful. For more data-driven insights, do explore our other blog posts.

Additionally, if you're navigating early-stage funding for your B2B startup, we're here to help. Don't hesitate to reach out to us for guidance and support in your entrepreneurial journey.

This examination includes both metrics at the time of the IPO and current data points of publicly traded companies. Our goal is to provide a comprehensive benchmark for early-stage companies aiming for public market success.

Top line Metrics Metrics

Exploring key top line metrics is crucial for SaaS companies preparing for an IPO, especially since these are some of the components most prominently visible to potential buyers, in particular, growth rates and revenue.

NTM Growth Rate

NTM stands for Next Twelve Months. The NTM growth rate is an estimation of a company's expected growth for the upcoming year. Hence, this is the forward looking estimation.

It is relevant to SaaS companies because it provides insight into their expected revenue growth over the next twelve months, which is a key factor in determining their valuation.

A Next Twelve Months growth rate over 20% likely increases confidence for companies going public. Median growth rate for public SaaS companies was 15%, while the top decile came in at 29%.

LTM Growth Rate

LTM stands for Last Twelve Months. It is a company's actual growth over the past year.

LTM growth rate is an important metric as well, because it measures the growth in actual ARR over the past twelve months, as compared to NTM which isn’t explicitly known. LTM growth rate is typically higher than NTM rate.

Companies should aim for at least 30%+ LTM Growth rates at the time of IPO. Median LTM growth rate for public SaaS companies is 21%, and the top decile show an astonishing 46%.1

Revenue at the time of IPO

Total revenue may be the biggest gating factor to going public. Companies simply need a certain scale for public markets to be receptive.

Most SaaS businesses going public fell into the $150M - $250M range, and very few had a revenue less than $100M. Especially with the SaaS markets maturing, expectations regarding a higher revenue before IPO have become the norm. On an average, founders should aim for about $200M of LTM Revenues before an IPO.2

Operating Metrics

Operating Metrics are arguably the most important component on this list, since they depict the financial and operational standing of a company. From a perspective of fundamental analysis, these are critical to evaluate the standing of a firm looking to go public.

Operating Margin

The operating margin measures how much profit a company makes on a dollar of sales after paying for variable costs of production.

Despite most SaaS businesses not being profitable when they go public, they bring the promise of profitability through recurring revenue.

With this in mind, the median operating margin for all public software firms is 10%, however the top decile come in at a much higher value of 38.5%.

FCF (Free Cash Flow) Margin

FCF Margin is the amount of cash available to a company after paying all expenses and making long-term capital investments.

It measures how much of a company’s revenue is converted to free cash flow, and hence is an indicator of the efficiency of the company’s financial management.

A great cash flow for SaaS companies lie somewhere between 20 to 25%, although the median for public companies lies at 9%.

Net Retention

Net Dollar Retention is calculated by dividing the sum of starting ARR plus Expansion Revenue minus Churned Revenue and Downgrades by the starting ARR.

Although the threshold varies slightly depending on the SaaS sub-sector, a net retention rate of over 100% is generally considered healthy. A high Net Dollar Retention rate in a SaaS company signifies strong customer loyalty, successful upselling, stable revenue, reduced reliance on new customer acquisition, potential for long-term growth,

The median net dollar retention of the companies above is 111% so that should be your target with the top decile at 128%.

Rule of 40

The Rule of 40 is a key metric used to to help assess a company's balance between growth and profitability. The Rule of 40 states that a company's combined growth rate and profit margin should be equal to or greater than 40%.

This rule is used to measure the trade-off between profitability and growth and hence is one of the more comprehensive measures on this list.

While the median value for Rule of 40 lies at 32.5% for all public SaaS companies, the top decile come in at an impressive 57.9%, which is testament to the importance of this base requirement for companies looking to go for an IPO.3

CAC Payback

CAC payback period, or simply payback period, is a metric that tells you how long it takes for a company to earn back the money invested in acquiring customers, which helps evaluate the sustainability of a company’s growth.

To calculate this, divide the customer acquisition cost by the average revenue per account multiplied by gross margin percent.

For companies that are still private, anything around 12 months is best in class, while under 20 months is considered fairly good, indicating that the company’s burn rate isn’t too high. Keep in mind that a too short payback period might indicate underinvestment in growth, potentially missing market opportunities. Conversely, a too long payback period suggests inefficient spending and a risk to cash flow.4

Bottom line metrics

S&M % of Revenue

Sales and marketing costs are one of the expenses that tend to balloon up the quickest. While S&M expenses do increase with growth, it should be ensured that the payback period stays fairly low.

While the median for public SaaS companies is at 35% of revenue, the top decile performers like Digital Ocean and Veeva spend below 14% in S&M.

R&D % of Revenue

Early on, when companies are young, the best ones have expenses dominated by by R&D indicating that it is heavily investing into building a great product. As the ARR increases, the R&D expenses start to reduce in favor of the S&M expenses, and a range of 25-30% is considered good, although some of the most successful companies Salesforce, Toast, etc. spend as little as 10%. 

G&A % of Revenue

While the General and Administrative costs being lower is a good indicator with the top decile companies coming in at under 10%, the main point of importance is that it should be relatively constant as a percentage of revenue.

What Valuation Multiples can you expect? 

Valuation Multiples are ratios that reflect the implied value of companies in relation to a specific operating metric, in this case, it measures a company's valuation relative to its revenue.

Valuation Multiples, especially those for public companies, can vary widely based on market sentiment and hence often fluctuate with the state of the economy.

That said, the median revenue multiple for public SaaS companies sits at about 7x; The value for the top decile companies is nearly 3 times at 18.5x. This value increased from about 14.8x from about a year ago.

If the markets continue to grow from the bottom that was a year ago, there should be an increase in these multiples, a positive news for the upcoming IPOs.5

Part 3

Having covered some of the most prominent metrics that companies should aim for before going public, next is the question of how founders can build their start-ups towards this goal from day 0. To take a look at the early steps in the life of a SaaS company hoping to go public, stay tuned for the final part of this series!

For those of us interested in and invested in the SaaS space, Klaviyo’s IPO was a significant event as it marked the first SaaS company to go public since HashiCorp and Samsara's IPOs in 2021

Retail Investors’ Reaction to Klaviyo’s IPO

Klaviyo's stock has experienced mixed results since the IPO. Following a strong start in September 2023, the share price eventually dipped to as low as $24.7 from the IPO price of $30. Recently, however, investors have shown renewed interest, with the stock closing at $27.68.

However, the subdued interest in Klaviyo’s IPO raises the question of what we should expect from the public markets, especially with a queue of SaaS companies ready to IPO.

Factors Indicating an Open Public SaaS Market in 2024

• In 2023, the U.S. economy remained strong with a 5.2% GDP growth despite multiple rate hikes by the Federal Reserve. However, there's optimism about a possible rate cut by mid-2024.
  With the interest rates and market volatility finally reducing, the second half of the year looks hopeful for companies hoping to go public. 

• With the election approaching, fiscal policy is likely to be eased in the run-up. As with past election years, US stocks are likely to deliver strong returns. In the last eight election cycles, the S&P 500 delivered a median return of +7.5% and +4.2% in the 12-months and 9-months leading up to election day. These strong past records could help spur the opening up of IPO markets.

• Going public requires businesses to meet shareholder and market expectations. Multiple SaaS startups now have the numbers to support going public, whether in revenue growth or operational efficiency. Leading the pack, Databricks boasts a $1B+ ARR, followed by up to 10 other firms with $200M+ ARR. We will deep dive into the numbers required for a successful SaaS IPO in our part 2, stay tuned.

• This anticipation is reinforced by the observation that numerous companies have refrained from securing private capital in the past 1-2 years. Now, they find themselves at a critical juncture, facing the need to secure additional funding or provide liquidity to their employees.

• Lastly, a successful IPO from a leading company like Databricks or Stripe could set a precedent, potentially inspiring others to follow in the latter half of 2024.

  (Source, Source)

Companies Waiting to Go Public in 2024

• ServiceTitan : ServiceTitan is potentially slated to be the first SaaS IPO of 2024, as reported by Reuters and other sources. The company, which specializes in service management software, reported an ARR of $250 million in 2021, which has recently increased to $460 million. Given that software companies typically have median Last Twelve Months (LTM) revenues exceeding $500 million when they IPO, ServiceTitan appears, at least on paper, to be well-positioned for a strong tech IPO. (Source)

• Databricks : Another potential candidate with a growth rate of about 50% and almost $2 Billion in ARR, reports say that Databricks will be trying to go public in 2024. Having raised $4 billion from private investors since its founding, is widely viewed as a top IPO candidate, with a $43B valuation. (Source)

• Canva : Another trailblazer with a 50% growth rate and $2B+ ARR, Canva is also one of the rare cash-flow positive SaaS companies. Although there is no official confirmation, the word around is that Canva is planning to IPO in 2024. (Source)

• Stripe : The Digital payment leader of the era, Stripe has filed paperwork showing its intent to make a public offering. Although there is no date set, the market conditions indicate that the IPO is likely to be in 2024. This likelihood is further increased since the company is looking to solve the issue of 10-year stock units awarded to veteran employees that are expected to expire at the end of this year. (Source)

Other companies that are likely to go public this year include Gusto, Algolia, Greenhouse, Talkdesk, Egnyte, Rubrik and Grammarly among others.

Concluding Remarks and Details about Part 2

As we witness these innovative SaaS companies gearing up for their IPOs, the tech landscape in 2024 is set to be dynamic and exciting.

Stay tuned for Part 2 of this series, where we will deep dive into the critical metrics and performance indicators of these SaaS companies. We'll analyze historical data from past SaaS IPOs and also the current public market metrics to provide a comprehensive understanding of what to expect. 

Keep an eye out for Part 2! 

The team is divided between Cupertino and Bangalore and features a formidable lineup of leaders with impressive expertise. Amar Kangaraj is a second-time entrepreneur and the CEO. Baskaran Alagarsamy, who previously led Data Teams at Apple is the CTO.

1. Market Forces Shaping Protecto's Path

The privacy and compliance technology sector is currently experiencing a remarkable surge, propelled by the following significant tailwinds:

• First and foremost, the stricter-than-ever privacy regulations, exemplified by GDPR, CCPA, and HIPAA, have become driving forces. In response to these regulatory mandates, organizations are compelled to reevaluate and enhance their methods for handling, storing, and safeguarding personally identifiable information (PII). 

• The second driver for this growth is the stiff financial penalties imposed for non-compliance. Companies can face substantial financial loss for failing to adhere to these stringent regulations. For instance, GDPR violations can result in penalties of up to €20 million or 4% of annual revenue.1 Additionally, the average cost of a data breach, factoring in lost business, has surged to $4.35 million, marking a 12.7% increase from the $3.86 million figure recorded in 2020.2

• Moreover, the complexity of this landscape is compounded by the emergence of privacy regulations in multiple jurisdictions, posing formidable challenges for companies aiming to maintain global compliance and secure sensitive information. Navigating this intricate regulatory web requires advanced solutions that can effectively adapt to varying legal frameworks from around the world.

• Lastly, the heightened awareness of the value of personal and sensitive data is reshaping consumer and business behaviour. A survey conducted by McKinsey underscores this shift, with 87% of respondents indicating they would not engage with a company if they harboured security concerns. Furthermore, a staggering 71% stated they would sever ties with a company that mishandled their sensitive data without consent.3 This signifies a sea change in expectations regarding data protection, compelling organizations to prioritize robust data privacy measures.

2. Protecto’s Offerings

A. Privacy Intelligence

Protecto's Data Posture Intelligence offers a solution for enhancing Privacy Intelligence in enterprise data management. It provides the following advantages:

1. Visibility into Data: The solution provides visibility into the data being handled by an enterprise, including who has access to it and how it is being used.

2. Identifying Risks and Gaps: The solution finds and prioritizes risks and gaps across data, users, and activities, and delivers continuous auditing.

3. Automating Compliance: The solution automates compliance steps, freeing up resources and reducing the risk of non-compliance.

4. Recommending Actions: Protecto's solution recommends actions to reduce risks, such as removing stale data, reducing over-exposed data, and reducing excess access. These recommendations help to improve data security, reduce the risk of breaches, and stay up to date with various compliance requirements.

B. Privacy Vault

Protecto.ai's Privacy Vault is the answer that a lot of enterprise companies looking for to ensure data privacy and security when trying to use 3rd party systems, including 3rd Party LLMs. Failure to do so could result in a breach of sensitive information as it did for Samsung in May this year.4

Privacy Vault uses Data Tokenisation to mask personally identifiable information (PII) in customer datasets with unique tokens, preserving data integrity. For instance, through the usage of advanced AI, it identifies and masks sensitive chat data, preventing confidential information exposure on AI chat platforms. Data integrity is maintained, enabling interaction with LLMs without revealing sensitive details.

Additionally, it offers comprehensive insights into data flow within AI conversations, empowering users with insightful analytics for better control.

3. The Business ROI of Using Protecto

A. Monitoring Data Posture and Reducing Compliance Efforts

Protecto's solution is a SaaS platform with no code setup. It comes with pre-built connectors to various data sources and is non-intrusive, making implementation easy and straightforward. It operates agentless, meaning there is no need to install any agents on the customer's infrastructure. With these features, customers can start monitoring their data posture in under an hour. Reduced audit/compliance efforts by 9-12 months and hundreds of thousands of dollars.  

B. Reducing Risks

With Protecto, customers can see results in just one day. In 24 hours or less, they can identify and prioritize risks and vulnerabilities, discover overexposed sensitive data, audit user permissions and activities, and generate compliance reports. This process is fast and efficient, even for large amounts of data. In financial terms, this means reduced data protection risks (~$100M+) and a reduction in 20-30% of data, resulting in savings of $100K per year in infrastructure costs.

4. The Expansive TAM 

The global cloud security posture management market, which was valued at $4 billion in 2021, is on a trajectory for significant growth. Projections indicate it will surge to a substantial $15.2 billion by 2031, with a notable CAGR of 14.5% from 2022 to 2031.5

When we conduct a bottom-up analysis, considering the vast landscape of technology companies in the USA, totalling approximately 585,000, we uncover an even more remarkable perspective.6 Every tech company would require some level of data protection, however, even if we focus on the top 5% of these companies as potential clients for Protecto, we unveil a billion-dollar opportunity that beckons.

5. Meet the Team

Baskaran, the brains behind the tech, previously led Data Teams at Apple, personally dealing with enterprise-scale data privacy and security challenges.

Amar, the CEO and a successful second-time founder scaled his previous B2B company to $10 million in ARR before a successful exit.

Together, Baskaran and Amar form a dynamic partnership, bringing to the table a complementary blend of experience and skills that sets the startup on a trajectory toward achieving substantial milestones in its growth journey.

6. FortyTwo’s Investment Focus

We at FortyTwo purely focus on B2B SaaS and enterprise Tech. Our investment in Protecto reflects our strong belief in the data infrastructure space. So, if you are working in data infrastructure or related domains, feel free to reach out to us at deepthought@fortytwo.vc.

The sheer breadth of the climate tech space might seem overwhelming at first glance.

However, when distilled, every solution being developed shares a common purpose: to tackle one of these three crucial challenges of the Climate Equation: 1

1. Innovating to curtail ongoing environmental harm,

2. Crafting solutions to reverse existing damage, and

3. Aiding in adaptation to the residual impacts of climate change.

In our prior blog, we delved deep into the defining metrics of green SaaS startups and how they operate differently from their general SaaS counterparts. Shifting our lens, we now turn to the foundational principles driving climate tech ventures, providing an in-depth look at the various components of the Climate Equation. Additionally, we'll underscore the pivotal role of SaaS within each of these segments.

I. The Damage Already Done

Efforts to mitigate climate risk today acknowledge the damage already caused by human activities. While we can't fully reverse this legacy, it's imperative to recognize the extent of emissions and halt their progression.

Since 1970, carbon emissions have risen by nearly 90%, with 78% of these from industrial processes and fossil fuel combustion.2  This surge has accelerated climate change, with average land and ocean temperatures increasing by 0.18 ºC every decade since 1981—more than double the rate since the late 19th century.3

These figures underscore the urgency for action. Climate tech startups, armed with innovative solutions, are crucial in our quest to limit global warming to a 1.5 ºC increase, steering us towards a sustainable future.4

II. Reducing the Ongoing Damage

Economic progress and maintaining our standard of living mean we can't eliminate carbon emissions overnight. However, a wave of innovative startups is making significant inroads in reducing our carbon footprint, i.e. mitigating the adverse effects of human-induced environmental changes.

In the pursuit of mitigating the carbon footprint of human activities, several significant contributors warrant closer examination, and we will now explore a few of them.

1. Electricity

With a staggering 42% of greenhouse gas (GHG) emissions stemming from electricity generation, the urgency to curtail this statistic cannot be overstated. Effectively addressing this challenge entails a multifaceted strategy, encompassing the transition to cleaner energy sources, bolstering energy storage capabilities, and fine-tuning energy efficiency throughout various processes.5

Pioneering this transformation are innovative startups such as Kitepower, reshaping the clean energy landscape through advancements in wind energy technology. Concurrently, companies like Phelas are spearheading energy storage innovation, providing safer, more cost-effective, and highly efficient solutions for electricity storage.

Yet, the trajectory of progress extends beyond disruptive hardware, with software serving as a catalyst for exponential impact. Consider Rebase Energy, for instance; they're at the forefront of revolutionizing energy modelling. Similarly, Clir Renewables champions renewable energy adoption by leveraging AI tools to optimize the performance of clean energy facilities.

2. Industry

Approximately 30% of emissions in the United States can be traced back to industrial activities, either directly or indirectly. While maintaining industrial progress remains crucial, the imperative to reduce carbon intensity within this sector cannot be overemphasized. 6

Given that a significant portion of indirect emissions originates from electricity generation, the strategies discussed in the previous section play a pivotal role in mitigating industrial emissions. However, the pressing need to address the direct environmental impact stemming from industrial processes cannot be underestimated. In this regard, pioneering ventures like Kanin Energy are making significant strides by assisting heavy industries in converting their waste heat into carbon-free power.

Green SaaS plays an unmatched role in cutting industrial emissions. We have seen a surge in carbon footprint, accounting, and emissions reduction software, which help businesses measure, track, and mitigate their environmental impact. Key players like Persefoni, Sweep, and Watershed are prominent in this field. CarbonBright, a portfolio company, leads in innovative software for product-level emission reduction in enterprises.

3. Food

Estimates of the carbon footprint associated with food-related activities vary, encompassing anywhere from one third to one fourth of total global greenhouse gas (GHG) emissions. This alarming magnitude demands immediate attention.7

In this realm, numerous startups are emerging to address challenges. For instance, in response to the high carbon footprint of meat production, Air Protein is working on achieving carbon negativity by converting captured carbon dioxide into alternative meat products. Similar efforts are underway in various facets of alternative food production (think Lab-Grown meat, Insect farming etc.), with companies like Vly and Jiminy striving for sustainability.8

SaaS plays its own unique role here too, for example, a French startup named Carbon Maps specializes in calculating the environmental footprint of food products, contributing to the broader effort to promote sustainable and environmentally responsible food choices.

4. Transport

With approximately a quarter of emissions originating from the transportation sector, taking decisive action in this domain is imperative. Fortunately, the transport sector has been a focal point of attention in recent years, offering promising avenues for carbon reduction. 9

Electric vehicles (EVs) have seen significant growth, with companies like Tesla leading the charge, and established manufacturers like Volkswagen and General Motors venturing into the sector. Simultaneously, ventures like Remora are dedicated to capturing carbon emissions from vehicles, contributing to emissions reduction efforts.

Once again, software plays a pivotal role in reducing emissions from transportation-related activities. Coulomb AI, a company in the FortyTwo portfolio, is making significant progress in battery analytics and optimization, actively supporting the transition towards electric vehicles. Similarly, Hive Power is championing the widespread adoption of electric vehicles by facilitating charging infrastructure through energy aggregation and optimising local consumption.

Each emission source, thus, presents a golden opportunity for both hardware and software innovations to tackle environmental hurdles.

Role of Green SaaS

III. Reversing Past Damage

Although complete elimination of existing greenhouse gases is not currently feasible, scientists and innovators are actively working to significantly reduce their presence. 

This facet of climate technology focuses on deep technological advancements, chemical and biological research, as well as natural strategies such as tree restoration, agricultural carbon sequestration, some of which we take a closer look at.10

1. Nature Based Solutions

Although natural measures alone cannot fully resolve the issue of climate change, they do play a significant role in its mitigation, potentially contributing up to approximately 20% of the necessary efforts to curb global warming and maintain the temperature increase below the critical threshold of 2°C. 11

This substantial contribution from natural solutions is being supported by global initiatives focused on activities like reforestation, the restoration of grasslands, wetland conservation, and the management of ecosystems on a large scale. These actions enhance nature's capacity to capture and store atmospheric carbon.

Furthermore, these solutions are not solely reliant on physical efforts; they are complemented by software ventures dedicated to optimizing and magnifying the impact of natural solutions. For instance, CarbonSpace leverages satellite tools to estimate biospheric emissions and the sequestration potential of carbon sinks, enhancing the efficiency and effectiveness of these vital environmental efforts.

2. Technology Based Solutions

Technology-driven Carbon Capture and Storage (CCS) primarily focuses on large point sources of emissions like power generation plants and industrial facilities. Advancements in CCS enable the capture and repurposing of carbon dioxide at the point of origin for these high-emission-density sources.12 

Although CCS is still in its early stages, its potential appears boundless, with startups leading the way. For example, Svante is developing infrastructure to capture carbon from industrial flue gas streams, while Carbon Clean is assisting some of the largest emitters, including cement factories and refineries, in transitioning to cleaner processes.

3. Emissions Offsetting

Carbon offsetting offers a means to counteract environmental damage by enabling both companies and individuals to balance their carbon emissions through investments in environmental projects.13

While SaaS may not have been the focus in previous discussions, its role in addressing historical environmental harm is undeniable. It serves as the crucial link that facilitates pioneering innovations and brings them into mainstream adoption, whether it's enabling carbon credit-based sequestration through rating platforms or serving as a financial intermediary in carbon offset marketplaces.

For instance, during carbon sequestration and capture processes, platforms like Sylvera play a vital role in evaluating and rating the carbon credits generated. Subsequently, startups like Patch and GoodCarbon serve as marketplaces for carbon offsetting, allowing stakeholders to reduce their carbon footprint and channel funds into green projects. In fact, platforms such as CarbonX are leveraging decentralization and blockchain technology to democratize carbon offsetting, making it accessible to individuals rather than solely catering to large corporations. Evidently, while it may not be in the spotlight, software continues to be the linchpin enabling emissions offsetting initiatives.

Role of Green SaaS

IV. Adapting to the residual damage

While there's a concentrated drive to curb climate change and temper global warming, equally pressing is the need to adapt to the changing climate realities—rising temperatures and altered natural patterns.

Although mitigation is usually interpreted as the action needed against climate change, it must go in tandem with adaptation to the consequences of global warming, a few arenas of which are highlighted below.

1. Climate Resilient Infrastructure

Climate change continues to exert its influence on every aspect of our lives, leading to various consequences such as rising temperatures, more frequent and severe extreme weather events, and shifting rainfall patterns. One significant area of concern is the vulnerability of built infrastructure, which faces increasing levels of stress and the risk of failure. As a response to this, there is a growing emphasis on constructing infrastructure capable of withstanding greater strains, along with the development of tools to assess and manage the climate risks that the built environment faces.14

This transition encompasses two key aspects. Firstly, companies like Arcadis are at the forefront of pioneering highly resilient and durable construction practices, ensuring that infrastructure is built to endure the challenges posed by climate change. 

Secondly, startups such as Climate Alpha specialize in leveraging AI analytics for real estate, utilizing scenario analysis and infrastructure risk forecasting to assess and mitigate climate-related risks. Regardless of the specific approach, the goal is to establish infrastructure that can withstand extreme weather events and the impacts of climate change, a vital necessity in our changing world.

2. Resilient Food and Water Solutions

The global population is steadily increasing, placing greater demands on essential resources such as nutritious food and clean drinking water. However, these vital food and water systems face mounting pressure, exacerbated by declining crop yields stemming from the depletion of natural resources and unpredictable weather patterns resulting from global warming.15

To address these challenges, there is a global wave of innovation aimed at ensuring the security of these fundamental human needs. Organizations like Climate Farmers are actively promoting innovative regenerative agricultural practices that not only boost crop yields but also contribute to the economic well-being of farmers. In a similar vein, Kilimo is working to enhance resilience against unpredictable rainfall patterns by implementing smart irrigation systems. Additionally, software plays a crucial role in this transformation, with startups like AgroScount offering intelligent monitoring and tracking solutions for fields to optimize agricultural production and preserve yields.

Recognizing the imminent threat to clean water sources posed by global warming, innovation is also underway in the water sector. For instance, Epic Cleantec is pioneering water recycling and reuse solutions designed for use in built environments. Through these diverse efforts, start-ups are paving the way to ensure that the very basic human needs will not be disregarded by climate change.

3. Climate Catastrophe Insurance

As the specter of climate change looms, its potential to wreak havoc on both financial and physical stability through extreme weather events and other disasters cannot be underestimated. Consequently, climate insurance has emerged as a crucial consideration at all levels, serving to safeguard individuals, businesses, and even entire nations from the perils of climate-related risks.

The solutions in the realm of climate insurance are highly diverse, tailored to the specific needs of various entities. These solutions encompass offerings by entities as substantial as the World Bank, aimed at providing financial protection to nations facing climate-related disasters, to startups like Plover Parametrics, which empower smaller insurance carriers to offer climate event assurances to their clientele. Irrespective of the mode or volume, it is apparent that insurance is a necessary part of the adaptation to climate change.

4. Climate Risk Monitoring and Data Analysis

Computation and predictive analytics are vital tools in humanity's fight against climate change. They predict business risks, manage resources, protect infrastructure, and assess natural disaster probabilities.

Software, reliant on sophisticated data modeling, is an indispensable ally in climate adaptation. With AI and advanced algorithms, numerous SaaS ventures lead these efforts. For instance, Climavision specializes in accurate weather forecasting and radar analysis, aiding businesses and communities. MistEO helps address climate change's financial implications, and Overstory proactively prevents wildfires and outages using global vegetation analysis. The scope of risk monitoring and data analytics is  of paramount importance in our efforts to combat the challenges posed by climate change.

Role of Green SaaS

As seen from these few illustrations, this part of the Climate Equation has seemingly limitless potential for Green SaaS development and growth.

Now that we've explored the composition of Green Tech, the opportunities for software in these sectors become even more evident. In the upcoming discussions, we will take a closer look at specific sub-sections of Green SaaS and highlight the emerging startups within them. Stay tuned for more insights!

FortyTwo.VC

If you're building in the Cloud Software or B2B SaaS space, don't hesitate to connect with us at deepthought@fortytwo.vc. Let's explore exciting opportunities together!

Based out of London and San Francisco, CarbonBright was established in late 2022. It boasts a dynamic founder trio: David Rodrigues, Francesca Kennedy Wallbank and Thejas Nair, who bring rich experiences from their tenure at Yahoo, Cloudera, and Unilever.

The Imperative Challenge

It's no news that Greenhouse gas (GHG) emissions are wreaking catastrophic effects on our planet and intensifying global climate change concerns. While entities like the UN are at the forefront, championing 'Net Zero' targets, many corporations are also stepping up to shoulder the responsibility.

Significantly, a vast majority of GHG emissions are traced back to the supply chains of these industries. Thus, there's a growing demand amongst organizations for tools that amplify visibility and empower them to diminish their supply chain footprints. Concurrently, the Lifecycle Assessments (LCA) facilitates a detailed assessment of the individual impacts of products, spanning aspects like water consumption, air pollution, and, of course, emission profiles.

A Wind of Change

There are two primary drivers of change pushing for more carbon-neutral initiatives within industries: consumer demand and climate regulations.

Increasingly, consumers have become eco-conscious, using their purchasing power to favour sustainable products and services. This heightened awareness of environmental issues means brands are now under pressure to adapt. This consumer drive is pushing industries towards greener practices and heralding a wave of green consumerism.

And when we examine climate regulations globally, the importance of GHG reporting has never been higher than it is now. Regulations requiring companies to report their overall carbon posture have been implemented in recent years in the USA, EU, and more recently, in India.

Furthermore, we are also observing countries mandate reporting at the product level, as demonstrated by the UK's Green Claims Code and the European Commission’s Product Environmental Footprint Directive. These regulations ensure that companies aren't just talking the talk but are also walking the walk. They aim to confirm that a company's claims about its product are based on accurate assessments and not just marketing gimmicks.

However, for Consumer Packaged Goods (CPG) companies, determining the carbon footprint of their product portfolio represents a monumental task. Relying on LCA  analysts is both time-consuming and expensive, with each product’s LCA taking weeks to complete and costing thousands of dollars for analysis.

This is where CarbonBright's capabilities truly shine.

CarbonBright's Innovative Solution

CarbonBright is at the forefront of transforming sustainability assessments. Their platform automates in-depth, product-level carbon impact evaluations, simplifying the intricate LCA process. 

With a foundation built on over 100,000 data points, CarbonBright efficiently gathers data and employs predictive modelling to deliver comprehensive analyses. This is especially valuable when data is scarce and LCA analysts would otherwise spend significant time attempting to source these data points, sometimes unsuccessfully.

More than just analytics, the platform identifies emission hotspots and provides actionable insights to help businesses reduce emissions and bridge the gap between companies and their sustainable goals.

Ultimately, businesses benefit in three key areas: 

• The platform excels in delivering rapid results by automating the complex process of supply chain data collection and analysis. This emphasis on speed enables businesses to quickly identify and integrate sustainable innovations across their entire product portfolio. 

• Furthermore, supported by an expansive data network and advanced modeling, it provides accurate LCA evaluations. 

• Lastly, such automation notably reduces the time and effort required for LCA assessments, leading to considerable cost savings.

Blending speed, precision, and cost-efficiency, CarbonBright's platform paves the way for more businesses to seamlessly achieve LCA reporting readiness.

TAM: Unveiling a Massive Market Opportunity

The CPG  sector offers a vast landscape for businesses to operate within. Take a moment to ponder the extensive reach of giants like Walmart, which commands a supply chain boasting over 100,000 suppliers globally. Now, if you consider the ripple effect — where many of these suppliers have their own cascading chains of suppliers — the scale of this ecosystem becomes truly awe-inspiring.

Our exploration into the TAM reveals a market brimming with potential. With suppliers stretched across the globe and nested within intricate supply chain structures. When we broaden our horizons further. Beyond the primary focus of the CPG sector, they present their own vast canvases of opportunity. 

In essence, when we synthesize this data, it becomes evident that CarbonBright is poised at the cusp of a colossal market opportunity. The potential is vast and undeniably impressive.

The Stellar Team:

CarbonBright's team is its linchpin.
Francesca, a beacon of environmental passion, has consistently demonstrated her commitment to sustainability. From launching green entrepreneurial ventures and assisting global brands at Unilever in digitally communicating their sustainable initiatives, to her notable appearance on The Apprentice UK, she embodies the ethos that CarbonBright champions. 

David, with his impressive product-centric background and history of driving companies to significant exits, brings unparalleled product expertise.

And Thejas, with his robust engineering acumen, steers the engineering endeavours leveraging his experience in building large-scale data-driven applications. 

FortyTwo’s investment Focus

FortyTwo's focus remains on world-changing entrepreneurs in B2B SaaS, with CarbonBright exemplifying that vision. As CarbonBright advances in its mission to create a lasting impact on the climate race, it is fortified by the power of software. Through its pioneering solutions that enable enterprises to adopt greener practices, it is poised to revolutionize both the climate and software sectors.

Reach out to us

If you are building within the Green SaaS domain or in Enterprise Tech, please don't hesitate to reach out to us. You can contact us at deepthought@fortytwo.vc.

With every challenge comes opportunity. As the pressing threat of climate change intensifies, it has paved the way for entrepreneurs to innovate and provide groundbreaking solutions in the Climate Tech sector. Currently, the cumulative enterprise value of climate tech startups worldwide stands at $2.6 trillion. Source

Having seen the importance of climate technology as a whole, the focus now shifts to the segments within green tech, which at the broadest level can be classified into hardware and software.

Why is software necessary for an effective transition to green solutions?

When most people think of Climate Tech, they envision cutting-edge technologies that have the potential to revolutionize our world. Indeed, deep-tech innovation in this domain is crucial for steering us towards a sustainable, green future. However, the development of new hardware and processes inherently carries risks.

Yet, a facet of Climate Tech that often slips under the radar for many enthusiasts is the optimal utilization of existing technologies. This is the juncture where software plays a pivotal role. Whether it's harnessing software to refine current methodologies and slash emissions, or deploying software solutions to introduce and integrate newer, eco-friendly technologies, Software remains at the heart of climate innovation.

Drawing insights from Energize Ventures' article titled “When SaaS Metrics Fail in Climate Tech”,  this post sheds light on a pivotal distinction. Even though software underpins the climate tech domain, the investment metrics for climate tech SaaS diverge significantly from their counterparts in traditional SaaS. This discrepancy has often led to misconceptions about the true nature and potential of climate software.

Market Size and Potential of Climate Tech:

Current Landscape: As per PwC's report, climate technology emerged as a dominant investment magnet in 2022, capturing a quarter of venture investments. This field witnessed a staggering $52 billion in investments just in that year. However, PitchBook predicts this to be the tip of the iceberg, forecasting the market's escalation to $1.4 trillion within the next five years. Source

• Evolving Demographics: Climate entrepreneurs, being at the forefront of their challenges, are still in the phase of defining their target market and potential clientele. While the market might seem nascent currently, its trajectory is set to expand exponentially. PitchBook's projections indicate that sectors like carbon tech software and fintech are poised to see a compound annual growth rate nearing 9%. Source

• Supporting Global Trends: A McKinsey report underscores several global trends amplifying the market's potential. Source One key observation is the existing dichotomy: the world's growing dependency on fossil fuels juxtaposed against robust commitments from both the public and private sectors to slash emissions. This scenario has sparked an unprecedented demand for scalable clean energy alternatives. Moreover, regulatory dynamics, such as the proposed SEC climate disclosures and the freshly ratified EU climate legislation, further bolster this demand.

• Green Technologies Gaining Ground: As green technologies become more cost-effective and their profit margins swell, they are rapidly transitioning from niche to mainstream. With rising public awareness, corporations face mounting pressures to adopt sustainable practices.

From all angles, be it regulatory pressures, market demand, or global commitments, the momentum behind climate tech is undeniable. The sector isn't just a fleeting trend; it's firmly rooted in our future, with surging demand for innovation.

Comparative Sales and Growth in Climate-Tech SaaS vs. Traditional SaaS 

1. Nature of the Sales Cycle:

Slower Growth Profiles: Climate SaaS companies generally exhibit slower growth profiles compared to traditional SaaS. This is attributed to their typical clientele, which includes energy companies, governmental bodies, and large corporations. These entities often have rigorous internal risk reduction processes, resulting in extended sales cycles.

Customer Familiarity with SaaS: A significant portion of the clientele for climate solutions is relatively unfamiliar with SaaS. Consequently, the additional time needed for persuasion and education further elongates the sales process.

2. Analyzing the Growth Metrics:

ARR Growth Rate: While the Annual Recurring Revenue (ARR) growth rate for climate SaaS might be more modest than that of traditional SaaS, there's an upside. Climate SaaS companies experience a far more limited decay in their growth rate, ensuring consistent and lasting growth. For context, while typical SaaS companies might witness a 15% growth decay, it can be a mere 5% for climate SaaS entities. Source

3. Margins, Retention, and Integration:

• Gross Margins: Climate SaaS might operate with tighter gross margins compared to their traditional counterparts. However, they compensate for this through the two primary avenues mentioned below.

• Higher Stickiness: Climate SaaS solutions tend to be more deeply integrated into a client's daily operations, ensuring their continual relevance and utility.

• Retention and Chain Adoption: Once a climate software tool is embraced for a particular function within an organization, it's frequently extended across multiple business units. This broader implementation confers upon it a distinct advantage over conventional software products.

The nuanced sales cycle and growth dynamics of climate SaaS shouldn't be perceived as shortcomings. Instead, they underscore the sector's unique characteristics and strengths. In upcoming segments, we'll delve deeper into the myriad sectors within green software and their transformative potential in the fight against climate change. Stay with us!

In today's rapidly globalizing economy, many Indian startups especially from the SaaS domain are considering the benefits of incorporating in the United States. This primer seeks to answer three critical questions for those considering this step: Why should you incorporate it in the US? How can you do so? And why is it important to incorporate early?

I. Why incorporate in the USA?

Market Size & Potential

The USA accounts for 40% of global software purchases in 2021. 1 By incorporating in the US, you gain access to a vast and high-spending market, creating more opportunities for your B2B startup.

Pricing Arbitrage

Our experience with SaaS companies reveals that as a rule of thumb, a dollar sale in India equates to ~$2.5 sale in Southeast Asia and Africa, ~$3 in the Middle East, and ~$7 in the USA. In fact, one of our portfolio companies saw a remarkable revenue increase by charging 15 times their original Indian pricing in the US market. This higher pricing results in greater revenue and profitability, as costs remain in Indian Rupees.

Customer Acquisition:

Challenges with customer acquisition can vary between India and the USA. Indian buyers may need long-term relationships before purchasing, while US customers may close software sales quickly if value and trust are conveyed effectively. Establishing trust with US clients is easier with a local presence. Consequently, setting up a company in the USA and integrating it into the US customer network can result in a faster sales cycle and higher pricing.

Funding and Valuation:

Establishing a company in the US can improve access to global funding, increase business valuation, and provide flexibility for potential future overseas listings. Tracxn data indicates that there are around 10,632 VC funds in the US, compared to a smaller pool of 1,654 Indian VC funds. 2 3.

II. How to Incorporate?

Once you have confirmed that a US incorporation aligns with your business goals, you can proceed with establishing your company in the United States. Here are the general steps that the founders should anticipate:

Step 1: Avoid Directly Registering a Delaware C Corp

The RBI has issued regulations which prevent creating a US entity directly from India, as it would trigger Round Tripping. Round tripping occurs when money flows out of India and then returns to the original Indian entity. 4
So, if you plan to operate in India and the USA, it's best not to set up a US entity directly, even though the USA allows foreign nationals to start businesses easily. Therefore, online services like FirstBase or Stripe Atlas might not be suitable, as they don't consider RBI round-tripping rules.

Step 2: The Workaround

To avert round-tripping, Indian lawyers and startups have historically employed three methods:

1. Gifting Shares: In this approach, someone would create a US entity and gift you the shares of the entity. This approach is now disallowed due to the RBI's recent statement in August.

2. ESOP Transfer: Uncommonly used, this method transfers US entity ownership to Indian founders via ESOPs. Tax inefficiencies and other commercial issues make ESOPs impractical, and this step is seldom employed.

3. Establishing Indian LLP: Founders create an LLP (“Founder’s LLP”) in India, dividing its ownership among them. This LLP then owns the US Holding company. Recently, many founders have chosen this route. Nevertheless, potential regulatory scrutiny and adverse tax implications for individual investors may arise. Additionally, indirect shareholding in a company could hinder enforcing contractual obligations on promoters. 5

Step 5: Setting up a New Indian Entity

Now that you have established a Founder’s LLP in India and then set up your Holding Company in the US, the next step is to create a New Subsidiary in India under the holding company.
However, if you already have a company (“old Indian Company”) registered in India, you cannot make it a subsidiary of the holding company as this would trigger round-tripping again.
Therefore, you need a new Indian subsidiary Company for the Holding company. 6

Step 4: Wind down any “Old Indian Company”

The Old Indian Company will have no use now and will have to be wound down. During this process, customer contracts will shift to the US Holding Company, while Indian employees and their contracts will fall under the new Indian subsidiary. 7

Why Incorporate Early?

More relationships more complications

As your company grows in India, you will add investors to your cap table, acquire more customers, and engage with various vendors. They will all be legally related to an Indian Entity.
Transferring all these relationships to a US entity becomes increasingly complex as more entities get involved. Furthermore, some stakeholders may be reluctant to shift their contractual relations to a US company.

Indian VCs and SEBI Restrictions

Indian VCs might be hesitant to move their investment, as they could face challenges holding shares in foreign entities. SEBI imposes a 25% capital limit for each India Registered VC fund, meaning that a fund cannot allocate over 25% of its corpus to entities registered outside India. 8
Furthermore, there is a cumulative limit at the national level on the capital that can be invested in foreign entities by all Indian VCs & AIFs combined. We have already reached that limit, and SEBI has not increased it. 9. This has meant all new foreign investments are put on hold until SEBI changes its mind.
In conclusion, it's crucial for SaaS founders targeting North America to transition to a US entity early and secure funding from US VCs. This strategy streamlines your focus, allowing you to concentrate on growing your business in the US.

Closing Remarks

If you're building in the Cloud Software or B2B SaaS space, then we should definitely catch up!!
You can reach out to me at dishan@fortytwo.vc.

Footnote

Today, we’ll take a stab at the Platform First approach. To qualify, this is not a product management conversation. It’s beyond it and more a company-focused approach.

In our view, the building blocks for this include the following:

• The Right Team

• Speed of Execution

• Right Starting Point

• And a clear “Why Now.”

The Right Team

We won’t really go into the Founder Market Fit aspect (you can find it covered here, here, and here)

Source: HowtoSaaS

Speed of Execution

Now Speed of Execution is very interesting and nuanced, where (our) words won’t do it justice.

We are at a time when software has become fairly modularized. There are playbooks for scaling, identifying the right architecture, etc., and most importantly, selling as an unknown vendor is easier now than 10 years ago. In this environment, being ahead of the competition is very crucial, and we believe Speed of Execution is a function of having the right leaders with the right team-building experience.

And the tacks need to change for different times. Work Chronicles below represented one of the most common scenarios.

Coming to what we want to cover in this post, the Right Starting Point, and “Why Now.”

The Right Starting Point

So what is the right starting point?

Companies that end up successfully fulfilling their vision get this part right. They start with the right feature/use case to build from; you’d generally hear this called the “wedge.” This could look like a tool/use case to manage new complexity.

An example of this would be Hashicorp building an entire suite of cloud management tooling platform starting with Terraform, which decreased the complexity of provisioning resources on the cloud or Databricks building an entire data science platform through their start with Apache Spark, which made it much easier to process large amounts of data.

Take an example of 2 companies with the same skill and experience starting at the same time and trying to disrupt an industry. But what’s different in this case is that they start with completely different approaches.

The way it usually pans out is that in the end state, they will probably converge on each other, see Snowflake and Databricks. We take this particular example since both are clearly moving toward each other, but the story hasn’t played out.

Another example of different starting points to a platform where the story hasn’t played out is Deel vs Rippling which are coming for Workday’s HRMS suite (or more if you ask some people)

In a lot of cases, the story plays out, and there only remains one. Because the other didn’t have the right starting point. Evernote is probably an example that comes to mind. While Evernote still exists (we believe), multiple companies came after the workflow it provided. Notion would be one contemporary example.

The other key point is that of Why now?

Starting at the wrong time either marries you to the wrong approach (one interesting thread from here is the classic first mover’s advantage, a contentious topic, which we will probably tackle some other day) or does not get the flywheel effects since your customers don’t know how to leverage your product/platform effectively — For example, AI companies that have been there from 2013 but might now see themselves competed out by their 1-2-year-old competitors.

Source: Avichal Garg

Coming back to the main theme, one of them has the platformization opportunity open to them while the other doesn’t.

So what makes a solution a better platform opportunity?

• It goes without saying that what we’ve covered, the right starting point, is crucial.

• But a few other things stand out as the best platform opportunity. Now these might not be applicable to everyone, but most will have one of these as a common factor.

  • Being embedded in mission-critical workflows

  • The same buyer for the additional modules

  • Network effects — Snowflake and how they are leveraging data sharing

  • User experience — a user is more likely to recommend a use case if they’ve had a great experience with the vendor for something else

  • More use cases for no additional implementation hassles

Platformization is not a winner take all in B2B as it is in B2C — Google in search and Amazon in online retail for their dominance over long periods but it is still advantageous

Some interesting platform approaches adopted by Big Tech companies

• Cloud Marketplaces by Public cloud platforms where new software is sold within the ecosystem

• Snowflake’s Data Collaboration product

• Cloudflare’s effort to become the 4th public cloud

• ServiceNow adding all enterprise workflows (adding employee and customer workflows to its IT workflow flagship product)

All this is not to say that point solutions cannot be successful.

Calendly is a good case study.

One has to look at Calendly, which in 2021 crossed $100M in revenues at a $3-4B valuation. Of course, things have changed now, but its success has continued to a large extent. And it hasn’t been disrupted to a large extent.

For the analysts out there

Bringing this all together, the platform opportunity is the most lucrative one out there.

A great Point of View to identify them would be to start with these 3 questions:

• Why now?

• Is it the right starting approach?

• How well are they embedded into the workflow?

While this could be a fairly basic representation and heavily focused on SaaS businesses, the key laws that govern this are universal.

This is a particularly interesting time to use this framework to evaluate the sudden explosion of AI-led/AI-native businesses propping up everywhere. With a major asterisk of course that there are always founders out there who break the norms!

We would love to chat with folks who’ve thought deeper about this as well as folks who have thought about this in the context of other industries!

You can reach out to us at deepthought@fortytwo.vc, or any of us individually (Asutosh, Dhruv, Dishan) and discuss/brainstorm in detail.

Do you know the one word that’s present on about 90% of the landing pages of Public SaaS companies?

It’s Platform.

Incidentally, this is the question that we also have to tackle every time we meet a new company — Does this idea have the ability to become a platform?

But before that, here’s a quick intro to this series that we call:

Hitchhiker’s Guide to …

It’s our attempt to capture & abstract our conversations and diligence notes around each potential investment we evaluate. Since we spend all of our time SaaS, we thought of breaking down some of the basic mental models and sectoral views we use to evaluate an industry or the interesting companies we meet.
The idea of this series is to go public with our thoughts and discuss this with the larger universe. Get critiqued and iterate.

Hope you will find this interesting. Feel free to drop any suggestions for any improvements or if this was helpful in the first place.

Okay, so back to platforms. Let’s start by defining a platform before going into why it’s important and some takeaways on identifying one.

Now we are not talking about Platform in a conventional sense of something like a PaaS1, but more so on how tightly a company is integrated across all the workflows of the user.

Examples include a Salesforce or a Clari in Sales, Postman for API management, Workday for HRMS, etc. The consistent factor in all of these platforms is that they are integrated deeply with their customers, which makes it difficult for someone else to compete with them.

To put it simply, Platformization helps you to:

• Sell more features to your customers — Increase NRR2. The below infographic shows how Datadog grew with its customers over the years by adding products to its suite.

  

  Source: Datadog Investor Presentation Feb ‘23

• Puts you in the best position to compete against potential disruptors — Atlassian bolstering its suite of products with Confluence, IT management, Trello, etc., in addition to Jira helps it compete against competitors who might offer solutions competing with any one of its products.

  

  Source: Atlassian: Analysis and strategic recommendation by Ryann M. Carlson (2017)

• Position yourself with strength in your ecosystem — If you have chosen the right starting point/capability, everyone in your landscape wants to partner with you. Snowflake & Databricks have executed this strategy brilliantly in the Data ecosystem, where every new entrant wants to partner with them.

  Source: Databricks & Snowflake

Don’t get us wrong, you don’t have to become a platform. You can own your competency and build a suite around your core use case. But if you don’t stay ahead of the curve with this, you end up at the risk of becoming a point solution or, worse, disintermediated.

💡 In the age of increased focus on NDR/NRR, platformization has become a dominant theme in capturing lifetime customer value.

The above approaches help Platforms build defensibility, the opportunity to capture a larger part of their TAM, and bring greater efficiency to sales.

What happens if you can’t create a platform opportunity?

The classic example here is Slack. Slack was one of the fastest companies to a $100M and captured one of the strongest starting points with displacing email within enterprises (a feat probably unthinkable before Slack). But it wasn’t able to create a platform around it, and Microsoft eventually built something, admittedly not of the same quality but with a much larger user base. Now the story is still playing out, and Slack is one of our most used products, but Microsoft’s Platform approach in competing with Slack puts it at a slight disadvantage.

Source: Kinsta

Now that we’ve covered what are Platforms and how can they help create sustainable advantages, we will cover the question - What are the building blocks for a platform opportunity? in our next post.

We would love to hear your thoughts on how you look at building and evaluating Platform businesses!

I’ve been meaning to start a series of posts for early stage founders starting their journeys of building B2B SaaS products out of India and focused on global audiences.

The learnings come from my day job where I work with Indian SaaS founders. Although I will refrain from offering advice, I did want to provide my perspective on some of these topics.

One thing that we come across again and again is that as a founder of a seed stage company there’s nothing more crucial, other than recruiting, than getting to a Minimum Viable Product (MVP) quickly.

One of the levers that help get to this phase is strategically selecting and collaborating with the right design partners to refine the edges of your product.

What are design partners, you ask?

Design partners are early adopters of your product who help in defining your problem statement and shaping solutions as you develop your product. They offer valuable input on your product, such as UI/UX, Features, Pricing, etc.

A common misconception I would like to clarify is that design partners and pilot customers are interchangeable, whereas they are not.

• When you do pilots, they are usually post-product POCs. What you are trying to find is whether your product solves the pilot customer’s use cases successfully, not whether your product is useful. A subtle but important difference.

• The way we look at it is, the outcome you are looking for from a pilot customer, is validating the value and converting to a recurring revenue customer. Whereas, the outcomes you look for with design partnerships is effective feedback that helps you validate the product value and get to an MVP quicker.

• While design partners transitioning to customers is an added bonus, a design partner is selected with an intention to provide feedback and not necessarily as a future source of revenue

Does every scenario require design partnerships? No.

Now if you are a product focused on SMBs or Individuals, you can get away with launching the product and iterate quickly based on user dropoffs and customer reviews. But when you have a mid-market/enterprise product, you can’t really go through the entire sales process before seeking product validation. In such cases, working with a few design partners helps you go to market with a product close to what your end user needs.

💡 Design partners help you put the finishing touches to your product.

One key point to emphasize before getting to the Checklist is the importance of working with design partners who closely align with your defined Ideal Customer Profile (ICP).

Why?

Working with the right design partners can help you add those additional features that makes your product enterprise ready or help you narrow down your Ideal Customer Profile (ICP) based on actual usage rather than just customer discovery.

If these partners are located in the US, it's crucial to explore all possible strategies to secure these partnerships, as they can help to accelerate the development of a Minimum Viable Product (MVP). While it may be challenging to establish these partnerships, the time and resources saved in the long run can be significant. If, on the other hand, you are limited to working with partners in India, it's crucial to ensure that they closely align with your ICP in terms of workflow and experimentation on the edges.

Here is a checklist of things to keep in mind to identify the right partners for you.

1. Impact — One thing that would set your product on the right path is if a company is using your product as a competitive edge. These are generally customers who drive innovation through their needs, and preferences. You are more likely to stay ahead of the curve when you engage with forward-thinking customers.

2. Agility — Time is a crucial factor for startups, as market opportunities are often time sensitive and funding is limited. As a time and money constrained organization, speed is your greatest asset. That’s the same thing you should look for in a design partner.

3. Size — Very early stage companies have other existential challenges, and collaborating on your product may not be a very high priority for them. While established market leaders may not always be exploring experimenting on the edges. Finding high growth companies aiming to displace/disrupt market leaders would be ideal design partners.

4. Target Market Match — The first step is to ensure that the design partner represents the target market. The needs and systems of the design partner should be similar to those of the companies you interviewed during your customer research journey and to the overall market. It's essential to avoid becoming too specialized for one particular customer, or worse, creating custom software that only serves one client.

5. Product Market Portability — This is particularly relevant for SaaS founders in India: how closely does the ideal customer workflow align with the workflow used by Indian customers. In many cases, the workflow may differ significantly, requiring significant adjustments to the product to accommodate the workflow of customers in different regions. However, this may not be an issue in sectors where the Indian market is significant in size. But it's not the case for all segments.

Okay, so we have answered the who. Let’s get to the when.

It is important to not start off too early. It is you who had the vision for the product. You have done all the customer discovery, identified a need and visualized a solution. Post building out this vision is when you should work with design partners to iron off the edges.

💡 This checklist would help avoid the critical misstep of working with users who don't fit the ideal mold of your ICP.

I also wanted to highlight a few challenges that you might come across.

1. Knowing a good customer from a bad — There would be times where you’ll have a customer who fits your ICP but has some peculiarity that makes you spend more time with them on feature requests, or the variable expenses are too high, etc. This would be a bad design partner at this point of your journey. Letting them go might be a prudent option even when they are good partners to have.

2. A similar challenge is when you will encounter a group of customers who are using your product for a drastically different use case than what you envisioned. If your sales pitch is based on this group's usage, it may not resonate with your target customer, making it difficult to sell the product. This can again result in wasting valuable time. Cutting them loose would not be a bad decision in these cases.

3. Another challenging area is building features that your customers tell you to build. Slightly counterintuitive but I’ll use a quote by Shailesh Lakhani (heard on one of the podcasts, you can find it here), “Customers don’t know exactly what they want, but they can give you clues and hints that can lead you to figure out what is the real opportunity that is in front of them.“ Customers may think they know what they want until they see something better.

4. This is one from an investors point of view, and while this could just be me nitpicking, sometimes founders or investors mistake design partnerships as "traction," assuming that these users will generate future revenue or that a high number of users on a platform is a sign of actual demand for the product. This can lead to unrealistic expectations on both sides of the table about what progress should look like. It's crucial for both parties to have a clear understanding of what the outcome from these customers is expected to be.

Your most important focus at this stage should be to swiftly iterate towards an MVP. The goal is to gather feedback, in its most candid and authentic form, from users on the problem they are facing, the current solution, and whether your product is a superior alternative to the status quo.

If you have gone through this process and would like to share your experience, I would love to chat with you and learn more about it! If you have any questions, please don't hesitate to reach out to us.

If you're building B2B SaaS or enterprise technology products for global markets, we would absolutely love to connect with you! We're excited to hear about what you're working on and how we can help.

Problem-Solution-Fit

I’d describe this stage as reducing churn, early signs of an ICP, customers using the product more and more progressively, and being able to provide a high NPS for the product.

Up to this stage, it’s mostly a founder-led sales process, but once you see these signs, it’s time to start building your scaling engine.

You now have a product that people like and your job is to put it in front of as many such customers as possible.

This is also the time to start hiring your Sales and Marketing teams.

One of the disconnects we have noticed at this phase is the question we are trying to tackle today.

That of, “Am I spending enough, am I spending less, Am I spending a lot?” and how have others dealt with this in the past.

The answer to this problem is 2 fold.

You need to measure 2 metrics, your CAC Payback as well as your LTV/CAC to make sense of how your scaling engine is performing.

CAC Payback

Your CAC Payback is essentially how long it takes you to make your sales and marketing dollars back.

The infographic below by Openview is quite interesting. Your CAC Payback (we will get into the definition later in the piece), is not a fixed number. It keeps shifting depending on your scale.

This is an oversimplification but the reason the $1-$2.5M CAC Payback is considerably lower than the rest of the periods was that this is a pre-scale metric. Once the “PSF!” is achieved in some manner, it’s time to go acquire customers.

This however should not be taken in isolation. It’s important to tie this up with the next metric.

LTV/CAC

This will give you how valuable the customer is.

Lifetime Value of the Customer(LTV) is important because, if you have a high LTV, you have the runway to go spend more on acquiring customers (CAC). And on the other side of the coin is making sure that you aren’t spending more than what you will make from the customer.

LTV is a tough figure to capture in the early stages. Especially in cases where you’ve gone through a major pivot recently, or your product is less than a year old, or if you’ve signed multi-year contracts.

But I would say that in these stages, it is key to measure your dropoff rates as granularly as possible. Examples of this would be, such as dropoff after onboarding, dropoff at the monthly billing cycles, and dropoff because of product issues. As this will give you signs of what your LTV would look like.

The reason both these metrics should be used together is that they form 2 critical parts of your scaling engine.

• CAC Payback: Represents the cash efficiency of spend to acquire these customers

• LTV / CAC: Represents the margin efficiency of an investment to acquire customers (ROI)

High cash efficiency is where you invest your S&M dollars, make back what you first invested, and reinvest them quickly into acquiring new customers.

On the other hand, high margin efficiency means that each dollar of investment will pay back multiples in the future.

A well-calibrated machine has the ability to create a flywheel of exponential growth. The goal is to align the dollars you spent in the past to generate the sales (ARR) you are seeing today. These should be tracked as granularly as possible, by channels, ICP, end-user industry, etc. Whenever relevant.

Let’s move on to how you should be calculating this.

Here, I’ll mostly reference Mostly Metrics, since he had written about this with all the nuance required.

CAC

Previous period S&M Expenses/Current Period New Customers

LTV

Average Annual Revenue per Account * Gross Margin / % Average Account Churn Rate

CAC Payback

(Previous Period’s S&M expenses* 12 (Depending on time period used)) / (Current Period’s New ARR * GM)

Definitions

• The idea for different time periods is given below but simply it varies according to your sales cycle (you would use the current period’s addition of new customers but the time period of S&M expenses would depend on your sales cycles)

  • Previous Period — Examples of lagging by segment

    • Enterprise sales cycle of 180 days = 2 quarter S&M lag

    • Mid-Market sales cycle of 90 days = 1 quarter S&M lag

    • SMB sales cycle of 30 days = 0 quarter S&M lag

• New ARR — New recurring revenue added in the particular period

• S&M Expenses — All sales and marketing expenses including Sale team payroll, Marketing payroll, Customer success payroll, Sales Software, Rev ops and Sales enablement, and trial costs. In some cases, things like non-cash stock-based compensation aren’t added. However, they should be for accuracy.

• New Customers — New customers added in the particular period.

• Average ARPA — Average of your annual revenues across customers

• Gross Margin — Variable expenses here include hosting costs, customer costs, etc.

• Average Account Churn Rate — Inverse of your average account retention rate, measured on an account basis

This is a good time to look at the below figure and see how some public companies have executed on these metrics.

Note: I have used S&M expenses here (Since LTV/CAC is not disclosed generally) but will go into this as well as LTV/CAC below.

Source: Clouded Judgement

This infographic is interesting but a nuance they are unable to capture is that generally, you’d see lower payback periods for SMB software compared to Enterprise software.

There’s structural churn embedded in an SMB business, with a higher % of companies going out of business, and companies doing well needing more calibrated software to suit their needs. Meanwhile, in the case of enterprise companies, the cost of setting up, from procurement practices, to customization, etc. means that the opportunity cost to switch software is much higher.

Examples

Now, we’ve gone through the what to track and how to track, let’s quickly touch on some qualitative examples of successes and the path they picked.

Veeva (Enterprise — Low Payback and low S&M expenses)

Lifesciences cloud

• Efficiency had been ingrained in Veeva’s history. Founded in 2007, they raised $3M in an angel round and a $4M seed, which interestingly wasn’t even used. They used Angel money to build the platform and the rest of the growth was funded by their customers

• IPO’ed in 2013 and today, at a scale of over ~1000 customers and a $30B Market Cap, it has a CAC payback of 8 months while spending only 17% on S&M expenses. Selling to enterprise meant that their first Customer came with a $3M ACV contract

💡 In Veeva’s case, they were selling solely to life sciences companies. Since it was a limited set of companies, their sales efficiency was quite historic. Even today, their biggest 100 customers make up the bulk of their revenues.

Snowflake (Enterprise — Low Payback and High S&M expenses)

Data Warehouse

• Snowflake raised $2.1B in overall funding and has spent heavily on its sales and marketing engine with S&M expenses of 61% (of total revenues) in FY21 down from 81% in FY20

• Even with this scale of spending, their CAC Payback comes to 14 Months

💡 With their metrics, the annual growth rate of 91% with a 170% NRR, it makes sense for them to spend as much as they can to acquire customers

Zoominfo (SMB — Low Payback and Low S&M expenses)

Sales Intelligence

• Zoominfo had efficiency ingrained in its DNA with the way it started. The founders, Henry Schuck and Kirk Brown started with 50k credit card expenses and took no funding for 7 years till they hit $25M ARR

• At the time of their MVP, they had information for 10,000 people on the platform. Today they are at 130M with revenues higher than $600M

💡 They have carried their sales efficiency from the beginning and to date, their CAC Payback is ~6-10 months. They also do this along with very short sales cycles which allows them to get started immediately — Sometimes it’s within a day

Hubspot (SMB — High Payback and high S&M expenses)

Marketing Automation

• Going through these learnings helped them increase their LTV to 52k from 25k while keeping the CAC around the same $10-11k. This enabled them switch on the scale engine

• I wanted to highlight an interesting point in time for Hubspot. The below excerpt is taken from an article by the CEO of Hubspot where he went into the scaling issues they faced in their journey (would highly recommend reading it!). The Mary Decision — Link

💡 Today, Hubspot is growing faster at a $1.7B ARR than it was last year at a $1B ARR. 41% against 32%. Their high S&M allows them to get 50% of all new revenues from new customers, all while setting up a strong cross-sell engine with 50% of New Upmarket Customers using 2+ Products.

Let’s move on to some benchmarks

On CAC Payback

In the early stages, a 5-15 month payback period seems like a good band to be in, depending on your end-user category and the industry you operate in.

Below are data points by a few VCs that point towards the same figures.

1. Bessemer puts CAC payback in the $1-$10M stages at 15 Months. This increases to 20-25 months in the $10-$100M stages and curiously 30 Months at a >$100M scale.

2. Openview, on the other hand, breaks this down even further. Top Quartile performance for companies in the range of $1-$2.5M is 5 Months, going to 8 Months for companies in the $1.5M-$10M scale. This is ~15-20 Months for companies between revenues of $10M→$50M.

3. Craft Ventures, during the May ‘22 market crash, put great CAC payback at 6-12 months, good at 12-18 months, and anything over 24 in the Danger Zone.

On LTV/CAC

As for LTV/CAC, good would be above 4x — 1x CAC, 1x-2x in your G&A and R&D, and the rest as free cash flow to reinvest in your scaling engine.

Another thing to keep in mind is tracking cohorts — Growing customer LTV → Good sign. Reducing customer LTV → Not a good sign.

Capchase, in an analysis of 439 private SaaS companies with $1 - 15m Annual Recurring Revenue put top quartile LTV/CAC in companies in the range of $1M-$3M at 4x, for companies between $3M-$5M at 3.5x, $5M-$10M at 4.5x and for companies in the $10M-$15M range at 6x.

I’d say anywhere between 4x to 10x is great performance with additional context coming from your CAC Payback periods.

Also, beware of very high LTV/CAC. A high LTV/CAC (double digits) is great for maturing companies, however, at earlier stages, it always makes sense to spend a part of that future LTV into ramping up growth.

Conclusion

Your payback period and LTV indicate the health of your GTM engine — they need to be measured together.

However, a nuance I’d like to add here goes back to the $1M-$5-10M journeys. A low CAC Payback allows you to fund your growth through customer revenues whereas a high CAC Payback will push you toward growth through VC dollars.

Neither situations are right nor wrong, but you have to find your path or take the path available to you. This is the point I wanted to highlight with the examples of Veeva, Zoominfo, Snowflake, and Hubspot.

In my experience, if you don’t have this thought process in place, there’s a chance you can get swayed by people giving very generic advice like “keep your CAC low”, or “it’s time to blitzscale”. These statements in themselves, while having some value, are meaningless. It also does not make any sense to track metrics like CAC any earlier than this.

You can also reduce CAC Payback by upselling better, increasing your sales funnel conversion, and/or adding “PLG” to your software (we’ll get to this at a later point).

Finally, I’d like to understand if this was helpful in any way in thinking about how to set up your scaling engine.

Feel free to reach out to me or my colleagues if you are building B2B Tech for Global Markets.

There’s no one answer to this, and anything anyone says must be caveated with what’s the basis of that point of view.

However, this isn’t to say that this question is not meaningful at all. It is. And through some frameworks, I will try to show that.

To me, this question comes down to the trajectory you sign up for, if you take on venture capital. If you want to take it to venture-level success (IPO), then we can backtrack to see what we should benchmark against at any stage of the journey.

The truth is, when you take venture money for your business, you get into the game. The game of velocity. And to be in the game, you have to play by some of the game’s rules.

This infographic by Bain shows the number of startups that go on to raise a follow on round of funding. We can see that even after each level of market feedback, the ratio of success while moving up stages doesn’t grow meaningfully. At every stage, less than half of your cohort will be able to raise their next round of capital.

This means that, at every stage, your business has to stack up favorably against others in terms of performance.

There are approximately 150-200 SaaS startups doing between $1M-$10M ARR in India. This piece should broadly apply to them. However, the intention of writing this piece is just to get the perspective out and not be prescriptive. This can be used as a general framework to keep in mind, with a few caveats at the end.

I will cover ARR growth here and I’ll be following this up with posts in the next month to go into more detail on other metrics and segments. So, let’s get to this.

Why Growth?

We’ll first qualify the question of why ARR Growth is the most important metric, to begin with.

For this, we go to what success looks like for a venture-backed startup — growing to IPO scale. Of course, there are multiple roads to success, but let’s stick with this one for the sake of simplicity.

This is what a US SaaS company at IPO looked like over the last 5 years. (Source: Clouded Judgement)

• $200M ARR (minimum $100M)

• 90% of revenue derived from subscriptions

• 50%+ YoY ARR growth

• $18M of net new ARR in the quarter you go public

• 72% gross margins

• 121% net dollar retention

• 25 months gross margin adjusted CAC payback

• (31%) LTM operating margin

You’d now come back and tell me that wait there are so many metrics here, so which one is it? Which one should I prioritize today?

Well, one data point comes from Guggenheim Securities. This puts the relative importance of Revenue Growth towards Valuations at 2x when compared to FCF margin growth.

This should establish the fact that ARR Growth is one of the critical indicators of growth in valuations.

This takes us nicely to the next question. Let’s say you have started growing.

Now, what’s a growth metric to target?

Let’s go back to what success looks like. IPO scale.

The minimum revenue number you need to get to is $100M. So how quickly do you need to get to it?

One of the ways of looking at this is the Mendoza line (a coinage from baseball, more info here).

This will give us a baseline for what is generally considered venture backable. This benchmark would largely be relevant at every point, although the linearity and consistency of the ARR growth are less important.

So, we can set the baseline of ARR growth in a less than $10M stage to grow 125%+ to be venture-backable. This would take a company to the $100M mark in 9 years. And while this might seem like exceptional performance, there have been companies like Workday, who at the time of their IPO was doing ~$250m in ARR while still growing ~90%.

Having gone through the lower end of the venture backable growth spectrum, let’s see how this looks for the leaders.

Another common heuristic is the Triple, Triple, Double, Double, Double. Tripling your revenues the first 2 years, and then doubling every year for 3 years.

If you start at $1.5M ARR, this will take you to $4.5M in the first year, $13.5M in year 2, $27M in year 3, $54M in year 4, and $108M in year 5. While this sounds very mathematical, the infographic below shows a whole host of top-of-the-line SaaS companies that have achieved this.

We have covered the top and the average ARR growth rates that you as a founder should benchmark against.

Another point of view on the ARR Growth rate would be to look at this every month. If you are growing 8% MoM, you are hitting a 150% YoY growth rate. at ~12% MoM growth, you are at 3x of your last year’s ARR.

All this is largely backed up by some of the metrics from VC funds like Craft Ventures and Bessemer Venture Partners for the US and India.

According to Bessemer, you are amongst the best of the crop in India if you are growing at >150%, while 100%-150% ARR Growth puts you in the range right below that.

Comparing this to what Craft Ventures put out for US-based SaaS companies, 300% ARR Growth is what they look at to be top of the line while 250% would be in the range right below that.

Note: Top-of-the-line Indian ARR growth rates are lower than their US peers. Interestingly, this doesn’t necessarily have much relevance to the quality, as I will touch on when we look at other metrics in the coming weeks.

So as an answer to how fast you should be growing, we’d say 8-10% MoM will keep you in the “default investable” category.

If you are below 6% MoM growth or below ~100% YoY growth, it’s time to go back to the drawing board to see where things can be improved.

One major caveat here is that these numbers and figures that we have looked at today aren’t going to be meaningful to everyone — These are applicable very strongly once you have a level of repeatability in your business model when you have a product in place and have figured out an early sales motion. However, pre-PMF (product-market-fit, described here by Marc Andreessen), you can use these frameworks to understand if your current traction is good enough or not.

With this piece, I hope you take away some of the heuristics to keep in mind when it comes to ARR growth. Especially when you are transitioning from your founder-led sales to adding resources to your sales and marketing engine.

Over the next few weeks, I am going to follow this up with more metrics that you should track and know where you stand. I would also love to hear from you if you have started looking into benchmarking where you stand today or if there’s something adjacent to this you’d like for me to cover.

And if you are building B2B SaaS or Enterprise Tech from India for Global Markets, I’d love to hear from you!