SaaS Business Models

💥 The EU just killed multi-year SaaS deals (and your revenue model) The EU Data Act has has given customers unprecedented power to walk away from any subscription with just two months' notice. Microsoft, Zoom, Slack, Adobe—every SaaS provider selling into Europe now faces the same reality. Here's what every SaaS vendor needs to know: 𝐌𝐚𝐧𝐝𝐚𝐭𝐨𝐫𝐲 𝐜𝐨𝐧𝐭𝐫𝐚𝐜𝐭 𝐩𝐫𝐨𝐯𝐢𝐬𝐢𝐨𝐧𝐬 ✅ Customer termination for convenience with max 2 months' notice (applies to ALL deals, including multi-year) ✅ Detailed data export procedures and supported formats ✅ Clear migration assistance commitments and timelines ✅ Transparent fee disclosure (early termination penalties must be "proportionate") ✅ Data collection, usage, and retention schedule transparency ✅ Technical specifications for data portability and interoperability 𝐑𝐞𝐦𝐨𝐯𝐞 𝐟𝐫𝐨𝐦 𝐲𝐨𝐮𝐫 𝐭𝐞𝐦𝐩𝐥𝐚𝐭𝐞𝐬 ❌ Minimum term enforcement clauses ❌ Auto-renewal without easy exit ❌ Excessive early termination fees ❌ Switching fees (phasing out completely by Jan 2027) ❌ Unilateral contract modification rights ❌ Data access restrictions or lock-in mechanisms 𝐊𝐞𝐲 𝐯𝐞𝐧𝐝𝐨𝐫 𝐜𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐠𝐨𝐢𝐧𝐠 𝐟𝐨𝐫𝐰𝐚𝐫𝐝 - Multi-year deals → effectively month-to-month. Retention must come from value, not contracts. - Invest in APIs, export tools, and migration support — now both a legal requirement and a competitive differentiator. - Quotas based on long-term commitments are obsolete. Shift to usage-based or value-delivered metrics. - Customer Success becomes your frontline for revenue protection. Contracts won’t stop churn. - Explore usage-based or outcome-based pricing tied to delivered value, not time. Bottom line? Customer-centric SaaS wins; vendor lock-in loses. Build products customers choose to keep, not contracts they're forced to honor.

7 Cloud Migration Strategies Every Cloud Engineer Should Know (with scenario questions for interviews) Cloud migration can originate from on-premises infrastructure or from another cloud provider. And it goes beyond just moving data. It's about strategically deciding the best approach for each application and workload. The goal is to optimize performance, cost, and long-term viability in the cloud. Here’s a simple breakdown of the key strategies you should focus on: 1/ Retain (Revisit later) ↳ Keep workloads on-prem if they aren’t cloud-ready or are still needed locally. Scenario : You have a critical legacy application with custom hardware dependencies. How would you initially approach its cloud migration? 2/ Retire (Decommission) ↳ Eliminate outdated or unused parts to reduce cost and simplify the system. Scenario : During an assessment, you identify an old reporting tool used by only a few employees once a month. What's your recommendation? 3/ Repurchase (Drop & Shop) ↳ Replace legacy apps with SaaS alternatives, a fast and cost-effective solution. Scenario : Your company's on-premise CRM system (example) is outdated and costly to maintain. What quick cloud solution might you consider? 4/ Rehost (Lift & Shift) ↳ Move your application to the cloud as-is, with no code changes needed. Scenario : A non-critical internal application needs to move to the cloud quickly with minimal disruption. What strategy would you prioritize? 5/ Replatform (Lift, Tinker & Shift) ↳ Make light optimizations before migration, for better performance with minimal effort. Scenario : You're migrating a web application, and a small change to its database will significantly improve cloud performance. What strategy does this align with? 6/ Relocate (Many Providers) ↳ Change the hosting provider without modifying the app, a quick and simple approach. Scenario : Your current cloud provider is increasing prices significantly for a specific set of VMs. How might you address this without rewriting applications? 7/ Refactor (Re-architect) ↳ Redesign your application for cloud-native capabilities, making it scalable and future-ready. Scenario : A monolithic, highly scalable customer-facing application is experiencing performance bottlenecks on-prem. What long-term cloud strategy would you propose?. Beyond these strategies themselves, successful cloud migration also focuses on: - thorough assessment, - understanding dependencies, - meticulous planning, - and continuous optimization Just remember: successful migration isn't just about the tools, but the approach. Very important to understands the "why" behind each strategy — not just the "how." Dropping a newsletter this Thursday with detailed scenario based questions (and example answers) for each of these patterns — subscribe now to get it -> https://lnkd.in/dBNJPv9U • • • If you found this useful.. 🔔 Follow me (Vishakha) for more Cloud & DevOps insights ♻️ Share so others can learn as well

We're moving away from charging for *access* to software and toward charging for the *work delivered* by software & AI agents. Don't freak out: this doesn't mean everything will become *pay-as-you-go* overnight. I can think of 7 flavors of charging for work: 1️⃣ Pay-as-you-go - No commitment, totally flexible - Enterprise procurement teams usually *hate* this! - Works best when your customers can bill-back the expense or bake it into an operating budget - Otherwise, there's a risk of customers policing their own usage (taximeter effect) 2️⃣ Subscription + pay-as-you-go - Small level of commitment helps 'lock customers in' and give them access to advanced features, support, etc. - Works well when the usage metric is getting commoditized (ex: SMS messages, compute, storage) -- you can advertise a low usage fee & make up for it with the subscription fee - Still not quite loved by enterprise procurement since their bill isn't predictable yet now includes multiple line items... 3️⃣ Three-part tariff (usage subscription + PAYG) - Similar to the above, but with a larger subscription fee that includes some level of usage "included" - Folks usually advertise the initial usage as a gift ("get your first 500 SMS messages for free!") - Including a minimum level of usage helps get the customer hooked & usually incentivizes more overall consumption 4️⃣ Usage-based subscription (high watermark) - Customers commit to a certain level of usage or tier (ex: up to 5,000 API calls per month); this is typically "use it or lose it" - Subscriptions are for a high watermark of usage -- if usage exceeds the plan in a given month, they immediate move into upgrade territory - Fear of overages + usage fluctuations encourages sales to over-sell & customers to over-buy 5️⃣ Usage-based subscription (annual drawdown) - Similar to the above, but the usage allocation can be consumed flexibly over the course of 12 months similar to a gift card - This gives the customer plenty of time to monitor adoption & plan for an early renewal/upgrade if usage is trending above their commit - Great for customers with seasonality or month-to-month usage fluctuations who still want a predictable bill 6️⃣ Roll-overs - If the customer doesn't consume their full allocation, they can "roll it over" to the next year -- typically only if they commit to a flat or increased renewal - More customer friendly, but also more painful to manage! 7️⃣ Adaptive flat rate - The customer commits to a usage-based subscription, but can use the product as much as they want with no overages/upgrades during that period - Their tier resets up/down at renewal based on their actual usage behavior - Much more predictable for customers while encouraging them to increase consumption (downside is that you could be stuck with the costs!) -- I suspect most folks will offer multiple options as they seek to balance lands, expands & tough procurement convos. The downside: complexity.

Reflecting on Agile Development with DevOps 2.0: A Flexible CI/CD Flow Last year, I shared a CI/CD process flow for Agile Development with DevOps 2.0, and it’s been amazing to see how much it resonated with the community! This framework isn’t about specific tools—it’s about creating a seamless, collaborative process that supports quality and agility at every step. ✅ 𝗣𝗹𝗮𝗻: Building a Strong Foundation with Clear Alignment The journey begins with planning—whether it's user stories, tasks, or broader product goals. Tools like JIRA or Asana (or any project management platform) help capture requirements and align the team with the Product Owner’s vision. This early alignment is essential to avoid misunderstandings and establish a shared understanding of success. Key Insight: Planning thoroughly and involving stakeholders from the start leads to a smoother process. When everyone’s on the same page, the entire pipeline benefits. ✅ 𝗖𝗼𝗱𝗲: Collaborative Development and Real-Time Feedback In the coding phase, developers work together, often pushing code to a version control platform like GitHub or Bitbucket and communicating via real-time collaboration tools like Slack or Teams. Open communication and continuous feedback help catch issues early and keep the team in sync. Key Insight: Real-time feedback is crucial for speed and quality. Regardless of the tools, creating a culture of continuous collaboration makes all the difference. ✅ 𝗕𝘂𝗶𝗹𝗱: Automating Quality and Security Checks As code is committed, it’s essential to automate quality and security checks. Tools like Jenkins, CircleCI, or any CI/CD platform can trigger builds and run automated tests, ensuring that quality checks are consistent and fast. This step helps prevent issues from creeping into production. Key Insight: Automated checks for quality and security are invaluable. Integrating these checks into the build process improves confidence in every deployment. ✅ 𝗧𝗲𝘀𝘁: Structured, Multi-Environment Testing Testing is layered across environments—whether it’s regression, unit, or user acceptance testing (UAT). Using frameworks like Selenium for automated testing or dedicated QA/UAT environments enables rigorous validation before production. Key Insight: Testing across environments is a safeguard for quality. Structured testing helps ensure that code is reliable and ready for release. ✅ 𝗥𝗲𝗹𝗲𝗮𝘀𝗲: Scalable, Reliable Deployments with Infrastructure as Code (IAC) Finally, using Infrastructure as Code (IAC) principles with tools like Terraform, Ansible, or other IAC solutions, deployments are made repeatable and scalable. IAC empowers teams to manage infrastructure more efficiently, ensuring consistent and controlled releases. Thank you to everyone who has engaged with this diagram and shared your insights! I’d love to hear how others approach CI/CD. Are there any tools or strategies that have worked well for you?

As a veteran SaaS lawyer, I've watched Data Processing Agreements (DPAs) evolve from afterthoughts to deal-breakers. Let's dive into why they're now non-negotiable and what you need to know: A) DPA Essentials Often Overlooked: -Subprocessor Management: DPAs should detail how and when clients are notified of new subprocessors. This isn't just courteous - it's often legally required. -Cross-Border Transfers: Post-Schrems II, mechanisms for lawful data transfers are crucial. Standard Contractual Clauses aren't a silver bullet anymore. -Data Minimization: Concrete steps to ensure only necessary data is processed. Vague promises don't cut it. -Audit Rights: Specific procedures for controller-initiated audits. Without these, you're flying blind on compliance. -Breach Notification: Clear timelines and processes for reporting data breaches. Every minute counts in a crisis. B) Why Cookie-Cutter DPAs Fall Short: -Industry-Specific Risks: Healthcare DPAs need HIPAA provisions; fintech needs PCI-DSS compliance clauses. One size does not fit all. -AI/ML Considerations: Special clauses for automated decision-making and profiling are essential as AI becomes ubiquitous. -IoT Challenges: Addressing data collection from connected devices. The 'Internet of Things' is a privacy minefield. -Data Portability: Clear processes for returning data in usable formats post-termination. Don't let your data become a hostage. -Privacy by Design: Embedding privacy considerations into every aspect of data processing. It's not just good practice - it's the law. In 2024, with GDPR fines hitting €1.4 billion, generic DPAs are a liability, not a safeguard. As AI and IoT reshape data landscapes, DPAs must evolve beyond checkbox exercises to become strategic tools. Remember, in the fast-paced tech industry, knowledge of these agreements isn't just useful – it's essential. They're not just legal documents – they're the foundation for innovation and collaboration in our digital age. Pro tip: Review your DPAs quarterly. The data world moves fast - your agreements should keep pace. Pay special attention to changes in data protection laws, new technologies you're adopting, and shifts in your data processing activities. Clear, well-structured DPAs prevent disputes and protect all parties' interests. What's the trickiest DPA clause you've negotiated? Share your war stories below. #legaltech #innovation #law #business #learning

Today, B2B SaaS products perform impressively in isolation, providing functionality, efficiency and productivity gains. But they don’t play well with others. Vendors know they need to offer a wide set of native integrations, but that’s getting harder to achieve. As the B2B tech stack swells (the average business uses 371 SaaS apps), the number of integrations vendors need to build is skyrocketing. In the coming decade, this problem will increase even further as B2B software will operate across thousands of highly specialized applications. These systems won’t just coexist, they’ll need to interoperate in real time, across dynamic, evolving workflows. Current SaaS architectures struggle with integration complexity. Fragmented stacks, ad hoc APIs, and manual workarounds introduce bottlenecks at scale. To fully unlock the value of SaaS, vendors require infrastructure that abstracts the burden of bespoke integration development. Legacy solutions fall short: Embedded iPaaS enables point-to-point connectivity but lacks scalability and maintainability. Unified APIs offer abstraction, but constrain customization and depth of integration due to rigid schemas. What’s needed is a universal, API-agnostic integration layer, one that enables composable, reusable logic across heterogeneous systems at scale with hundreds of apps. At Integration App, we’re building exactly that. Our platform introduces a standardized integration framework that decouples integration logic from underlying APIs. Using AI, we generate adaptive, app- and tenant-specific implementations, allowing developers to build complex, multi-surface integrations with minimal overhead. This architecture dramatically reduces time-to-integration, supports scalable extensibility, and aligns with modern expectations for one-click deployments and dynamic orchestration. SaaS value is shifting from standalone features to ecosystem interoperability. The next generation of platforms will be defined by how well they connect.

Subscription commerce failed in India for a decade. Now it's working. Why? I remember 2016. Every other pitch deck had "subscription box" on it. Fab Bag, beauty boxes, meal kits - everyone wanted to build India’s Dollar Shave Club. By 2020, most were gone. My Ayurveda brand tried too, even with 6–9 month purchase cycles, it didn’t work. Cut to today, a very different picture.I recently spoke to 3 founders running subscription businesses. All launched post-2022. All profitable. One doing ₹50-1000 Cr+ ARR with 65% retention at month 6. That got my attention. So I spent the last few days digging into why it's suddenly working. Why did FAB BAG, Doctalk, Doodhwala, Otipy fail but today's winners are killing it? The answer came down to two words: UPI AutoPay. The successes: → Kuku FM: >12 M+ paying subscribers for regional audio-video content (our first investment at @V3 Ventures India) → Country Delight: Daily milk delivery via subscription, does ₹600+ Cr in revenue → Wholsum Foods (Slurrp Farm and Mille): Kids nutrition products on weekly/bi-weekly subscription. Parents don't want surprises, they want the same healthy millet cookies delivered automatically. Aisha is a big customer → Licious: Meat subscription component growing fast. You pick your cuts, they deliver weekly What changed? 1. UPI solved the payment problem: 131 billion UPI transactions in 2023. Auto-debit on UPI is now seamless. It had a lot of friction in the past. This has led to what one founder told me: "COD customers churn at 40%. UPI auto-debit customers churn at 12%. Payment method is the business model." 2. Q-Com also proved daily delivery is possible: When Zepto can deliver groceries in 10 minutes, milk every morning doesn’t sound crazy anymore. Cold chain, reliability, last-mile ops - all the boring things finally clicked. 3. Model Shift: Replenishment > Discovery, Subscription in India isn't about trying new things. It's about auto-delivering stuff you already buy by removing friction & making customers loyal. Indians now buy the same atta, same milk brand, same baby food every week. Subscriptions just automate what we'd do anyway - with a small discount as incentive. So, what works is obvious now Category: Consumables (milk, eggs, baby food, meat)  Frequency: Weekly/bi-weekly (monthly too long)  Discount: 5-15% ( like Country Delight’s early-bird plans)  Flexibility: Easy skip/cancel (trust builder)  Payment: UPI auto-debit (not COD) After a decade of failed experiments, subscription commerce has finally found its moment in India and it looks nothing like the US playbook. The brands that understand this will build annuity businesses in categories everyone else is fighting for one transaction at a time. The question: there’s been talk of consumers forgetting their upi auto pay subscriptions. Will this be regulated/some friction be added?

New research alert: From GenAI to agents: the $267 billion AI opportunity for partners by 2030. The evolution of AI, from instruction-dependent generative functions to autonomous, agentic capabilities, is shifting business models and rewriting the rules of engagement for partners. The shift from experimental use cases to embedded, strategic business integration presents a generational opportunity for vendors, partners, and customers. While reports from the Massachusetts Institute of Technology are showing 95% failure rates (after talking to only 52 people and using a 6-month timeline), smart technology services companies are investing heavily in the next 20-year era of our industry. Vendors are pivoting as well; agentic AI is now at the core of their long-term product and business strategies, with hyperscalers and ISVs reshaping their partner programs, incentives, and co-creation models to support it. Simultaneously, customers are rapidly prioritizing agentic AI initiatives, making specialized expertise from partners essential for designing, building, training, integrating, governing, securing, and optimizing these intelligent systems.   From cloud marketplaces to agent ecosystems, every touchpoint across the industry is being recalibrated. For partners, this means moving beyond project-by-project delivery and into repeatable IP, agent development frameworks, and hyper-specialized vertical capabilities with new, value-based packaging and services. Agentic AI is evolving as a partner-delivered service; the partners that lean in will capture long-term relevance and value, and those that wait risk marginalization in an increasingly agent-driven market. The $267 billion services opportunity is growing at 35.3% CAGR, making it one of the largest partner opportunities in the next 3-5 years timeframe. This report by Lisa L., myself, and the team at Omdia explores the partner ecosystem approach of AI leaders such as Microsoft, Amazon Web Services (AWS), Google Cloud, Salesforce, ServiceNow, IBM, and Oracle. We also dive into key moves by data companies Snowflake and Databricks, as well business software leaders including SAP, Adobe, Workday, and HubSpot. There are significant programmatic, pricing, and packaging implications for channel partners as well - with new compensation models, value-based selling, and different levels of certifications and competencies. Pricing will move to micro-consumption models and delivered based on outcomes, consumption-plus models, subscriptions, managed services, IP monetization, and hybrid. By measuring the number of billion-dollar partners we knew what success was in the 20-year client-server and 20-year cloud eras. What will be the secret sauce for the AI era?

How do you *actually* create a product roadmap? Try this. Any product leader knows that deciding what to build, and when to build it, is an art form. How do you balance the needs of customers with the resources of your engineers? How do you coordinate what your sales team wants with what YOU - as a business - need? It's not easy. But it starts with ... The Four Lists List 1: What your customers want Start by listing out the kinds of customers who already use your product and what's important for them. As new users become power users over time, they start finding gaps in the product and begin asking for different capabilities. If you don’t listen and demonstrate an ability to offer those features that they need, those customers become dissatisfied and are less likely to renew. List 2: What your sales team want Are you losing deals because you're missing a feature that a competitor has? At Harness, we call these "opportunity gaps." This list enables you to close those gaps and helps sales win new customers.  List 3: What your engineers want Every startup will accumulate "technical debt" as they scale. If you don’t take care of it and only focus on building more features, eventually your product architecture gets so unwieldy that product quality suffers and it creates more serious problems in the long run. This list is all about taking the needs of your engineers into consideration.  List 4: What the vision of your product is This list rises above the nuts and bolts of the company and forces you to think about the bigger picture. What do you need to build to hit revenue goals? How do innovate in a way that expands your total addressable market?  One more note: it's critical that someone keeps track of all these lists. For example: at Harness, sales has a list of feature gaps, account managers keep track of customer requests, while engineers maintain their lists of technical debt, etc. Ultimately, these factors decide what you focus your resources on. A good product leader is constantly balancing the four lists and making conscious decisions to prioritize certain aspects depending on what the company needs. #PMF #ProductRoadmap #ProductManagement #Startup

SaaS finance cardinal rule: You must not fixate on a single metric. I've seen far too many founders and executives fixate on 1-2 metrics without context because a board member, investor, or blog said that its critical for growth, valuation, etc., etc. In the hypothetical example below, a SaaS company hits its annual bookings goal of $3m in combined New and Expansion ARR. And it does so efficiently with a CAC Payback Period of between 8-9 months and a blended CAC Ratio around .5. The issue is that this particular company exhibits a frustrating combination of Sales and Marketing prowess with poor retention. Zooming out and looking at the annualized churn rate, we can see that the company has a huge problem. And this issue shows up in another composite metric: The CAC to CLTV ratio. CLTV is an important metric. It's essentially the expected future cash flows from a single customer, and it's highly sensitive to churn rates. Because of this company's poor retention, the CAC to CLTV ratio is below 3 for most of the year (not good). Basically, this company is the classic leaky bucket. It's good at bringing in revenue but not keeping. Had we focused on the positive signals alone, (e.g., CAC Paypack Period), we would have missed the larger underlying issue. Now, what causes a company to have such a mixed profile. Two of the most common reasons I have seen: -Sales & Marketing prowess without product<>market fit. The team is good at selling to anyone and everyone, but is having a hard time delivering value. -Selling indiscriminately. Poor ICP discipline. The company may have a core of very happy customers, but there is no discipline around who we sell to. Peeling back customer data may reveal high retention in certain segments. THAT IS WHO YOU WANT TO SELL TO. Remember, it's essential to look at metrics in context rather than fixating on one or two in isolation. #saas #bootstrapping #founders #finance #startups #metrics