Setting Up An Ecommerce Subscription Model

We're moving away from charging for *access* to software and toward a model of charging for the *work delivered* by a combination of software and AI agents. Let’s dive into what’s happening and what it means for you ⤵️ 1. The rise of disruptive AI pricing models Tech companies are realizing they can't solely rely on seat-based subscriptions in an age of AI, automation and APIs where value is disconnected with how many people are logging in. Perhaps Salesforce going all-in on Agentforce (and charging $2 per conversation) was the push the industry needed. Each product category has its own flavor of disruptive pricing. - Legal AI products might charge for a demand package generated by AI or an AI-generated summary. - Creator AI products might charge for the content that gets produced such as a video generation or amount of video created. - GTM products might charge for specific tasks completed or workflows executed by the AI. 2. Selling work, not necessarily success As a customer, I wish I only had to pay for software when it delivered results. But the reality is that true success-based billing won’t work for the vast majority of today’s products. Most products should charge for work output instead. The issue is attribution. You want the customer to get a fantastic outcome — and you want them to recognize that your product powered that outcome. As soon as you start charging for success, the customer begins to rethink the results. 3. Goodbye ARR as we know it? Shifting to these newer value-based pricing models isn't a simple pricing change you can just announce in a press release. It's a business model evolution that looks a lot like the shift from on-prem to SaaS in the first place. These new AI pricing models might mean greater volatility in both usage and spend. Variable margin profiles across products and customers. Seasonal revenue fluctuations. The potential for project-based, non-recurring use cases. Put simply, annual recurring revenue (ARR) continues to get dethroned. — Full post in today’s Growth Unhinged newsletter: https://lnkd.in/ea5eTrVD Things are about to get interesting 🍿 #ai #pricing #saas

Salesforce just fired the starting gun on a seismic shift in how we pay for software. At Salesforce #Agentforce, they announced they’re moving away from the traditional per-seat SaaS model to a consumption-based pricing for their AI agents. This is huge. Why? Because it signals the end of paying just to have access to technology. Instead, we’re moving toward paying for outcomes—the actual value delivered. Think about it. In a world where AI agents can perform the job functions of entire departments, does it make sense to charge per seat? Probably not. Here’s what’s changing: - From access to outcomes: Companies will pay for what the AI actually accomplishes. - From subscriptions to value: Pricing adjusts based on usage and results. - From Software-as-a-Service to Agent-as-a-Service: Technology that collaborates with you as a partner This isn’t just a tweak in pricing—it’s a radical upending of commercial models for large SaaS companies. What does this mean for businesses? - Budgeting will evolve: Costs align directly with value received. - ROI becomes clearer: Easier to measure the direct impact of technology investments. - Greater flexibility: Scale usage up or down based on needs without worrying about seat counts. It’s an exciting time, but also a challenging one. Is every SaaS company ready to embrace a model where companies pay directly for the value they receive? At Uniti AI, we’ve been thinking along these lines. We price our AI agents based on the amount of work they do, not on how many seats a company has. I believe this is the future. What do you think? Is the per-seat model on its way out?

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?

Unlocking New Revenue Streams with SaaS Models A few years ago, I sat across from a startup founder who had built a brilliant product—an AI-powered analytics tool for eCommerce businesses. The problem? They were struggling to scale. Their high upfront costs and one-time licensing fees limited customer acquisition. “We have a great product, but revenue is unpredictable,” he admitted. I’ve seen this challenge time and again—companies with exceptional tech but outdated monetization models. That’s when I asked him, “Have you considered transitioning to SaaS?” Fast forward 18 months, and that same startup saw a 3x increase in revenue, higher customer retention, and expansion into global markets. That’s the power of Software-as-a-Service (SaaS). Why SaaS is Driving Business Growth The SaaS market is projected to reach $908 billion by 2030, growing at a CAGR of 18.7% (Fortune Business Insights). Businesses are increasingly moving away from traditional software licensing to subscription-based, cloud-enabled solutions, unlocking new revenue streams and market opportunities. At Devsinc, we’ve helped numerous clients transition to SaaS, and the benefits are clear: 1- Recurring Revenue Stability: Unlike one-time sales, SaaS provides predictable, subscription-based income. 2- Scalability: SaaS businesses grow exponentially with minimal incremental costs. 3- Global Reach: Cloud-based delivery removes geographic limitations. The Real Impact of SaaS: A Case Study One of our eCommerce clients, initially selling packaged software, struggled with declining sales. We helped them pivot to a SaaS-based model, offering monthly subscriptions and AI-driven customer insights. The results? A 42% increase in customer lifetime value and 60% higher user engagement. The Future of SaaS: AI, Verticalization, and Automation By 2026, 70% of software products will shift to SaaS-based models (Gartner). Emerging trends include: - AI-powered SaaS: Automating workflows and enhancing decision-making. - Industry-Specific SaaS: Tailored solutions for sectors like healthcare, fintech, and retail. - Usage-Based Pricing: Charging customers based on consumption, increasing flexibility. Building a Successful SaaS Business Transitioning to SaaS isn’t just about moving to the cloud—it’s about redefining how value is delivered. Companies that invest in customer-centric experiences, seamless onboarding, and continuous product evolution will lead the market. The conversation with that founder wasn’t just about switching business models—it was about embracing a new mindset. SaaS is more than software; it’s a strategy for sustained, scalable growth. For companies looking to unlock new revenue streams, the question isn’t whether to adopt SaaS—it’s how quickly they can adapt. The future belongs to those who can innovate, iterate, and deliver continuous value. Are you ready to make the shift? #SaaS #BusinessGrowth #RecurringRevenue #TechInnovation #DigitalTransformation

Replit's gross margins went from 36% to negative 14% in two months. Same product. Same pricing. Same team. The only thing that changed: they launched a more autonomous AI agent that consumed more LLM resources than their pricing covered. Traditional SaaS has 70-80% gross margins because one more subscriber costs almost nothing. AI products pay for compute on every prompt. Your best users are your most expensive users. That single fact breaks every pricing model designed for the SaaS era. I mapped pricing across the top 50 AI startups by valuation with Moe Ali. Six patterns emerged. The scariest finding: in most AI products, the P90 user costs 10-40x more than the P50 user. Both pay the same subscription. You're subsidizing your heaviest users with revenue from your lightest ones. And that subsidy grows as power users discover more ways to use the product. Cursor learned this the hard way. They switched from flat 500 requests/month to a credit pool system. A developer burned the entire monthly allocation in a single day. $7,225 invoice. The CEO published a public apology on July 4th. The plan description quietly changed from "Unlimited" to "Extended" twelve days after launch. Anthropic took a different approach. Their $17/$100/$200 tiers map to genuinely different user personas. A casual user, a power user, and a developer replacing an IDE. Those are different products with different willingness to pay. Then weekly rate limits targeting less than 5% of subscribers to push the heaviest users toward the API, where per-token pricing covers actual compute. The pattern across all 50 companies: pure flat pricing is dying. Nearly half use two or three models simultaneously. Here's the full breakdown: 1. Complete AI pricing guide: https://lnkd.in/gdKaQSMk 2. Replit guide: https://lnkd.in/gmA_c_AG 3. AI product strategy: https://lnkd.in/egemMhMF 4. AI agents guide for PMs: https://lnkd.in/eeey5Cxr If you can't estimate your cost distribution across P10 to P90, you're not ready to set a price.

After sending over a billion emails for 600+ brands… here are my 7 top tips for selecting the right audience. You can have the best email creative in the world — but if it lands in the wrong inbox, it won’t convert. Audience is everything. Here’s what we’ve learned at esbconnect after years of powering customer acquisition for brands like Tails.com | B Corp , AA Insurance and ASOS.com : 1. Target by behaviour, not just demographics Look for people who open, click, and act. Intent beats age and gender every time. 2. But… don’t always go for the obvious behaviour When Tails.com wanted to reach new pet owners, you'd assume targeting people engaging with pet brands would outperform, right? Wrong. They were being over-targeted. Instead, we found higher conversion by targeting segments engaging with health, home and subscription offers — less crowded and more curious. 3. Test broad, then narrow Start wide to understand what actually performs — then double down. Too niche too soon and you lose scale and surprise wins. 4. Layer in recency Someone who interacted with an email yesterday is more likely to convert than someone who did 3 weeks ago. Recency = relevance. 5. Don’t ignore ‘non-buyers’ Sometimes your best audience is one that’s never bought from the category — yet. Think curious, not converted. 6. Think beyond income — target by contextual wealth We’ve seen clients waste budget by targeting £100k+ earners assuming they’re affluent. But some of the wealthiest people are those on modest incomes with low outgoings — think high equity, long-term property owners with few financial ties. 7. Make it locally relevant A £1m house in London doesn’t signal the same wealth as it does in Scotland or Wales. Tailor your audience selection to geography and cost of living — precision wins. Audience strategy isn’t guesswork. It’s data, nuance, and constant testing. Want help finding your best segments? We’ve got 17 million opted-in UK profiles and years of experience to test with.

A subscription is a tactic, not a strategy. It’s a delivery model, not the mission itself. The real strategy is delivering ongoing value that helps your subscribers reach their goals. Because when they win, retention takes care of itself. 1. Go deeper, not wider (at first) Before adding tiers, perks, or a new audience, go deeper with the members you already have. Ask: Are they consistently getting the outcome they came for? That means: ↳ Refining onboarding ↳ Measuring early wins ↳Closing the gap between sign-up and success Retention is a reflection of results. 2. The Access–Consumption–Performance test Every subscription should pass three checkpoints: • Access: Can members easily get what they paid for? • Consumption: Are they actually using it? • Performance: Are they seeing tangible benefits? If any one of these fails, you’ve got a churn risk. Subscribers stay for transformation, not transactions. 3. The ethics filter (yes, it matters) Don’t trap customers with hidden cancellations or manipulative billing cycles. That’s not strategy. It’s survival mode. A great subscription earns loyalty by delivering so much value that members want to stay. If they’d remain even when it’s easy to leave, you’re doing it right. 4. The pricing reality check Pricing is where many teams confuse tactics with strategy. Free trials, flash sales, and bundles work short term. But real strategy aligns pricing with long-term outcomes. Think: ✓ Sustainable for your business ✓ Fair for your customers ✓ Transparent to build trust Price for the relationship, not the renewal. 5. The bigger play nobody’s talking about AI discovery is changing the game. When someone asks ChatGPT for “the best membership for entrepreneurs” or “a trusted subscription in wellness,” it won’t pull the cheapest. It will surface the most cited, most consistent, most trusted brands. That’s why every video, post, and resource you publish matters. You’re training both your audience and the algorithms to see you as the go-to expert. That’s the 2026 play. 6. Redefine your content pulse Your content should reinforce three things: • The outcomes your subscribers achieve • The community and relationships you build • The values your brand lives by One clear strategy. One promise. One recurring result. Because subscription success isn’t about getting people to pay again. It’s about earning their continued belief that you’ll help them win. +++++++++++ 👋 I'm Robbie, I'm a consultant, author, and speaker covering all things subscription businesses. +++++++++++ 🛎 Tap the bell under the banner on my profile to catch the next post. ++++++++++++

Does AI have an unused growth lever hiding in plain sight? AI compute feels expensive. Users pay $20 to $200+ for access, and APIs charge by the token. But behind the scenes, inference costs are dropping, usage breakage is high, and scalable compute is becoming more abundant for many workloads. There’s a widening gap between what AI feels like it’s worth and what it actually costs to deliver. That’s an arbitrage opportunity. And while not exact, it looks a lot like what Dropbox pulled off in 2009. Remember: Dropbox gave away 250MB of storage for every referral. It felt huge, because hard drives were expensive. But it cost them almost nothing to incrementally add space on AWS. That’s the part everyone remembers. But what mattered more was that the product got better when more people used it. The storage unlocked shared folders, syncing, and collaboration. The referral loop wasn’t just about the incentive. It was about amplifying value through the network. Today, most AI platforms (ChatGPT, Claude, Gemini, Perplexity) give away compute too. They just do it through solo-player free tiers: – Limited speed – Smaller models – Capped usage – No shared context – No incentive to bring others in It’s a sampling strategy, not a viral engine. What if we built the Dropbox version for AI? A Better Model: Shared Compute, Shared Context, Shared Incentive Don’t just give away tokens. Pool them. Share them. Multiply them. Unlike disk space, people can't price a token, but they can price outcomes that matter. What if: You invite a teammate → your model remembers both your histories. Your group shares credits → your assistant becomes more capable. Your team grows → projects get done faster and better. Invites unlock more context, more memory, more speed—more wins for everyone in the workspace. Now you’re not just giving away compute. You’re giving away collaboration. Here's why this could work: Perceived Value → Tokens still feel scarce. Leverage that before the market catches up. Strategic Differentiation → Everyone else is playing the solo-player free tier. You’re building shared systems. Compounding Retention → Team-based tools stick longer. And grow faster. Product-Led Growth, Upgraded Sampling → Usage → Friction → Upgrade becomes Referral → Activation → Shared Value → Expansion Dropbox didn’t scale just because it gave away free megabytes. It scaled because it let people do something together they couldn’t do before—seamlessly. AI has the same opportunity. Maybe even bigger. How can we start thinking of compute not as a solo resource, but as a networked asset? The first company to build this loop could unlock something magical. Let me know if you're working on it.

Anthropic has quietly introduced the next AI pricing model. And most product leaders are going to miss it: Everybody saw the launch of Claude Fable 5 - the most powerful public model from Anthropic. But here’s the detail most people missed: Fable 5 is only included in Claude subscription plans until June 22. After that, access becomes usage-based. Not just, “Pay $20/month and get the best model with limits.” More like, “You can access the frontier model, but intelligence is now metered.” That tiny pricing detail is a massive signal. Because this is where AI pricing is going. The future might not be: Free plan Pro plan Team plan Enterprise plan The future will be: Basic intelligence included Advanced intelligence metered Frontier intelligence priced separately Specialized intelligence gated by use case High-risk intelligence controlled by policy Enterprise intelligence sold with governance, security, and SLAs This is a very different world. For the last decade, SaaS pricing was mostly about access to software. Seats. Features. Workspaces. Storage. Dashboards. But AI pricing is about access to cognition: - How much reasoning do you need? - How long should the model think? - How expensive is the task? - How sensitive is the domain? - How much context does it need? - How many tool calls will it make? - How many mistakes can you afford? That means the best AI product leaders will stop thinking only in terms of “plans.” They’ll start thinking in terms of intelligence economics. Because not every user needs the best model all the time. A support ticket does not need the same intelligence as a legal contract review. A simple SQL query does not need the same intelligence as a multi-step strategic analysis. And countless examples like these. So this is the shift: AI products will not be priced by software access. They will price by cognitive value delivered. And this creates a new product strategy question: - Where do you give intelligence away - Where do you meter it? - Where do you gate it? - Where do you downgrade it? - Where do you route to cheaper models - Where do you charge a premium because the outcome is worth it? This is why product leaders need to understand token economics, model routing, latency, evals, cost controls, and reasoning depth. Because pricing is no longer just a packaging decision. It is now an architecture decision because: 1. Your pricing model will depend on your model stack. 2. Your margins will depend on your routing system. 3. Your customer experience will depend on when you use cheap models vs frontier models. 4. Your competitive advantage will depend on whether you can deliver useful intelligence at the right cost. >>> Check out #1 AI PM Certification where you can learn all this from frontier AI leaders ($500 off): https://lnkd.in/eR8t7CMf

Email frequency matters more than most marketers assume. An analysis of 53,000 emails and 5,300 purchases across 200 customers revealed a clear pattern: the best results come when brands tailor frequency to buying behavior.  The optimal monthly cadence: ↳ 5-7 emails for frequent buyers ↳ 6-10 for medium buyers ↳ 12-14 for occasional buyers When customers aren’t segmented, 7 emails a month deliver the strongest performance. The highest open rates and most purchases over time. Sending only 4 emails reduces lifetime profit by 32%, while sending 10 cuts it by 16%. The reason is simple. Frequent buyers already know the brand, so too many emails create fatigue. Occasional buyers, on the other hand, read more when they’re still exploring and learning. This makes segmentation strategy the real growth lever. Instead of treating every subscriber the same, match communication frequency to purchase behavior. The balance is all about timing and relevance. The right message to the right segment builds stronger engagement, higher retention, and more revenue over time. How often do you adjust your email frequency based on buyer type?