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?

Silent Red Flags in a Contract Not all contract risks are obvious. Some don’t wave big red flags they sit there quietly, sipping coffee, waiting to ruin your day when it’s too late. Here are a few sneaky ones to watch out for: 1. Termination Notice that has a trap ex: “Either party may terminate by giving a 90-day prior written notice by registered post.” This sounds fine until the other party refuses to accept mail, leaving you stuck. Flexibility in notice delivery methods (emails, RPAD, etc.) helps avoid this. 2. Auto-Renewal that feels like some subscription you forgot to cancel ex: A contract that auto-renews unless terminated 60 days before expiry. Missed the deadline? Congratulations, you just bought another term of commitment. Always check renewal terms and negotiate flexibility. 3. ‘Reasonable Efforts’ without a guiding light ex: “The service provider shall take all reasonable steps to ensure 99.5% website up-time.” Reasonable to whom? The client? The universe? Always define obligations with measurable standards. 4. Confidentiality that lasts forever ex: “The receiving party shall never disclose or use the confidential information.” Never is a long time, longer than some companies exist. A well-drafted clause should account for practical realities (disclosures required by law, etc.). 5. One-sided dispute resolution ex: “All disputes shall be resolved by arbitration, and the Party A shall appoint the arbitrator.” Agreeing to this means you’re going to their turf every time. Always ensure jurisdiction and dispute resolution are neutral. 6. Hidden costs in referenced documents ex: The main contract looks great, but a linked “Standard Terms & Conditions” document quietly adds extra fees, penalties, and other nightmares. Always review referenced docs. for no surprises. 7. ‘Best efforts’ vs. ‘Commercially reasonable efforts (CRE)’ ex: “The contractor shall use its best efforts to complete the project on time.” Best efforts could mean working 24/7 with unlimited resources. CRE = practical, business-minded execution. Choose wisely. 8. Non-Compete clauses that overreach ex: “The employee shall not engage in a competing business at any time in the future.” is a legal life sentence. Restrictions ought to be reasonable in scope, and duration. 9. Force Majeure that helps one side ex: “In case of an unforeseeable event, Party A is excused from obligations.” And Party B? Well… good luck. Force majeure should work both ways. 10. Silent Assignment clauses ex: You sign a contract with a trusted vendor, only to realize they’ve assigned their obligations to an unknown entity. Avoid unpleasant surprise, and require written consent before assignment. A little ambiguity is unavoidable. But when vagueness creates risk, or gives one party too much control, that’s when alarms should go off. #ContractReview #InHouseCounsel

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.

From the Journal: A bundle that Disney and Warner Bros. Discovery launched last July that offers Disney+, Hulu and Max at a discount has shown early signs of success in keeping customers subscribed, according to new data from subscription analytics firm Antenna. About 80% of the bundle’s subscribers were still paying for the service three months later, based on data for those who signed up between July and September, making it stickier than any of the services on their own. It also has a higher retention rate than Disney’s own bundles, such as its Duo pairing of Disney+ and Hulu or its Trio package of Disney+, Hulu and ESPN+. During that period, the triple-whammy bundle was even stickier than Netflix, the envy of the industry in its ability to keep customers. About 74% of people who started subscribing to Netflix between July and September were still subscribed three months later, according to Antenna. Customer retention is a major challenge in #streaming, since many consumers cancel a service once they have finished watching a particular show. Antenna found last year that most streaming services count about twice as many casual consumers—people who are either past subscribers or have signed up less than six months ago—as long-term users. The rise of the streaming bundle marks the resurgence of a familiar strategy for #entertainment: paying one price for a package of content made by different companies. “Warner and The Walt Disney Company to some degree have built their entire business around the cable bundle, so they’re very comfortable with bundling,” said Brendan Brady, Antenna’s strategy director. “We’re starting, increasingly, to see it come back.” The triple-play bundle had attracted roughly 2.2 million paid subscriptions as of Dec. 31, according to Antenna.

With CAC rising is EMAIL the? UK’s Most Underrated Acquisition Channel? In the UK, email is often underestimated in terms of customer acquisition. Meanwhile, in the U.S., it's a top-performing channel, with 81% of businesses using for acquisition (v. 80% for retention), with an average ROI of $36 for every $1 spent (DMA) you can understand why. So why the disconnect in the UK? A big part of it comes down to GDPR & perceived limitations around high-quality data. But after sending billions of acquisition emails for some of the UK’s biggest brands, I can say with confidence: email works—when done right. Here are my top 10 tips for using email as a scalable acquisition tool & ensuring you qualify traffic: 1. 🚫 Don't buy or rent data to send emails yourself Sender reputation determines inbox placement. You could buy the best list, but if you haven't engaged with them before, you are unlikely to inbox. Only work with senders who mail their data. (nb. Delivery is everything to them, so they will ensure your offer drives engagement or they wouldn't send) 2. 🤝 Trust senders to know their audience Ask providers what’s historically performed well—designs, content, send times. Use their insight to maximise your campaign effectiveness. 3. 🧪 ROI rarely comes from a single send Create a structured testing programme. Experiment with subject lines, creative formats, audiences, timing. Think performance, not one-and-done. You wouldn't run a one hit wonder on meta - so don't do it on email. 4. 🔁 Use a multi-touchpoint approach Just like paid media or social, consumers need multiple exposures before they convert. Plan repeat sends to build familiarity and intent. 5. 🖼️ Tell your story, but make it scannable Email gives you space—use it! Combine visuals, GIFs, storytelling. But keep it easy to skim, with prominent CTAs. Guide the reader clearly. 6. 🙅♀️ Skip the “Hi [First Name]” In acquisition, personalisation by name isn’t effective. You haven’t earned a relationship yet—focus on value and relevance first. 7. ✨ Nail your above-the-fold content The top section drives most engagement. Make sure your primary USP shines here. Grab attention fast, and give users a reason to click. 8. 👁️ Think beyond opens—email is brand awareness Even unopened emails contribute. People read subject lines and from-names when deciding what to engage with. An email from “M&S – 50% Off Sale” makes an impact, even if it’s deleted. 9. 📊 Question low open rates Thanks to auto-image loading, open rates are often inflated. So if your open rates are low, it may point to real quality issues—look deeper. 10. 🚀 It can be a pure acquisition channel Email makes it easy to exclude existing customers. Clean deduplication ensures you're reaching only new potential buyers. Email isn’t just a retention tool—it’s a powerhouse for acquisition, brand visibility, and testing at scale. UK marketers who embrace its potential will unlock a competitive edge that many are still missing.

What happens when you stop treating bundles like boring discounts and start using them to reflect how customers actually shop? That’s what NALA, an underwear brand, did. The result? A bundling strategy that increased AOV, built stronger relationships, and highlighted the brand’s core mission 👉 Key benefits: * created a seamless, personalized shopping experience * encouraged exploration across product categories * boosted customer trust and loyalty * increased AOV through meaningful value (not just % off) 👉 Results & takeaways: 1) Product bundles included more than just discounts; they reflected how customers wanted to feel: supported, free, confident 2) Bundles were integrated into product pages organically, not pushed aggressively 👉 The secret to success: Customer-centered bundling. NALA didn’t just bundle items; they bundled emotions, values, and lifestyle. The strategy prioritized how customers want to feel, not just what they want to buy 👉 Supporting tactics: - designed bundles based on real customer needs and purchase behaviors - let customers choose within bundles, avoiding rigid pack structures What’s the most effective bundling strategy you’ve seen or used? Was it discount-driven or something deeper? #shopify #ecommerce

Most CPG brands fail at eCommerce. Not because of ads. Not because of their website. They fail because their offer stack is broken. Too many launch with: – “shop our range” – a discount code – hope that subscriptions just happen This never works. Because the offer stack IS the strategy. It dictates: – conversion – CAC payback – churn – cash flow Here’s the 7-step framework I use with good-for-you CPG brands: 1️⃣ Rule of One Focus on one hero product ↳ clarity = conversion 2️⃣ Trial → Subscription Make trial irresistible ↳ then roll into sub 3️⃣ Offer Stack = Value Exchange First order feels like a no-brainer ↳ give more than they paid for 4️⃣ Subscription Cadence Align with consumption rate ↳ quarterly often beats monthly 5️⃣ Trial → Sub Journey Educate in first 30 days ↳ stop churn before it starts 6️⃣ Economics First CAC payback in 3 months ↳ protect contribution margin 7️⃣ Offer Evolution Start simple ↳ layer in bundles and seasonals later Examples: Everyday Dose doesn’t just sell coffee. They include a frother + app. The trial feels abundant. That creates stickiness. Purdy & Figg doesn’t default to monthly. They ship cleaning products every 90 days. Higher AOV. Lower churn. Better cash flow. So ask yourself: Is your offer stack doing the heavy lifting? Or are you relying on ads to fix a packaging problem?

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.