Ecommerce

𝟭𝟬 𝗥𝘂𝗹𝗲𝘀 𝗳𝗼𝗿 𝗛𝗶𝗴𝗵-𝗖𝗼𝗻𝘃𝗲𝗿𝘁𝗶𝗻𝗴 𝗪𝗲𝗯𝘀𝗶𝘁𝗲𝘀 🔥 Most product sites don’t convert. Here’s how to fix it: 𝟭/ 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘆𝗼𝘂𝗿 𝗯𝘂𝘆𝗲𝗿 Before designing, talk to real users. Figure out what they want, what stops them, and what triggers action. → Talk to 5 signups: “What made you try it?” → Exit survey: “What’s stopping you?” → Watch session recordings → Skim support chats → Bonus: Buy someone coffee for quick feedback ✅ Example: Users say: “I just want to send invoices and get paid.” → Don’t write: “Smart billing software” → Say: “Send your next invoice in under 60 seconds.” 𝟮/ 𝗡𝗮𝗶𝗹 𝘆𝗼𝘂𝗿 𝗵𝗼𝗺𝗲𝗽𝗮𝗴𝗲 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 Your layout needs: → Headline: pain point → Subheadline: curiosity → CTA: single action → Visual: product in action → Body: benefits > features ✅ Example: → “Hiring is broken.” → “Our AI recruiter finds top 3 candidates in 24h.” → “Try it free” → Demo video → “Save 10+ hours/week on screening” 𝟯/ 𝗠𝗮𝗸𝗲 𝘃𝗮𝗹𝘂𝗲 𝗰𝗹𝗲𝗮𝗿 𝗮𝗯𝗼𝘃𝗲 𝘁𝗵𝗲 𝗳𝗼𝗹𝗱 Most people won’t scroll. → What is this? → Who’s it for? → Why does it matter? → What should I do next? ✅ Example: → Don’t say: “AI-powered web builder” → Say: “Launch your landing page in 60 seconds” 𝟰/ 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀, 𝗻𝗼𝘁 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 People don’t want “real-time sync.” They want fewer meetings, faster work. ✅ Example: → Don't say: “Real-time collaboration” → Say: “No more back-and-forth emails. Edit together live.” 𝟱/ 𝗔𝗱𝗱 𝗽𝗿𝗼𝗼𝗳, 𝗲𝗮𝗿𝗹𝘆 Trust builds conversion. → Logos → Quotes → Counters → Screenshots → Case studies ✅ Example: → “Trusted by 4,000+ teams at Meta, Notion, and Vercel” 𝟲/ 𝗥𝗲𝗺𝗼𝘃𝗲 𝗱𝗶𝘀𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀 Stick to one goal and cut everything else. → No blog links → No footer clutter → No secondary CTAs ✅ Example: If your goal is “Try for free,” everything should lead there. 𝟳/ 𝗨𝘀𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 𝗖𝗧𝗔 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 Avoid vague buttons. Make CTAs feel easy + specific. ✅ Example: → Don't say: “Start now” → Say: “Try for free” 𝟴/ 𝗗𝗲𝘀𝗶𝗴𝗻 𝗺𝗼𝗯𝗶𝗹𝗲-𝗳𝗶𝗿𝘀𝘁 60%+ of traffic is mobile. If it’s clunky, it’s broken. → Large tap targets → Sticky CTAs → Short scroll → Preview breakpoints ✅ Example: → Desktop: CTA beside video → Mobile: CTA pinned bottom → Preview with Lovable 𝟵/ 𝗧𝗲𝘀𝘁 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝘁𝗼 One version is only one guess. ✅ Example: → “The fastest invoicing tool for freelancers” vs. → “Send your next invoice in under 60 seconds” → Ship both with Lovable 𝟭𝟬/ 𝗗𝗼𝗻’𝘁 𝘀𝘁𝗼𝗽 𝗮𝘁 𝘁𝗵𝗲 𝗖𝗧𝗔 Conversion isn’t the goal. The activation flow right after is. → Pre-fill content → Show a 60s walkthrough → Highlight one key action ✅ Example: User signs up → edits sample invoice → sends in 1 click LFG

The New York Times just revealed everything wrong with how brands think about creators. Their headline yesterday: "How Brands Are Taking Back Social Media from Influencers" “Taking back?" As if social media was ever theirs to begin with. The Times covered Hasbro hiring a full-time creator for Nerf. Smart move. But they missed the bigger pattern. From my years at YouTube, Facebook, and Spotter, here's what the best brands are actually doing: 𝗧𝗵𝗲𝘆'𝗿𝗲 𝗻𝗼𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝗯𝗮𝗰𝗸 𝗰𝗼𝗻𝘁𝗿𝗼𝗹. 𝗧𝗵𝗲𝘆'𝗿𝗲 𝗳𝗶𝗻𝗮𝗹𝗹𝘆 𝗹𝗲𝘁𝘁𝗶𝗻𝗴 𝗴𝗼 𝗼𝗳 𝗶𝘁. The winners aren't picking one type of creator. They're building portfolios: USER-GENERATED CONTENT (UGC) The RealReal gave their superfan editorial control of their Substack. No brand guidelines. No approval process. Result: Authentic enthusiasm that converts. CREATOR-GENERATED CONTENT (CGC) Traditional influencer partnerships. But the smart brands aren't micromanaging scripts anymore. They're trusting creators to know their audiences better. EMPLOYEE-GENERATED CONTENT (EGC) The massive blindspot. Your team is already creating content — just not for you. Because you haven't given them permission to be themselves. The Times frames this as brands "taking back" their narrative. But the real winners are doing the opposite:  • Your barista with 50K on TikTok doesn't need your talking points  • Your designer's YouTube following trusts them, not your brand guidelines   • Your customers' real results beat any scripted testimonial I've watched this evolution from inside the platforms. The brands winning aren't choosing between UGC, CGC, or EGC. They're orchestrating all three by replacing control with trust: → Customers showing unfiltered results → Creators bringing their authentic voice → Employees sharing real insider perspectives While the NYT thinks this is about "taking back" social media, smart brands are asking: "How do we empower EVERY authentic voice in our ecosystem?" The best content strategies I've seen don't come from controlling the message. They come from trusting the messengers. In 2025, your brand voice isn't what you say. It's who you trust to speak for you. Your move. #CreatorEconomy #ContentStrategy #BrandContent

Yesterday, the open internet got its first toll booth. Not from courts or Congress, but from Cloudflare. The company, whose infrastructure touches roughly 20% of all global internet traffic, announced a significant shift: All new customer domains will now block AI bots by default. That means crawlers like OpenAI's GPTBot, Anthropic's ClaudeBot, and Google's Extended bot can no longer freely help themselves to your content. Unless you, the website owner, explicitly allow it, they’re cut off. Cloudflare also announced a Pay‑Per‑Crawl marketplace, where publishers can set terms for access - turning content into a licensed input, not a free good. With one product update, Cloudflare rewrote the default terms of engagement between AI and the web. From open to closed. From assumed permission to enforced consent. From passive scraping to active negotiation. Cloudflare has forced the question that’s been dodged for years: If AI systems are built on the backs of human expression, who owns the value they create? ▪️ For 20+ years, the internet operated on a basic exchange: Publish freely → Get discovered via search → Monetize attention. But AI broke that contract. Users now ask Claude or ChatGPT for answers. The models reply using human-created content - with no credit, no clickthrough, and no compensation. When publishing stops being a path to discovery - and starts being a donation to model training - incentives collapse. What Cloudflare did was reintroduce friction. Not to break the web. But to rebalance it. ▪️ What makes this moment so interesting is that the solution isn’t coming from regulators. It’s not the result of a moral awakening or a philosophical reckoning. It’s a default setting in a SaaS dashboard. But because of Cloudflare’s scale, it might as well be policy. This is capitalism at its best. You don’t always need top-down regulation to enforce guardrails. Sometimes market incentives create their own form of governance. In a world where governments often lag behind technology, infrastructure becomes policy. ▪️ Cloudflare may not have intended to reshape digital economics, but they’ve done exactly that. By forcing AI firms to ask, license, or walk away, Cloudflare has built the bones of a content licensing infrastructure, without ever saying the word “copyright”. ▪️ Let’s be clear: Cloudflare didn’t do this because it’s noble. They did it because it’s profitable. Their customers - TIME, Condé Nast, Reddit, News Corp - are tired of being strip-mined for training data without so much as a backlink. And Cloudflare is in the perfect position to intervene. I won’t be surprised if Fastly, Akamai, maybe even AWS follow. For 30 years, we assumed the internet had no gatekeepers. But it did. We just didn’t notice them until they started saying no. The principle is planted: Scraping without consent is not neutral. It’s extraction. We could see a more cohesive consent layer for the web emerge - driven not by altruism, but by incentive alignment.

Website traffic was a valuable metric correlated to growth. Now it may be a vanity metric, not correlated to growth. Search has been disrupted. Visits to your website are declining. So, marketers - what now? The search landscape was already shifting (I talked about this at INBOUND last year). Now, the change is accelerating dramatically: - AI Overviews appear in 43% of Google searches – when they do, organic CTR drops by nearly 35%. - Google’s AI Mode and audio AI overviews are coming – they will cause clicks to collapse further. - More buyers are using LLMs to find information, ChatGPT search in Europe grew 3.7x in six months. So, what should marketers do? And how can AI help? 1. Be everywhere and diversify your channels The days of relying solely on Google search are way over. You need to show up on YouTube, LinkedIn, Instagram, podcasts, and in niche communities. The good news? AI makes multi-channel, multi-format content creation scalable – even for small teams. 2. Be specific with context In the past, broad informational content was the way to rank in Google. Today, buyers expect results deeply relevant to them, whether they’re on Google, LLMs, or Reddit. You need specific content that reflects your expertise and resonates with your buyers. 3. Optimize for conversion, not clicks Traffic was once the lever you could pull. Now, conversion is where the opportunity lies. AI enables you to deliver personal messages that drive better conversion. Don’t ask, “How do we get more blog visits?” Ask, “How do we convert more prospects into customers across all channels?” The changes in search are sending shockwaves across marketing teams and media companies everywhere. The era of traffic-based marketing is ending. But a new era full of opportunity is just beginning. Super exciting times for marketers to reinvent the playbook!

Google just killed the checkout page 😦 At Google I/O, they just announced "agentic checkout" - letting users complete purchases *directly within search results.* This could be a genuine existential threat to every step in the payments value chain. Here's why this changes everything 👇 1. The Fintech arms race just accelerated This is no coincidence: • OpenAI hired Instacart CEO Fidji Simo for consumer operations • Perplexity embedded Stripe within its chatbot • Visa, Mastercard and PayPal announced agentic commerce services in April Google's response? Gemini 2.5 (their most advanced AI) will power checkout directly in search. The battle for who owns the moment before, during and after payment has begun. 2. The checkout page is dying For decades, merchants optimized checkout pages for conversion: • A/B tests on button colors • Reducing form fields • One-click purchasing • Cart abandonment emails Now Google's agentic checkout could make all that irrelevant. The agent can even "pay autonomously" - removing humans entirely from the payment flow. Merchants will need entirely new optimization strategies. 3. The fraud prevention nightmare begins When Google's AI completes transactions: • Who handles fraudulent purchases? • What happens when products don't match descriptions? • How do you validate customer identity? • Who owns risk management? Current fraud tools are built for human behaviors, not AI agents acting on behalf of humans. Every fraud model needs retraining - FAST. We need a directory for Agents and network tokens (whitepaper coming soon on this) 4. The bigger fintech strategy is clear Google is transforming "search into a big AI chatbot" with: • Shopping features in search • Virtual try-ons with your own photos • Price tracking with notifications • Agentic checkout in "a few months" • Integration with your Gmail, Docs, and Calendar My takeaway. The first platform to make agentic commerce seamless wins the next decade. Every Fintech CEO should be in emergency planning mode right now. • Payment providers: How will you integrate with Google's system? • Merchant acquirers: How will you manage these new flows? • Checkout optimizers: What's your new value proposition? • Risk platforms: How will you adapt your models? The future of advertising was always commerce. The future of commerce is loyalty and data. AI Agents could link all of those.

The PayPal, Mastercard and Visa announcements are not about agentic AI. They are about ownership of the next chapter of commerce and payments. Here is how they compare. 𝗪𝗵𝗮𝘁 𝗵𝗮𝘀 𝗯𝗲𝗲𝗻 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗱: -   PayPal : APIs that let any AI agent pay, track shipping, issue invoices and resolve disputes without leaving the chat. -   Mastercard : Network tokens + passkeys so agents become “trusted purchasers,” with programmable rules and biometric SCA baked in. -   Visa:  Five modular APIs for discovery → checkout, including user‑set spend caps, MCC filters and real‑time approvals. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮𝘁 𝘀𝘁𝗮𝗸𝗲? -   The payments race has always been about shaving seconds off checkout. In the agentic era, the winning time is 0 seconds, 0 clicks. Checkout disappears entirely as search, recommendation, and payment collapse into a single LLM-driven conversation. -   Whoever owns the payment credential becomes the default wallet in the loop, capturing not just the transaction, but data, interchange, and value-added services that follow. -   The players that get this right won’t just win conversions. They’ll own the customer relationship. The ones that don’t will find themselves disintermediated by someone else’s agent. 𝗧𝗵𝗲 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹: Imagine: • A travel bot books flights, hotels, insurance and pays - no forms. • An SME sourcing agent negotiates fabric in Guangzhou and settles with a virtual card - no emails. • A grocery assistant notices the fridge is low and re‑orders - no conscious decision. Multiply that by every vertical and every consumer. That’s always‑on demand capture - and potentially trillions in incremental volumes routed through whoever provides the agent‑native rails. 𝗪𝗵𝗮𝘁’𝘀 𝗹𝗶𝗸𝗲𝗹𝘆 𝗻𝗲𝘅𝘁: 1.     Industry standards: Common schemas for trusted-agent registration, permissions, and dispute handling. 2.     Granular consumer controls: Per-transaction biometrics, spend limits, time-of-day and merchant-category restrictions. 3.     Merchant enablement: SDKs and APIs to expose real-time inventory, pricing, and loyalty programs to agents. 4.     Regulatory attention: How frameworks like PSD3, CFPB guidelines, or MAS oversight will apply to autonomous payers. 5.     New revenue models: Pay-per-call risk scoring, agent onboarding fees, premium fraud protection layers. 6.     Advanced risk infrastructure: Real-time monitoring of agent behaviour, intent detection, and adaptive risk scoring to flag anomalies. 7.     Liability frameworks: Clear rules for who’s accountable when an agent transacts incorrectly: the user, the platform, or the agent provider. The race to build the payment infrastructure for autonomous agents is underway. Expect a wave of partnerships, acquisitions, and early execution challenges as the industry adapts to a new model of always-on, agent-driven commerce. Opinions: my own 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

Consistency is not growth. It's only half the battle: I see this advice everywhere: "Just be consistent and you'll get there." I've seen people: ⚠️ Consistently pitch the same failing product ⚠️ Consistently work 80-hour weeks without results ⚠️ Consistently network without building real relationships I'm not saying consistency isn't crucial. It is. But it won't get you to your goal alone. Here's the full equation: Consistency + Intentional Change = Growth The real work starts here: 1. Spot your loops ↳ Where you're consistent but not improving 2. Learn from experts ↳ Ask people who've solved what you're facing 3. Adjust your approach ↳ Keep showing up, but actually make changes Show up every day AND: ↳ Challenge your assumptions ↳ Question your methods ↳ Upgrade your toolkit Let's stop celebrating consistency alone. Start asking, "What do I need to change while staying consistent?" That's where real growth happens. -- Speaking of consistency in content: I've created 120 post ideas to help you build consistently online → https://lnkd.in/gKzZUq-b ♻️ Repost to help others grow ➕ Follow me for more like this

🗺️ AirBnB Customer Journey Blueprint, a wonderful practical example of how to visualize the entire customer experience for 2 personas, across 8 touch points, with user policies, UI screens and all interactions with the customer service — all on one single page. AirBnB Customer Journey (Google Drive): https://lnkd.in/eKsTjrp4 Spotify Customer Journey (High-res): https://lnkd.in/eX3NBWbJ Now, unlike AirBnB, your product might not need a mapping against user policies. However, it might need other lanes that would be more relevant for your team. E.g. include relevant findings and recommendations from UX research. List key actions needed for next stage. Add relevant UX metrics and unsuccessful touchpoints. That last bit is often missing. Yet customer journeys are often non-linear, with unpredictable entry points, and integrations way beyond the final stage of a customer journey map. It’s in those moments when things leave a perfect path that a product’s UX is actually stress tested. So consider mapping unsuccessful touchpoints as well — failures, error messages, conflicts, incompatibilities, warnings, connectivity issues, eventual lock-outs and frequent log-outs, authentication issues, outages and urgent support inquiries. Even further than that: each team could be able to zoom into specific touch points and attach links to quotes, photos, videos, prototypes, design system docs and Figma files. Perhaps even highlight the desired future state. Technical challenges and pain points. Those unsuccessful states. Now, that would be a remarkable reference to use in the beginning of every design sprint. Such mappings are often overlooked, but they can be very impactful. Not only is it a very tangible way to visualize UX, but it’s also easy to understand, remember and relate to daily — potentially for all teams in the entire organization. And that's something only few artefacts can do. Useful resources: Free Template: Customer Journey Mapping, by Taras Bakusevych https://lnkd.in/e-emkh5A Free Template: End-To-End User Experience Map (Figma), by Justin Tan https://lnkd.in/eir9jg7J Customer Journey Map Template (Figma), by Ed Biden https://lnkd.in/evaUP4kz Free Figma/Miro User Journey Maps Templates https://lnkd.in/etSB7VqB User Journey Maps vs. Service Blueprints (+ Templates) https://lnkd.in/e-JSYtwW UX Mapping Methods (+ Miro/Figma Templates) https://lnkd.in/en3Vje4t #ux #design

A very easy way to improve your Amazon ads efficiency by at least 10% Let’s say you’re spending ₹4–5 lakhs/month on Amazon ads. Your ACoS looks okay. Conversion rate seems fine. But your gut tells you—you’re still wasting some money on irrelevant traffic You’re not wrong At Atomberg, we had found that some of our Amazon spend was going toward search terms that had no business seeing our ads: - “cheap fan” -“rechargeable fan” - “usb fan under 1000” None of these users were in-market for a ₹3,000+ BLDC ceiling fan. But we were still showing up. And paying for those clicks. And it’s not just us. I’ve seen 6–7 brands' Amazon ad accounts across categories over the last few years—same problem, every single time The fix? N-gram analysis Takes less than an hour. You don’t need to be a performance marketing expert. But the results compound What’s N-gram analysis? It’s breaking down every search term into its word components—1-grams, 2-grams, 3-grams—and then identifying patterns that consistently drive waste… or conversion. Example: “cheap rechargeable fan for hostel room” turns into: 1-grams: cheap, rechargeable, fan, hostel, room 2-grams: rechargeable fan, hostel room 3-grams: fan for hostel, etc. When you do this across all your search terms, you start seeing the real picture. Why this matters more than just checking your search term report: Search terms ≠ keywords a) One keyword can trigger 100s of different queries. Some convert. Most don’t. You need to find the patterns. b) Waste is diluted across low-volume terms. Maybe “rechargeable fan for hostel” spent ₹300. You ignore it. But what if 12 other queries with “rechargeable” spent ₹6,000 in total with zero conversions? c) Long-tail is infinite. N-grams are finite. You can’t negate every bad search. But you can block the core terms—“cheap”, “usb”, “mini”—once and be done with it. d) It helps you scale campaigns too. You can find goldmine phrases like “white ceiling fan”, “silent BLDC fan”, “fan for living room”—with 5x+ ROAS. Those became exact match campaigns What you should do: a) Pull last 3 months of search term data b) Break them into unigrams, bigrams, trigrams c) Create a pivot with spend, orders, ROAS by N-gram d) Negate high-spend, low-conversion N-grams (e.g., “cheap”, “rechargeable”) e) Boost high-ROAS ones (e.g., “bldc”, “ceiling fan white”) f) Add exact match campaigns g) Rinse and repeat monthly Try it. Guaranteed to improve efficiency at whatever scale you are operating If you want to read an expanded version of the post, link is in the first comment

India has 150 million+ people above the age 60 and there is a massive opportunity to keep them healthy & fit. But everyone’s focused on Gen Z and no one’s building for their parents. It’s a hard business but a big one. We’ve invested in two companies. Here’s why it’s tough and how one should crack it. Understand the reality first. 1. Elders don’t think of “health” as proactive. They’re conditioned to wait until something breaks before acting. You’re selling a solution to a problem they don’t know they have yet. 2. The 65-year-old needs it but their 35-year-old child pays for it. You're not selling to the elder. You’re selling to their guilt-driven kids in Gurgaon or US. The buyer ≠ the user. 3. Trust is everything and you don’t have it. Indian elders trust: Their doctor, astrologer & their neighbour Not apps. Not tech bros. Not AI. You can't growth hack trust. You earn it slowly, locally. 4. They don’t want new habits. They’ve had the same breakfast for 40 years. You’re not selling a product. You’re undoing decades of routine. 5. Distribution is hyperlocal. Elders don’t click Insta ads. They talk to the uncle in their colony. You scale building by building not by user cohorts. Yes, 150M+ elders. But it’s not one market. It’s a thousand tiny tribes. Different languages, cultures, food habits, family structures, and tech comfort levels. If it were easy, Tata or Reliance would’ve done it already. But it’s wide open now. The one who combines tech + trust + real care will win. So how do you crack it? 1. Think first principles & not trends Don’t build a “senior fitness app.” Ask: Why did they stop moving? What gives them joy? You’re selling independence, not health. 2. Design for peace, not features. One-click help, One daily routine, One trusted face. Great elder products feel like human care not software. 3. Human-first, tech-enable. Don’t replace the daughter. Support her. Train 100 amazing elder coaches. Build tools to help them scale. 4. Don't focus on CAC. Here, it’s about trust per acquisition. You’re not selling toothpaste. You’re asking to be let into their daily life. Start offline. Build trust then tech. 5. You’re in the business of habit change & not selling an app or a pill. Get them to walk 15 minutes a day. Add protein to breakfast. Laugh more. Sleep better. Small wins compound. Don’t build for scale first. Build for consistency. Be in the business of habit change. 6. This isn’t a hackable D2C play. It’s a decade-long trust business. Build for one community. Get to know 100 elders by name. Solve deep, boring problems with elegance. Everyone’s chasing the next billion youth users. But the hidden opportunity lies in serving the first 150 million elders. The elder care market in India isn’t just underserved. It’s misunderstood and needs long-term play. Founders who crack this will build generational companies.