Ecommerce

The difference becomes much clearer when you put it into a real product. Take ElevenLabs’ voice AI as an example. 𝟏. 𝐓𝐡𝐞 𝐛𝐚𝐬𝐞 𝐥𝐚𝐲𝐞𝐫: 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐲 At the first layer, ElevenLabs can turn text, scripts, voice references, or multilingual content into natural speech. For many products, this appears as a generative AI feature: AI narration in an education platform automatic voiceover in a video tool multilingual dubbing for content natural voice response in a support system Here, the value is mainly output quality. The system is generating voice, but it is not necessarily running a workflow. 𝟐. 𝐓𝐡𝐞 𝐦𝐢𝐝𝐝𝐥𝐞 𝐥𝐚𝐲𝐞𝐫: 𝐀𝐈 𝐯𝐨𝐢𝐜𝐞 𝐚𝐠𝐞𝐧𝐭 The next layer is when voice becomes interactive. A generated voice is not an agent. But a voice interface that can listen, understand intent, respond in context, ask follow-up questions, and manage a conversation starts to look much closer to one. This is where voice AI becomes more than audio generation. It becomes an interaction layer. The user is not just listening to generated speech. They are talking to a system that can handle a role inside a conversation. 𝟑. 𝐓𝐡𝐞 𝐡𝐢𝐠𝐡𝐞𝐫 𝐥𝐚𝐲𝐞𝐫: 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐬𝐲𝐬𝐭𝐞𝐦 The more interesting layer appears when the voice agent is connected to real company systems. CRM. Support tickets. Calendars. Order databases. Knowledge bases. Payment tools. Internal APIs. Telephony stacks. Workflow automation tools. At that point, the system can do more than speak naturally. It can check an order, update a customer record, create a ticket, schedule a demo, trigger a follow-up, escalate to a human, or write the result of the conversation back into the system. In short: Generative AI creates the voice. An AI agent uses voice to interact. An agentic system connects that interaction to tools, data, permissions, and workflows. Explore more here https://lnkd.in/g57BYwHz *The chart is simplified, but it gives us a useful starting point to map these ideas to an actual product.

We studied 2 lakh+ Indian threat indicators in 2025. And here’s what 2026 regulators now demand (but most companies still don’t do.) 2025 changed the game. We tracked threats across every state in India, from Maharashtra to Manipur. The scale of activity is no longer random. It’s strategic, coordinated, and sector-targeted. And now, so are the regulators. Here’s what 2026-ready companies are expected to do (but 90% still haven’t): 01. State-wise Risk Mapping is now a compliance expectation. 82% of malware volume came from just 6 Indian states. But the fastest-growing threat zones were Tier-2: Punjab, Odisha, Assam. Regulators now want geo-behavioral segmentation, and not just IP logs. 02. Proof of real-time detection, not just dashboards. In sectors like BFSI and energy, response time is now being scrutinised. Can you prove your system reacts in seconds, not hours? 2026 audits will ask: “Show me what your XDR did the last time your East zone flagged an anomaly.” 03. Sector-specific threat coverage: not optional anymore. Pharma, power grids, BFSI, healthcare, they’re all being hit differently. A generic firewall rule isn’t compliance. Mapping sector threat intel to your stack is now a regulatory demand, not a suggestion. 04. The death of checkbox compliance. 68% of compromised orgs in 2025 were “fully compliant”. But only 12% had active breach simulations in place You can have 100 tools. But, if nobody’s testing them in real-world breach drills, it won’t save you in 2026. 05. From centralised to hybrid monitoring Work-from-anywhere isn’t new. But regulators now want user behavior-based controls that adapt to geolocation, risk context, and device intelligence. 2026 audits will go beyond log files. They’ll ask: “How does your system behave when a user travels from Pune to Patna?” Regulatory audits in 2026 will feel more like red-team simulations. What are you seeing across sectors? Seqrite Quick Heal #CyberSecurity #ThreatIntelligence #XDR #RegTech #CISO #Compliance #CyberRisk #IndiaCyber #BFSISecurity #CriticalInfrastructure #SecurityLeadership

The European Parliament has officially passed Extended Producer Responsibility (EPR) legislation that fundamentally shifts the responsibility for textile waste management to fashion brands and retailers – with far-reaching global implications. This new law requires all producers, including e-commerce platforms, to cover the full cost of collecting, sorting, and recycling textiles, regardless of whether they are based within or outside the EU. The financial burden of Europe's textile waste now falls squarely on the brands that create it. What are the critical business implications? UNIVERSAL SCOPE: The legislation applies to all producers selling in the EU market, including those of clothing, accessories, footwear, home textiles, and curtains. No company is exempt based on location. FAST FASHION PENALTY: Member states must specifically address ultra-fast and fast fashion practices when determining EPR financial contributions, creating cost penalties for unsustainable business models. GLOBAL SUPPLY CHAIN DISRUPTION: As the world's largest textile importer, the EU's new rules will ripple across global supply chains, particularly impacting exporters from Bangladesh, Vietnam, China, and India who supply much of Europe's fast fashion. TIMELINE PRESSURE: Officially adopted September 2025, this creates immediate operational and financial planning requirements. COMPETITIVE RESHAPING: Brands and retailers will inevitably pass increased costs down their supply chains, fundamentally altering supplier relationships and pricing structures globally. What are the implications for various stakeholders? For CEOs and board members: This represents more than regulatory compliance – it's a complete business model transformation. Companies must now integrate end-of-life costs into product pricing, rethink supplier partnerships, and accelerate circular design strategies. For sustainability and decarbonisation executives: This creates unprecedented opportunities for circular economy solutions, sustainable material innovation, and traceability system development across global supply chains. Link: https://lnkd.in/dTyHtHuD #sustainablefashion #circulareconomy #textilwaste #epr #fashionindustry #sustainability #supplychainmanagement #fastfashion #environmentalregulation #businessstrategy #decarbonisation #textilerecycling #fashionceos #boardgovernance #climateaction #wastemanagement #producerresponsibility #fashionsustainability #textileindustry #greenbusiness

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!

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

"Is $20/month too much for our product?" Instead of guessing, we used the Van Westendorp method to find our pricing sweet spot. 4 questions revealed exactly what users would pay (and we haven't touched our pricing since). Here's the framework any founder can steal: 1. Send a survey to actual users, not prospects We surveyed people already using Gamma. They understood the real value of our product, not hypothetical value. Too many founders survey their waitlist or randomly select people who have never used their product. That's like asking someone who's never driven about car prices. 2. Ask these 4 specific questions - At what price would this be too expensive for you to consider it? - At what price is it expensive but still delivering value? - At what price does it feel like a bargain? - At what price is it so cheap you'd question if it's reliable? These create bookends for perceived value. You're mapping the entire spectrum of price psychology, not just asking "what would you pay?" 3. Plot the responses and find where the lines intersect Graph responses from lots of users. Where "too expensive" and "too cheap" lines cross: that's your acceptable range. Where "expensive but fair" meets "bargain": this is your optimal price point. 4. Test within the range, don't just pick the middle The intersection gives you a range, not a number. We ran pricing experiments within that range to see actual conversion rates. A survey shows willingness to pay; testing reveals actual behavior. 5. Lean towards generous (especially for product-led growth) We chose to be more generous with AI usage than our "optimal" price suggested. Word-of-mouth growth matters more than maximizing initial revenue. Not everything shows up in the numbers. 6. Lock it in and stop tinkering Once you find the sweet spot through data, stick with it. We haven't changed pricing in 2 years. Every month debating pricing is a month not improving product. Remember: pricing is a signal, not just a number (Image: First Principles)

Retail is dead. Foot traffic is down across the board. That’s the narrative we hear over and over being pushed in the media. Yet TALA - Grace Beverley’s brand born online - has opened their first physical store in Carnaby Street this weekend, to queues around Soho & a sell-out ticketed event. So rather than being dead, what if the role of brand retail has simply transformed? My take 👉 The store is no longer solely top of the funnel or entirely about discoverability. It’s the destination. The community hub. The clubhouse. It’s where content becomes tangible. Where brand world becomes real world. Where you walk through the door and it feels like stepping into their Instagram, their TikToks, their values. We’re not just talking racks and rails - there’s a coffee bar, photobooths, events, and experiences. This is community-led commerce. It’s a cultural space disguised as a high street shop. And I believe this is where we see the real revival of the high street - not as a retail destination, but as a brand world brought to life. A place to deepen connection with your community - ultimately strengthening the life time value of that customer. The blueprint is clear: Content captures. Community keeps. IRL deepens. TALA joins the ranks of Gymshark, Odd Muse and Glossier, Inc. - brands that built strong digital tribes before laying a single brick and now use their stores as destinations for the community to connect IRL. And in a world where discovery is unpredictable - spanning podcasts, group chats, TikToks and Substack - trying to funnel people in linearly is a lost cause. The smartest brands aren’t forcing a path. They’re showing up where their community already is & then inviting them in deeper. Retail isn’t dead. It’s reinventing itself & I'm so here for it. Calling it now - your favourite digital brand worlds will manifest in real life in the next 18 months whether through pop ups or permanent stores. Mark my words!

So, here’s a quick story about how I managed to take our app ratings at airtel from a 3.2 to a solid 4.3 in just 30 days. I was on a call with our account executive at MoEngage where we were discussing the RFM model. If you’re not familiar, RFM stands for Recency, Frequency, Monetization—it’s basically a way to understand customer behavior based on how often they use the app, how recently they’ve been active, and if they’ve made any purchases. After the call, I started thinking—how can we use this data beyond just targeting users for offers or notifications? And then it clicked: we could use this to improve our app ratings. Here’s what I did next: instead of showing the app rating prompt to everyone (which was clearly not working), I decided to get more specific. I created a segment of users who were really engaged—people who were listening music for at least 20-30 minutes a day and opening the app 5-6 times daily. These were our power users, the ones who were already loving the app. But I didn’t just stop there. I made sure the rating prompt would only pop up after an “aha moment,” like after they listened to five songs or changed their hello tune. I wanted to catch them at a high point when they were already feeling good about their experience. Plus, we capped the prompt to only show up once a week, so we weren’t bombarding them. And guess what? It worked! By focusing on the users who were most likely to give us positive feedback, we managed to take our ratings from 3.2 to 4.3 in just a month. It was all about understanding who to ask, when to ask, and how to make that moment feel seamless.

We grew an email list from 0 to 500K subscribers in just 10 months. If I were starting from scratch today, here's exactly how I'd do it again: 1) Nail the Lead Magnet: The fastest way to grow your email list is by offering something valuable in exchange for an email. Think of it like this: people won't give up their email for nothing. Create something they can't ignore: a discount, exclusive content, or a tool they can’t find elsewhere. For us, offering free travel guides was a game-changer. 2) Optimize for Opt-Ins Everywhere: Your website, blog, and even social media accounts should work like opt-in machines. For example: - Add pop-ups and fly outs on key pages. - Place CTAs above the fold. - Use scroll-triggered modals when visitors are engaged. We tested endlessly, and this attention to detail paid off big. 3) Tap Into Paid Growth Early: Ads get a bad rep, but when done right, they’re a growth accelerant. We launched targeted ads promoting our lead magnet and built a funnel that turned traffic into email signups. Paid campaigns helped us scale fast while testing which offers resonated with our audience. 4) Partner with the Right People: Collaborations can grow your list faster than any single effort. Whether it’s co-branded giveaways, email swaps, or shoutouts, find brands or creators that share your target audience. A well-executed partnership will unlock exponential growth. One really unique thing we did: We bought a bunch of viral social accounts and rebranded them for our business. This was huge in kickstarting massive and sustainable growth. And we fast-tracked the social proof we needed to build trust and scale quickly. 5) Focus on Quality, Not Just Quantity: A big list is meaningless without engagement. From Day 1, we focused on high-value emails to ensure subscribers opened, clicked, and stayed. Here’s a pro tip: Consistency wins. Sending emails weekly or bi-weekly keeps your list warm and engaged. 6) Build a Content Machine: Pair email growth with an organic content strategy that feeds your funnel. Blog posts, social media, and SEO aren’t just good for traffic—they create trust. The more valuable content you share, the more people will want to hear from you. 7) Leverage Cheap Marketing Channels in Ways Others Haven’t: This is going to ruffle some feathers but we absolutely dominated cold email for user acquisition. To the tune of 6 figure subscriber acquisition. No one was doing cold email for B2C the way we did it. This proved to be the most scalable yet cheapest acquisition channel we had. — To recap: - Offer something valuable for free to grow your list. - Use every channel—paid and organic—to drive opt-ins. - Build relationships with partners who already have your audience. The result? A system that scales. Your list is the one asset you fully own—start building it ASAP!

Killer graph. Out of the £130 billion online non-food purchases we make in the UK, £27 billion of them get sent back to retailers. Our research with ZigZag Global shines a spotlight on the significant challenge online returns cause in the industry, focusing on those consumers who consistently and intentionally over-order - the "serial returners". Key stats ➡️ Around 11% of online shoppers are serial returners (frequently over-ordering with the intention of returning many items) ➡️They account for 24% of all online returns ➡️Serial returners send back, on average, £1,400 worth of online orders per year, compared with an average of £650. ➡️ This amounts to £6.6 billion of returns. ➡️ Almost three-quarters of serial returners are under the age of 45, and they return more than 42% of all their orders. A 1/4 of serial returners admit to over-ordering just to reach a minimum order value (often to trigger free delivery) only to return goods they had no intention of keeping. The same proportion also said they had returned items after finding them cheaper elsewhere or on promotions. While 18% admitted to returning items having already used them for a short period. There is no silver bullet here that is going to fix this issue for retailers. A nuanced understanding of specific triggers and barriers is essential to effectively target returners through pricing and returns options. 💥 For many boardrooms debating whether they should charge for returns, my thoughts are: 💥 The returns equation transcends simple binary choices between free or paid. Retailers must architect differentiated returns propositions that align commercial realities with customer lifetime value. Smart retailers will segment their returns strategy by customer profitability metrics, leveraging AI to identify purchase patterns that predict long-term value. This enables dynamic returns pricing that protects margins while fostering relationships with truly valuable customers. The goal isn't to punish returns – it's to price them according to their true cost to serve, while rewarding profitable shopping behaviours. There's also a paradox at play where customer acquisition costs are optimised but customer profitability is compromised. Many retailers are essentially subsidising unsustainable shopping behaviours at the expense of margin, unknowingly targeting customers they could do without. The real opportunity lies in leveraging returns data as a predictive indicator of customer profitability. By applying advanced analytics to returns patterns, seasonal purchasing behaviours, and cross-category browsing and mining deep behaviour insights, retailers can enable proactive intervention before profitability erodes. This shifts the conversation from universal policies to personalised solutions that can turn returns from a pure cost centre into a strategic lever for customer engagement and loyalty. Full research is available to download here ⬇️ https://lnkd.in/e5paRNWC