E-commerce Technology Trends

The same people hunting for discounts on Myntra are paying ₹1,500 for instant fashion on Zepto. This isn't just another retail trend. It's a complete reversal of how we understand fashion buying. Urban consumers have started treating fashion like groceries, demanding immediate delivery for immediate needs. Think about it. That Saturday evening party outfit can't wait three days.  The campus event tomorrow needs the perfect look today. Quick commerce understood this shift before traditional retail even noticed and quick commerce platforms are specifically targeting trend-conscious urban customers and Gen Z. Why? Because they're willing to pay ₹500 to ₹1,500 on Zepto or ₹1,400 to ₹1,600 on NEWME for 25 to 60 minute delivery. The implications for fashion brands are staggering. Expanding inventory to new regions now requires: → Tech-led demand prediction systems → Understanding hyperlocal preferences → Building distributed warehouses → Tracking regional buying patterns Brands studying fashion demand must consider completely new factors. Weekend travel creates spikes in metro cities. Festive seasons hit differently across regions. Occasion-based purchases drive impulse buying. Each locality has its own style DNA. Traditional retail spent decades perfecting central warehouses and seasonal collections. Quick commerce demands the opposite. Small inventory points everywhere. Weekly design drops. Regional customization. Fashion has entered the 10-minute economy, and there's no going back. What's one fashion emergency that made you wish for instant delivery?

🚨 New Elevation Capital thesis: Quick Commerce x Fashion! Young Indians are discovering quick fashion through spontaneous moments - weekend plans, last-minute parties, or simply the urge to refresh their look within hours. While horizontal quick commerce players have added fashion to their offerings, the category demands specialized capabilities around assortment, sizing, and the critical try-and-buy experience that generic platforms struggle to deliver. Players like Slikk, KNOT, ZILO, NEWME and incumbent Myntra's M-Now are pioneering this space. These vertical fashion platforms are reimagining the entire shopping experience by marrying the discovery of online with the confidence of offline trial. Some highlights: > 10-20% of early users already buying twice monthly, transitioning from emergency use cases to regular browse-and-buy behavior > Impulse commerce creates entirely new demand - "I'm at a friend's place, we just made plans, I need an outfit in an hour" is driving adoption > Try-and-buy solves fashion's biggest online pain point - riders wait while customers try outfits, eliminating fit anxiety and reducing RTOs to 15% (vs 30% traditional) > Dark stores of 3,000-5,000 sq ft stock tens of thousands of styles, but the edge lies in merchandising algorithms that predict hyperlocal fashion preferences > Sale-or-return models critical for scaling without inventory risk - but success depends on brand relationships and negotiating power > Operating model complexity creates defensibility - balancing assortment breadth with inventory efficiency requires sophisticated demand prediction even when SOR isn't available > Categories like ethnic wear and bottom wear see strongest traction where fit matters most > Key challenges: expanding assortment without bloating inventory, achieving omnichannel coordination with brands, managing mix of SOR and outright purchases > TAM expansion opportunity - converting offline shoppers who avoid malls due to poor experience, not just capturing existing online wallet share

I walked into Harvey Nichols this week and witnessed the new-age QVC in real time. Two live sellers were streaming Moncler on TikTok to viewers in Asia, right there on the shop floor. A steady stream of orders flowing in. Is this the future of luxury live streaming? Going live from inside the luxury store itself. Live selling on apps like TikTok and Whatnot is reshaping e-commerce and the top sellers are making five and six figures in a single livestream!! → Global live commerce was estimated at $𝟭𝟯𝟱–𝟭𝟱𝟬 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 𝗶𝗻 𝟮𝟬𝟮𝟱, mostly driven by China but growing quickly in the US and Europe. → McKinsey projected it could reach 𝟮𝟬% 𝗼𝗳 𝗮𝗹𝗹 𝗲-𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲 in some markets by 2026. → TikTok users are 𝟭.𝟰𝘅 𝗺𝗼𝗿𝗲 𝗹𝗶𝗸𝗲𝗹𝘆 to buy something they discover on the platform compared with other channels. And for luxury, this is where it gets interesting. People still trust physical retail for authenticity. They want to know the item is real, the provenance is real, the seller is real. At the same time, discovery has moved online and impulse buying is happening in the moment. Put those together and you get a new format: 𝗟𝗶𝘃𝗲 𝘃𝗶𝗱𝗲𝗼 + 𝗮 𝘁𝗿𝘂𝘀𝘁𝗲𝗱 𝘀𝘁𝗼𝗿𝗲 𝗯𝗮𝗰𝗸𝗱𝗿𝗼𝗽. You get the credibility of Harvey Nichols or Selfridges × the reach of TikTok audiences across Asia, the US and Europe. Standard live commerce already converts at 𝟯–𝟭𝟬𝘅 𝗻𝗼𝗿𝗺𝗮𝗹 𝗲-𝗰𝗼𝗺𝗺. Add the trust signals of a well-known retailer and the potential is obvious. For overseas audiences, it’s the appeal of shopping “live in London” without being anywhere near London. This is why platforms like Amazon Live, TikTok Shop and Whatnot are pushing so hard. And why sellers are becoming performers. TikTok Shop is actually a client of OK COOL, and the scale we’re seeing behind the scenes tells you exactly where this is heading 🚀 Feels like the start of something mega…. are you buying luxury live?

My fourth trip to China left me with a renewed sense of awe and insight. Each visit brings new learnings, but this time, the changes in how Chinese sellers are approaching Amazon really stood out. Here are the key takeaways: 1️⃣ From Product Sellers to Brand Builders Chinese sellers are evolving. I now see a clear divide between “product sellers” and “brand sellers”. The old-school approach of managing based on ACOS and TACOS is giving way to a new generation of sellers who prioritize growth and ROAS (Return on Ad Spend). These brand-focused sellers are building lasting businesses, not just chasing volume. 2️⃣ AI is Leveling the Playing Field Many of the challenges Chinese sellers have historically faced are now being solved through AI tools. Sellers are using AI to refine listings, enhance images, and craft product pages that truly resonate with customers. The result? A better customer experience and more polished brand presence. 3️⃣ Temu is Still a Thing, But... Temu may be popular, but the smart Chinese brands are recognizing that cheap products don’t build profitable businesses in the long run. Many sellers are realizing that the real value lies in building quality brands, not simply flooding the market with low-cost goods. It’s a big shift, and those who are making it are now focused on premium products. I met one brand that made a dramatic shift—from low-margin electronics to selling heavy, premium outdoor furniture. Talk about a 180-degree pivot! 4️⃣ Brand Building Meets Performance Marketing It’s no longer just about ACOS—brands are finally recognizing the importance of balancing brand-building with performance marketing. The best sellers understand that long-term growth comes from a combination of brand recognition and smart, data-driven performance tactics. 5️⃣ AMC is Still Underutilized—But Not for Long I’m excited to see that AMC (Amazon Marketing Cloud) is still flying under the radar for many sellers, both in China and the U.S. But that’s about to change. With recent updates, AMC for Sponsored Ads is poised to explode in 2025. Sellers who tap into this tool will have a major advantage in expanding their reach and fine-tuning their advertising strategies. Expect to see more wins from Chinese brands leveraging AMC. 6️⃣ The Next Wave of Generative AI I got a sneak peek at what I would call the next wave of tech: generative AI and chat-based systems built from the ground up. Early tests are encouraging, with brands able to scale ad spend while maintaining solid ROAS. As these systems improve, we’ll see Chinese brands using Generative AI to gain an edge in both marketing and operations. The future is smart, and it’s here. A huge thank you to Lin (Susan) Zhai, Diana Lai, and the entire team for your incredible hospitality during this trip. Thanks also to my fellow travelers Jason Cohen, Jem McIlveen, Andrew Roth, and Yong Sohn for making this trip even more memorable.

Instant gratification shopping, driven by quick-fashion startups, is pushing fashion retailers to speed up their delivery times, Vaeshnavi Kasthuril reports for Mint. Established brands and newer players are both trying to keep up, but they’re taking different approaches. Brands like Biba and The House of Rare are considering setting up dedicated delivery hubs in cities where they have a higher concentration of stores, rather than using their retail outlets as fulfilment centres. This is to avoid disrupting the in-store shopping experience and create operational challenges. “We don’t have very large stores; they are anywhere between 1,000 and 2,000 square feet. So, that’s not the right efficiency,” says Biba’s MD Siddharath Bindra. Opting for the hub-based model would allow same-day or two-to-three-hour deliveries, he adds. Brands like Libas, meanwhile, are integrating stores into fulfilment networks. A gradual rollout, it is starting with selected cities and a narrowed product mix catering to consumer expectations that move beyond groceries to fashion for quick deliveries. “At Libas, the timeframe will be approximately 60-90 minutes at the max,” says Bhavay Pruthi, the company’s SVP, E-commerce and Product Management. However, customers are hesitant to spend large amounts, such as ₹5,000, on fashion products through quick-commerce channels, he adds. The urgency to adapt is fuelled by a surge of quick-fashion startups attracting investor funding. While Zilo raised $15.3 million, Knot secured $5 million. Quick-commerce platforms have expanded from basic fashion essentials to specialised categories. And new entrants like Klydo, Newme’s Zip, and Snitch Quick are taking the model further by centering their businesses on near-instant fashion access. ➡️ Is instant delivery poised to become the new standard in fashion retail? Share your take in the comments section. Source: Mint: https://lnkd.in/gHeSzD-q ✍: Dipal Desai 📸: Getty Images #fashion #retail

The major tech companies - Amazon Web Services (AWS), Google, Meta Facebook and Microsoft - invested over $65 billion in CAPEX this quarter (Q3) on cloud and AI infrastructure. Year-to-date spending exceeds $171 billion, setting records for quarterly investment: Amazon: $22.79 billion (+79%), marking a new high. Spending primarily targets AWS and fulfillment. Amazon expects around $75 billion in CAPEX for 2024, with further increases projected for 2025. Google: $13.06 billion (+62%), matching nearly all of 2017’s annual spend in one quarter. Investments focus 60% on servers and 40% on data centers. Meta: $9.2 billion (+36%), slightly below guidance due to timing, with increased spending expected in Q4 and 2025 for infrastructure growth. Microsoft: $20 billion (+79%), equivalent to its full-year 2020 spend, aimed at AI-driven cloud capacity. Microsoft’s enterprise offering, Fabric, now has over 16,000 customers, including 70% of the Fortune 500. Detailed Company Quotes: Amazon:  - “We expect to spend approximately $75 billion in CAPEX in 2024. The majority supports AWS’s growing AI demand, alongside infrastructure in North America and internationally. Investments in fulfillment and transportation networks aim to enhance delivery speeds and reduce service costs.”  - “Many of these assets, such as data centers, have useful lives of 20 to 30 years.”  - "Our AI capacity demand currently exceeds available infrastructure."  - "CAPEX growth is particularly driven by generative AI, with anticipated further spending in 2025." Google:  - "We expect Q4 CAPEX to match Q3 levels and project further increases in 2025, though not as substantial as from 2023 to 2024."  - "In Q3, approximately 60% of CAPEX went to servers, with 40% allocated to data centers and networking equipment." Meta:  - “Our full-year 2024 CAPEX range is now $38-40 billion, slightly up from prior guidance, with significant infrastructure growth anticipated in 2025.”  - "The expected increase in Q4 CAPEX will be partly due to server spend and data center investments, with delayed cash outflows from server deliveries appearing in Q4."  - “We’re training Llama 4 on a cluster of over 100,000 H100 GPUs—one of the largest known setups.” Microsoft:  - “Half of our cloud and AI spending is on long-lived assets supporting monetization over the next 15 years, with the remainder for CPUs and GPUs to meet current demand.”  - "Demand, especially for AI inference, continues to exceed capacity."  - "We don’t sell raw GPUs externally due to our own high demand and adverse selection in the current market."  - "Our Fabric platform now has over 16,000 customers, including 70% of the Fortune 500, with Copilot Stack sitting atop Fabric to provide advanced enterprise infrastructure." #ai #digitalinfrastruture

Every ecommerce leader I know is running on the same hamster wheel: growth targets keep rising, but the rules of the game are being rewritten under their feet. When you place a leader and later sit down with them to swap insights, you’re reminded why the right talent shapes entire industries. I had a great conversation with Julian Exposito-Bader (ex-Amazon, TAG Heuer) about what’s really shaping the future of ecommerce, and he boiled it down to four pillars every executive should have on their radar: 1. Tariffs & Supply Chain Disruption Tariffs are no longer background noise. They’ve reshaped global commerce. Chinese manufacturers are redirecting from the US into Europe, flooding marketplaces with B-brands and copycats. Leaders who win will be the ones who diversify sourcing, master customs optimization, and use bonded warehouses strategically. 2. Sustainability as a Competitive Advantage It’s no longer acceptable to send a small product in three layers of plastic. Lastmile innovation (bike couriers, drones, reusable packaging) is moving from “PR play” to “bottom-line differentiator.” Zalando is pushing hard here. Consumers are watching, and they notice who’s lagging behind. 3. AI-Powered Commerce Revolution Gen Z isn’t Googling “best running shoes”, they’re asking ChatGPT or Alexa. LLMs are the new storefront. The question is: do brands have a strategy to influence those models? Add in 10-minute delivery in Southeast Asia (coming soon to Europe) and AI-driven fraud vs. fraud detection… the entire purchase journey is being re-engineered. 4. Channel Strategy & ROI Focus Social commerce is expensive and messy, but TikTok Shop is where the next generation buys. DTC remains the highest margin, but demands world-class storytelling. Amazon gives you traffic, but only if you’re willing to pour money into ads. And let’s not forget the “lipstick effect”, beauty keeps outperforming even when wallets tighten. The takeaway? Ecommerce leaders aren’t just choosing a channel anymore, they’re orchestrating these four forces simultaneously. For me, it was also a reminder of why the right hire matters: leaders like Julian don’t just react to market shifts, they anticipate and shape them. I’m curious, in your markets, which of these four pillars is hitting hardest right now? #ecommerce #fmcg #trending

Amazon is spending billions to make sure it doesn’t fall behind in #AI With Microsoft tightly partnered with OpenAI, and Apple, Google, and Meta adding their own AI into pretty much all their products, #BigTech is hard at work creating as much value - or hype - from AI as possible. Amazon’s latest move is a $4 billion bet on Anthropic, announcing the investment in the AI startup on Friday, doubling its total stake in OpenAI’s largest rival to $8 billion. 🤖 The new investment will be deployed in phases, starting with $1.3B and maintaining Amazon as a minority investor. 🤖 AWS becomes Anthropic's primary cloud and training partner, with Claude models optimized for Amazon's Trainium and Inferentia chips. 🤖 Anthropic is also collaborating with Amazon's Annapurna Labs to develop and optimize next-gen AI processors. 🤖 The move comes amid other massive fundraising efforts from top AI labs, with OpenAI recently raising $6.6B and xAI raising $11B over the past year. Why it matters? The race to the top of the AI industry requires deep pockets, and Amazon is betting on Anthropic to help secure its foothold in the space. Anthropic gets the resources and distribution needed to compete with OpenAI and other AI leaders, while Amazon boosts its chip ambitions to compete with NVIDIA. For years, Big Tech was the epitome of the capital-light business model, driving profits from intangible assets like software. Now, the tech giants are pouring billions into physical stuff, including massive data centers and custom chips. The four tech giants - #Amazon, #Microsoft, #Meta, and Alphabet Inc. - spent nearly a combined $60 billion on capital investments in Q3, up 59% from last year. By the end of 2024, this figure is expected to surpass a total of $200 billion, with Amazon leading at $75 billion — most of which supports Amazon Web Services (AWS) and its AI business. AWS, while accounting for just 16% of Amazon’s revenue in 2023, generated two-thirds of the company’s operating profit. Amazon’s spending spree shows no signs of slowing, with the company expecting to splurge even more in 2025. In the latest earnings call, CEO Andy Jassy called the company’s relentless spending a “once-in-a-lifetime type of opportunity.” #artificialintelligence #CAPEX #technology #data #tech #nasdaq #ecommerce #ppc #VR #AR #investment Source: Chartr

Every industry eventually learns the same lesson: Transactions record history. Behavior reveals truth. In banking, transaction history doesn’t prevent fraud -  behavioral patterns do. How money moves, what deviates, how usage evolves. In aerospace, the "Digital Twin" wasn't built to study design, it was built to study operation. The gap between “as designed” and “as flown” is where performance truth emerges. Fashion is now confronting this same inflection point. For a decade, the industry optimized for the checkout. It scaled e-commerce, refined CRM, and mastered performance marketing. It built extraordinary supply chains and powerful storytelling engines. But the consumer journey has become more complex, and control over the customer relationship has shifted. According to Coresight Research, 70% of consumer behavior data lives outside direct brand ownership. Discovery happens on one platform. Purchase may happen on another. Marketplaces observe cross-brand patterns. Social platforms shape influence. Resale captures the second life. Insight has become highly fragmented. When data fragments, control fragments. Customer acquisition costs are rising. Retention feels less predictable. Price increases are meeting resistance. Brands are leaning more heavily on concentrated high-value customers while aspirational segments behave differently than they did even a few years ago. In a market where products can be copied, pricing can be matched, and marketing replicated, the only advantage that compounds is an intimate understanding of behavior. Financial services, media, and aerospace all made the leap from transaction records to behavioral infrastructure. Fashion is at the threshold of that same transition. The future of fashion won’t be decided at the checkout. It will be decided by who understands behavior. #Business #FashionTech #Retail #DataStrategy #DigitalTransformation

“AWS’ AI business is a multibillion-dollar revenue run rate business that continues to grow at a triple-digit year-over-year percentage and is growing more than 3x faster at this stage of its evolution as AWS itself grew, and we felt like AWS grew pretty quickly.” “Our AI business is on track to surpass an annual revenue run rate of $10 billion next quarter, which will make it the fastest business in our history to reach this milestone.” Those quotes from Amazon & Microsoft last week underscore the dramatic transformation in cloud growth rates. Across the 3 major clouds, the growth rates have increased between 27% and 58% from their nadir about a year ago. But the businesses are 60% bigger today than they were the last time they touched those growth rates. Plus the operating margins of these companies is massive at around 40% for the top two. GCP’s is the lowest, but accelerating rapidly. It was 3.1% last year. Microsoft & others have said their growth is limited by GPUs which will continue until late next year. Amazon & Google are developing their own chips : “As customers approach higher scale in their implementations, they realize quickly that AI can get costly. It’s why we’ve invested in our own custom silicon in Trainium for training and Inferentia for inference. The second version of Trainium, Trainium2, is starting to ramp up in the next few weeks and will be very compelling for customers on price performance.” And internally, the impacts are real. Google said 25% of new code written is AI generated. AWS quantified it further : “The team has added all sorts of capabilities in the last few months, but the very practical use case recently shared where Q Transform saved Amazon’s teams $260 million and 4,500 developer years in migrating over 30,000 applications to new versions of the Java JDK.” All of these advances are expensive: “We expect to spend approximately $75 billion in CapEx in 2024. The majority of the spend is to support the growing need for technology infrastructure.” In total, these hyperscalers invested about $52b last quarter in data centers & GPUs. But the chips are now valuable for longer than they were (again from AWS). “We made the change in 2024 to extend the useful life of our servers. This added about 200 basis points of margin year-over-year.” The most important metric for these businesses will be profit dollars per GPU dollar cost. Which chip design will produce the best profits : Google’s TPUs, Amazon’s Inferentia/Tranium, or Microsoft’s Maia and Cobalt? It’s hard to calculate exactly this figure because the public data isn’t granular enough to compare across the three. But over time we should be able to infer major differences.