Mobile Optimization For Ecommerce Websites

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.

The 2025 Worldpay Global Payments Report is out, and it’s a must read for anyone who wants to understand #payments. These are my highlights. 1. The evolution of Digital Payments (DP): —    DP grew from 34% of e-com value in 2014 to 66% in 2024. —    In POS DP grew from 3% to 38% in the last decade. —    DP will account for 79% of global e-com value and $8.6 trillion in online spend by 2030. —    The no of smartphone users grew 4.5 times in the last decade to 4.2 billion (6.1 billion estimate by 2029). 2. Global #ecommerce trends: —    The value of global e-com transactions grew more than sixfold from 2014 to 2024. —    Global e-com growth continues to decelerate from the pandemic all-time high (10% during last year). —    Global online spending is now at $6.8 trillion and will exceed $10.8 trillion by 2030 (8% CAGR). —    E-com now accounts for 15% of all C2B payments (to reach 19% by 2030). —    Mobile’s share of global e-com tripled from 19% in 2014 to 57% in 2024. 3. Global POS trends: —    Digital wallets’ share of POS transaction value rose more than 10X in a decade, from 3% in 2014 to 32% in 2024. —    By 2030 25% of all in-person shopping will be done via mobile devices ($25 trillion vs 14.2 trillion in 2024 and vs $1.2 trillion in 2014). —    Cash share fell from 44% of global POS transaction value in 2014 to 15% in 2024. This represents a $10.5 trillion value reduction in 10 years. 4. Digital wallets (DWs): —    DW value grew ~10X from $2.3 billion in 2014 to $342 billion in 2024. —    DWs accounted for more than a third of global C2B spending in 2024 – over $15.7 trillion. —    By 2030, combined consumer DW spending will exceed $28 trillion, more than the USA GDP in 2023, at $27.7 trillion the world’s largest. 5. Buy-Now-Pay-Later (#BNPL): —    Global BNPL online value will grow at 9% CAGR through 2030 to ~$580 billion (vs just $2.3 billion e-com value in 2014). —    BNPL innovators like Affirm, Afterpay, Klarna, and PayPal disrupted traditional finance. —    Banks and card networks rode the BNPL wave via installment offerings. 6. Cards are as relevant as ever: —    Card networks continue to successfully withstand competition via innovation (i.e. ClicktoPay, flexible credentials, installments). —    Cards seemingly lose market share to DWs (from 56% to 32% in e-com spend in the last decade), but most wallet spending (56%) is done through cards. —    Cards account for nearly two-thirds (65%) of 2024 consumer spending ($29 trillion). 7. Real-time A2A payments as critical infrastructure: —    Global A2A value is forecast to near $3.8 trillion by 2030. —    India (UPI) and Brazil (Pix) in the lead. Driven by Pix, A2A e-com payment value in Brazil jumped from $1 billion in 2014 to $35 billion in 2024. —    The next would-be disruptors include FedNow, Paze and Wero. Summary: Panagiotis Kriaris, source: Worldpay Global Payments Report 2025 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

Gartner has just released its 2024 Magic Quadrant for Digital Commerce Platforms—a must-have resource for evaluating the top solutions in the market. This report categorizes vendors into Leaders, Challengers, Visionaries, and Niche Players, based on their ability to execute and their strategic vision. Why is it worth considering? The Magic Quadrant helps businesses identify innovative and reliable platforms, reducing risks and maximizing ROI in digital commerce strategies. Here are five platforms from the report that caught my attention: Salesforce: A leader known for its global reach and native integrations, perfect for large B2C and B2B enterprises. Robust capabilities, but its monolithic architecture can be a challenge. Shopify: Great for quick launches with easy setup and omnichannel support. However, its advanced features and pricing may limit scalability for large companies. commercetools: A modular and scalable option, ideal for mature, high-volume businesses. While highly innovative, its implementation can be complex. VTEX: A strong choice for businesses combining B2B and B2C. Its composable, modular architecture enables flexibility, though native customization is limited. BigCommerce: Perfect for mid-market companies needing flexibility. Its cloud-native architecture is modern and composable, but its global reach is still developing. There’s no one-size-fits-all solution in digital commerce. Digital leaders need to conduct a thorough analysis to select the platform that best aligns with their unique business needs.

🚨 𝐇𝐨𝐰 𝐝𝐨𝐞𝐬 "𝐌𝐞𝐫𝐜𝐡𝐚𝐧𝐭 𝐨𝐟 𝐑𝐞𝐜𝐨𝐫𝐝" (𝐌𝐨𝐑) 𝐰𝐨𝐫𝐤 𝐢𝐧 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 — by Solidgate 👇 The Merchant of Record (MoR) model plays a crucial role in simplifying global commerce. For businesses operating across multiple markets, MoR acts as the legal and financial intermediary that takes on the responsibility of selling to end customers. Instead of every seller navigating compliance, tax, and payment complexity independently, an MoR assumes these responsibilities — making expansion faster, leaner, and compliant. — 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐭𝐡𝐞 𝐌𝐨𝐑 𝐌𝐨𝐝𝐞𝐥? ► The MoR is the entity legally responsible for processing transactions and delivering goods/services to end customers. ► It manages payment acceptance, compliance, taxes, and chargebacks — so sellers can focus on scaling rather than building regulatory and financial infrastructure. — 𝐇𝐨𝐰 𝐃𝐨𝐞𝐬 𝐌𝐨𝐑 𝐖𝐨𝐫𝐤? 1️⃣ The seller sells products/services to the MoR. 2️⃣ The MoR processes customer payments, ensuring tax, compliance, and local regulations are covered. 3️⃣ End customers purchase from the MoR — not directly from the seller. 4️⃣ The MoR pays out the net amount to the seller after deducting taxes, fees, and associated costs. — 𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐨𝐟 𝐚 𝐌𝐨𝐑 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫: → 𝐏𝐚𝐲𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 – Accepts, settles, and reconciles transactions globally. → 𝐓𝐚𝐱 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞 – Calculates, collects, and remits local sales/VAT taxes. → 𝐑𝐢𝐬𝐤 & 𝐂𝐡𝐚𝐫𝐠𝐞𝐛𝐚𝐜𝐤 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 – Absorbs liability for fraud, disputes, and regulatory breaches. → 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 – Ensures fulfillment obligations are tied to the MoR entity. → 𝐑𝐞𝐜𝐨𝐧𝐜𝐢𝐥𝐢𝐚𝐭𝐢𝐨𝐧 – Consolidates fees, FX, and payouts into a simplified structure for the seller. — 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐌𝐨𝐑 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫𝐬: 𝐅𝐮𝐥𝐥-𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐏𝐚𝐲𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫𝐬 – Solidgate, Paddle, Stripe Atlas 𝐌𝐚𝐫𝐤𝐞𝐭𝐩𝐥𝐚𝐜𝐞 & 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐌𝐨𝐝𝐞𝐥𝐬 – App stores (Apple App Store, Google Play) or eCommerce Platforms (Amazon, Shopify, Apple). — 𝐃𝐨𝐰𝐧𝐬𝐢𝐝𝐞𝐬 𝐨𝐟 𝐌𝐨𝐑: ⚠️ Reduced control over direct customer relationships. ⚠️ Dependency on the MoR for revenue collection and reconciliation. ⚠️ Potentially higher fees due to bundled compliance, risk, and tax services. — 𝐖𝐡𝐞𝐧 𝐢𝐬 𝐌𝐨𝐑 𝐍𝐞𝐞𝐝𝐞𝐝? → Digital platforms entering new geographies with strict tax & compliance requirements. → SaaS companies selling subscriptions globally without establishing local entities. → Marketplaces or gig platforms processing payments on behalf of thousands of sellers. As global commerce accelerates, Merchant of Record models are becoming essential enablers for cross-border scale, handling quietly the heavy lift of payments, compliance, and risk. — Source: Solidgate ► Subscribe to 𝐓𝐡𝐞 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐁𝐫𝐞𝐰𝐬 ☕: https://lnkd.in/g5cDhnjC ► Connecting the dots in payments... | Marcel van Oost

If you are running App campaigns on Meta, you should know this. Till 2021, Meta used to share the last-click level data for all your app installs. i.e., you get the details on any install's last-click time, location, and many more, as the data in your MMP. You can download this data from your MMP and use it to build models for ROAS, LTV, and fraud detection. Meta has referred to it as Advanced Mobile Measurement (AMM). However, they stopped it in 2021 in response to Apple's App Tracking Transparency. After stopping AMM, they only shared the aggregate with MMP. You will only get to see how much each source contributed to App installs. Now they are back. Last week, Meta announced that it will restart AMM this month. Interestingly, they will also start sharing the engaged view(leading to conversion) data as part of this from July 21st. One of the use cases for this data is in App fraud detection, specifically identifying parasitic ad networks. These ad networks detect when users click on Meta ads and generate a malicious click immediately after the Meta click, before the installation, thereby taking the installation attribution. We developed a parasitic ad network fraud detection rule for Google in 2022, utilizing UAC clickstream data while I was with Unacademy. It helped us save 20% of our Ad network budget without affecting the scale of new user acquisition. With AMM being available, now you can do the same for Meta as well. ♻️ Repost if you think this will be useful for your connection & followers. 🙏🏼

Children's information and sharing it is top of mind for regulators, as we have been telling our clients for a while, and as we saw yesterday in a new CA AG $500,000 settlement with Tilting Point Media LLC (Tilting Point) for #CCPA and #COPPA compliance issues in mobile app game “SpongeBob: Krusty Cook-Off.” Practice points: Directed at children: 🔹 If you are aware that children under 13 are using your services - they are is directed to children. Saying in your terms of service and privacy policy that consumers under 13 are not authorized to use it - doesn't change this. Regulator 1, 2, 3: 🔹 CA AG will use every enforcement tool to ensure compliance with the law and that companies exercise diligence with privacy law requirements 🔹 If one regulator tells you that you are not compliant (here BBB National Programs CARU): assess your compliance with other laws you could be enforced against by another regulator Data minimization: 🔹 Don't collect more personal information than reasonably necessary for a child to participate. Mind your SDKs: 🔹An SDK facilitates data sharing that can be a sale (CCPA) and/or unfair/deceptive (FTC) and/or subject to COPPA just like any data sharing. 🔹 You need to know: what information each SDK collects; evaluate contracts re: sharing of data through them - making sure you have the right consent. 🔹 You may need a formal SDK governance framework. 🔹 Every year: assess data minimization and SDK usage. (ensuring data flows appropriately change based on the consumer's age). 🔹 Every year: conduct adequate training for personnel re sharing and SDKs Sale/share: 🔹 Disclose your sale and share correctly in your privacy notice 🔹 Don't sell/share personal information of under 13's without parental consent 🔹When you do sell/share: provide a just-in-time notice explaining what information is collected, the purpose, sale/share, link to privacy policy, & parental or opt-in consent required. [FTC also says this in BetterHelp] Mixed audience 🔹When using an age screen it has to be neutral. 🔹Neutral means: (1) ask age information in a neutral manner that does not default to a set age of 16 or above or encourage users to falsify age information; (2) not suggest that certain features will not be available; and (3) provide CLEAR AND CONSPICUOUS notice that the age entered should be accurate to the user and is collected to ensure data use and advertising is appropriate. 🔹If the person is under 13 or 16 - direct them to a portion of the service that doesn't use data other than as permitted by COPPA/CCPA or get parental / opt in consent For ads in your apps, make sure they are: 🔹Identified as being an ad; 🔹Include a prominent one-click “X” or “Close” button; 🔹Do not manipulate or deceive consumers into engaging 🔹Do not advertise activities/products in which children cannot legally engage/possess. #dataprivacy #dataprotection #privacyFOMO Complaint: https://rb.gy/enu19e Agreement: https://rb.gy/jq6lke

A sluggish API isn't just a technical hiccup – it's the difference between retaining and losing users to competitors. Let me share some battle-tested strategies that have helped many  achieve 10x performance improvements: 1. 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 Not just any caching – but strategic implementation. Think Redis or Memcached for frequently accessed data. The key is identifying what to cache and for how long. We've seen response times drop from seconds to milliseconds by implementing smart cache invalidation patterns and cache-aside strategies. 2. 𝗦𝗺𝗮𝗿𝘁 𝗣𝗮𝗴𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Large datasets need careful handling. Whether you're using cursor-based or offset pagination, the secret lies in optimizing page sizes and implementing infinite scroll efficiently. Pro tip: Always include total count and metadata in your pagination response for better frontend handling. 3. 𝗝𝗦𝗢𝗡 𝗦𝗲𝗿𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 This is often overlooked, but crucial. Using efficient serializers (like MessagePack or Protocol Buffers as alternatives), removing unnecessary fields, and implementing partial response patterns can significantly reduce payload size. I've seen API response sizes shrink by 60% through careful serialization optimization. 4. 𝗧𝗵𝗲 𝗡+𝟭 𝗤𝘂𝗲𝗿𝘆 𝗞𝗶𝗹𝗹𝗲𝗿 This is the silent performance killer in many APIs. Using eager loading, implementing GraphQL for flexible data fetching, or utilizing batch loading techniques (like DataLoader pattern) can transform your API's database interaction patterns. 5. 𝗖𝗼𝗺𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 GZIP or Brotli compression isn't just about smaller payloads – it's about finding the right balance between CPU usage and transfer size. Modern compression algorithms can reduce payload size by up to 70% with minimal CPU overhead. 6. 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻 𝗣𝗼𝗼𝗹 A well-configured connection pool is your API's best friend. Whether it's database connections or HTTP clients, maintaining an optimal pool size based on your infrastructure capabilities can prevent connection bottlenecks and reduce latency spikes. 7. 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗟𝗼𝗮𝗱 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 Beyond simple round-robin – implement adaptive load balancing that considers server health, current load, and geographical proximity. Tools like Kubernetes horizontal pod autoscaling can help automatically adjust resources based on real-time demand. In my experience, implementing these techniques reduces average response times from 800ms to under 100ms and helps handle 10x more traffic with the same infrastructure. Which of these techniques made the most significant impact on your API optimization journey?

“70% of our marketing time is spent on recovering abandoned carts. On WhatsApp.” That was the single biggest takeaway from a customer call yesterday, for me. A French retailer selling bespoke fashion worldwide. Here’s what they told me: "WhatsApp messaging isn’t cheap. Everybody knows that. But we believe in the channel. We know it’s our best shot at being seen. At being heard. At carving a space right where our customers live, next to their friends and family.” So they stopped treating abandoned cart reminders like afterthoughts. Instead, they built campaigns that command attention. And I’ve never seen anything like them. 🔥 Campaign #1: The After-Dark Discount Window Instead of sending a routine cart reminder, they unlock a private discount window at 10 PM. Why? Because late-night browsing isn’t rational, it’s emotional. Customers who opt-in get an exclusive deal during this nocturnal shopping spree. 💰 Campaign #2: Shoppers Name Their Price They don’t shove a price at the customer. They hand over the pricing power. Shoppers reply with a price they’re willing to pay. If it falls within range, it’s approved. This campaign has the highest engagement numbers I’ve EVER seen on WhatsApp. 🎥 Campaign #3: Staff Wearing the Carted Item Forget static product images. They broadcast videos of staff members wearing the item, describing the fit and fabric. It kills doubts. It brings the product to life. It makes buying feel effortless. For every $1 spent on WhatsApp cart recovery, they make $30 back. Why? Because they treat every abandoned cart like a full-fledged marketing campaign. No lazy nudges. No generic messages. Every interaction, memorable. WhatsApp marketing is wildly profitable—if you refuse to take shortcuts

Boosting API Performance: Best Practices and Techniques Improving API performance often involves a combination of strategies and techniques. Here are some methods to enhance API performance, focusing on pagination, asynchronous logging, connection pooling, caching, load balancing, and payload compression: 1. Pagination:   Implement server-side pagination to limit the amount of data transferred in a single request/response. Allow clients to request a specific page or range of data.   Use query parameters like `page` and `pageSize` to control the pagination, and ensure your API documentation is clear on how to use it. 2. Asynchronous Logging:   Log asynchronously to avoid introducing latency to API responses. Use a message queue or a dedicated logging service to process logs in the background.   This decouples the logging process from the request/response cycle, improving API responsiveness. 3. Connection Pooling:   Use connection pooling for database and other resource intensive operations. Connection pooling helps efficiently manage and reuse database connections, reducing overhead. 4. Caching:   Implement caching mechanisms to store frequently requested data. Consider using in memory caching systems like Redis or Memcached to speed up data retrieval.   Utilise HTTP caching headers (e.g., `CacheControl`, `ETag`) to instruct clients and intermediaries to cache responses, reducing the load on your API. 5. Load Balancing:   Set up load balancers to distribute incoming traffic across multiple API servers or instances. This ensures even load distribution and redundancy.   Consider using dynamic load balancing algorithms to adapt to changing server loads. 6. Payload Compression:   Compress API responses before sending them to clients. Use popular compression algorithms like GZIP, Brotli, or Zstandard to reduce data transfer times.   Ensure that clients support decompression of compressed payloads. Remember that the effectiveness of these methods depends on the specific requirements of your API and the technologies you are using. Monitoring and performance testing are crucial to fine tune and optimise your API further. Additionally, consider using content delivery networks (CDNs) to distribute static content, and use API gateways to manage and secure your API endpoints effectively.

Most brands underestimate the power of one line. Zomato built an empire on it. Not the app. Not the UI. Not even the discounts. Their biggest growth hack? Notifications. Your phone lights up and instead of a boring “Order food now,” you see: 👉🏻“When you open the fridge and find nothing but disappointment.” 👉🏻“Mood: fries before guys.” It’s short, witty, and ridiculously relatable. You don’t swipe it away. You smile. Often, you click. And order. That’s the genius of Zomato’s strategy  They turned push notifications into content marketing. Here’s why it works: 1️⃣ Context over copy — They don’t just sell food, they sell moods. 2️⃣ Consistency beats campaigns — Dozens of micro-moments a week > one ad film. 3️⃣ Entertainment = engagement — By making people laugh, they earned permission to market daily without feeling spammy or salesy. Deepinder Goyal has always pushed for Zomato to have a voice that feels human, witty, and instantly shareable.  That founder-led vision is why their messaging feels less like “marketing” and more like a conversation. And here’s what every D2C founder should note: Zomato processes 2 million+ orders a day — many triggered by these tiny nudges. Their notifications aren’t a side tactic. They’re a revenue engine. Great branding isn’t about louder ads or bigger spends. It’s about creating consistent touchpoints so simple that they feel invisible,  yet powerful enough to influence behaviour at scale. Because the brands that delight people in the mundane moments are the ones they remember when it matters. Zomato isn’t just an app anymore. It’s a daily conversation. And that’s the power of brand positioning done right. If you’re building in a crowded space and want positioning that actually converts attention into loyalty — DM me “BRAND.”