Interactive Ecommerce Features

Returns and exchanges are not just operational necessities – they sit at the intersection of customer experience, revenue flow, and efficiency. As businesses scale globally, managing these high-volume and often complex processes becomes increasingly challenging. AI is starting to play a pivotal role here – bringing speed, accuracy, and intelligence into everyday operations.   In this video, Henkel’s Dimitri Lerner shares how their collaboration with SAP Customer Innovation Services is helping reimagine returns and exchanges management.   Together, we are co-developing an AI-assisted solution that: Automates document interpretation Accelerates dispute resolution Provides real-time visibility across markets   By embedding AI directly into operational workflows, the solution reduces manual effort, improves accuracy, and enables faster, more responsive engagement with customers and partners. The highlight of this collaboration is customer-specific innovation, applying AI in ways that are deeply aligned to business processes, data, and industry context.    Watch it here: https://lnkd.in/gcC78SnT Thomas Saueressig   SAP  #CustomerStory #Testimonial

PUMA Group's Shanghai activation shows how neuroscience drives modern retail success. Here's the blueprint: PUMA transformed West Bund Dream Center into a racing district (Dec 20-22). Racing garages, pit stops, and floor-to-ceiling tracks created an arcade-like atmosphere. Visitors became drivers - collecting tokens, earning certificates, competing in challenges. The Psychology: Dopamine Triggers: Gaming mechanics and achievement systems create reward cycles Social Currency: Photo ops at "gas stations" and shareable driver credentials generate organic content Premium Positioning: Racing aesthetic aligns with high-end retail expectations Digital Integration: Tmall Heybox partnership extends reach beyond physical space Smart Product Integration: - New Speedcat colorways displayed as racing gear - Rosé's silver jacket placement creating style touchpoints - Gaming rewards include exclusive PUMA merchandise Business Impact: - Deeper engagement through gameplay mechanics - Higher social sharing through engineered moments - Product drops positioned as achievements - Brand elevation through premium experience design The Evolution: Building on September's Douyin collaboration, PUMA creates retail spaces that drive neural engagement and social proof simultaneously. This model transforms customers into brand advocates through shared experiences and status signaling. Credits: Puma #Retail #Experiencedesign #Marketing #China Thoughts on gamified retail? Share your experiences! 🎮🛍️

🟢 Roblox lets users buy real-world items directly from the platform using Shopify's checkout system 👇 Shopify brands will soon have access to Roblox's huge audience of nearly 80 million daily active users, offering a new channel to boost sales & connect with the community. 🛍 Users aged 13 and older will be able to purchase physical items like clothing and accessories through Roblox. Players can interact with virtual versions of these items, which will open a Shopify checkout page where they can view product pictures, choose sizes/colors and complete their purchase using the same payment methods as on regular e-commerce. 📅 The integration is expected to pilot soon, with a wider roll-out planned for early 2025. 💳 This partnership not only creates new ways for creators & brands to generate revenue through Roblox, but also changes how transactions work on Roblox. For the first time, players will be able to buy (physical) goods using their real currency -instead of Robux- without leaving the game. 🚀 This opens up possibilities for developers to sell a wide range of products from different retailers. I can immediately think of 3 new business models coming to life on the back of tthis partnership. ❶ Virtual branded stores: brands set up their virtual stores in popular Roblox games to sell (virtual &) physical items, driving both in-game and real-world sales. ❷ Creator collaborations: popular Roblox creators partner with brands to design and sell limited-edition digital and physical goods, boosting engagement and exclusivity. ❸ Gamified shopping quests: users complete in-game challenges to unlock discounts or exclusive physical products. 📊 The financial details, including commission rates, haven't been disclosed. However, this move is part of Roblox's broader efforts to grow its e-commerce capabilities and offer more ways for creators/brands to earn money. ➡️ In summary, the new partnership between Shopify & Roblox is expected to bring gaming & shopping closer together. Will this be the future of shopping? #innovation #roblox #ecommerce #retail #shopify #phygital #commerce #business

After 6 years in Germany, I am still struck at how crucial Easter is for grocery retail. Germany still closes grocery stores on Sundays, AND on public holidays. The stretch from Good Friday to Easter Monday therefore sees shops closed 3 of 4 days. No shopping on Friday, Sunday, or Monday. All while families gather and folks prepare more meals at home. What does that mean?
The Thursday before Easter is a must-win for grocers. Larger volume, bigger baskets –– Thursday is the biggest spend day of the year for grocery. That also justifies a more aggressive spend on incentives & marketing, given the size of the prize. And so, every major grocer is very visible right now. Especially Lidl in Germany, which has been leaning in with gamified messaging driving traffic to their Lidl Plus app. They're even making in-app games the centerpiece of their out-of-home advertising. We regularly find that gamification increases three things: 👀 Conversion ↳ CTAs with gamification get higher click through, downloads, etc. ✅ Engagement ↳ Gamified experiences see greater engagement & completion. 💸 Redemption ↳ Won / earned rewards see a drastically higher redemption rate. When I played the Lidl Easter game today, I got €5 off a €50+ basket. That is a really juicy reward in grocery! But it could be a slam-dunk ROI for Lidl if it does three things… → Gets me to come in and do my €100+ pre-Easter shop at Lidl instead of a competitor → Cements Lidl as my go-to grocery for larger baskets  → Drives lots of app downloads / engagement Simple mechanics, clear value, a fun experience… Given the higher conversion, engagement, and redemption gamification drives, I think it's a winning playbook 🐰

Here’s something most retail brands are finally waking up to: What works at one store might totally flop just 10 km away. I’ve seen this first-hand. Back when I was at Reliance Retail, heading marketing for 170+ stores across 30 cities, we had a dedicated budget for local store marketing. But this wasn’t centrally planned. We encouraged local store teams to take the lead, to understand their micro-market and suggest activities that would grow awareness in their communities. From sponsoring local events, eye check up camps at housing societies & corporates, organising in-store promotions tied to local holidays or festivals, or even collaborating with nearby businesses for cross-promotions, we did everything to reach the people closest to us. Even when marketing our malls, we follow the same philosophy. Hyperlocal marketing helps us connect with our hyper-primary catchment—the people most likely to visit, shop, and return. And that lesson carries over just as powerfully to online retail today. Online retail is playing on the same turf now. D2C brands are using geotargeting campaigns, collaborating with local influencers, offering region-specific discounts, and running ads in local languages. In both worlds, today, physical and digital, local context wins attention. And often, loyalty too. Because today, success doesn’t come from being everywhere. It comes from being right where it matters most. Have you spotted a hyperlocal campaign that made you stop and take notice, online or offline? #marketing #retail #hyperlocal #branding

Exciting breakthrough in e-commerce recommendation systems! Walmart Global Tech researchers have developed a novel Triple Modality Fusion (TMF) framework that revolutionizes how we make product recommendations. >> Key Innovation The framework ingeniously combines three distinct data types: - Visual data to capture product aesthetics and context - Textual information for detailed product features - Graph data to understand complex user-item relationships >> Technical Architecture The system leverages a Large Language Model (Llama2-7B) as its backbone and introduces several sophisticated components: Modality Fusion Module - All-Modality Self-Attention (AMSA) for unified representation - Cross-Modality Attention (CMA) mechanism for deep feature integration - Custom FFN adapters to align different modality embeddings Advanced Training Strategy - Curriculum learning approach with three complexity levels - Parameter-Efficient Fine-Tuning using LoRA - Special token system for behavior and item representation >> Real-World Impact The results are remarkable: - 38.25% improvement in Electronics recommendations - 43.09% boost in Sports category accuracy - Significantly higher human evaluation scores compared to traditional methods Currently deployed in Walmart's production environment, this research demonstrates how combining multiple data modalities with advanced LLM architectures can dramatically improve recommendation accuracy and user satisfaction.

Most restaurants discount. Dishoom gamified. Many people know Dishoom for its food. In fact, the last time my wife and I were in Edinburgh, it was perhaps the best meal we had. But today, I want to share something different. Instead of taking 15–20% off every meal, Dishoom gamified the bill: roll a dice, and you might get the entire meal for free. At first glance, the maths looks similar. A 1-in-6 chance of a free meal roughly equates to a ~16–17% expected discount. But behaviourally, it is not even close. First, it quietly lifts average spend. When customers believe they might win, they become less price-sensitive. More importantly, few want to “win” a free meal that felt mediocre. The upside feels more meaningful if the bill is larger. So they order the extra dish, the better cut, the dessert. Not consciously, but consistently. Second, it exploits the fact that people are not rational calculators of expected value. A guaranteed 1/6 discount feels mundane. A small chance of getting everything for free feels exciting. The perceived upside is amplified; the probability is discounted. Third, it transforms a cost into theatre. Payment is usually the worst part of the dining experience. Here, it becomes the peak moment. Even those who “lose” still remember the experience positively. And no, our meal was not discounted. The result is outsized returns relative to the same economic cost: Higher average spend Stronger memorability Organic word-of-mouth Compare that to simply lowering prices by 1/6th. You may get none of the above. Just thinner margins. This is the broader lesson. If you are going to give value away, do not just discount it. Design how it is experienced.

I know it's tempting... but loyalty programs don't have to be the default paint-by-numbers points, tiers, and refer-a-friend. Here are four interesting loyalty plays that have caught my eye in the past week. Adore Beauty Group changed its program from Adore Society to Adore Rewards to move beyond being online-only. Surprise, surprise, it included a quarterly gift box, but the differentiator to the MECCA Brands loyalty masterclass is that customers get to choose their products rather than it being a mystery. McDonald's partnered with Snap Inc. to allow MyMcDonald's users to redeem points for a month of Snapchat+. It's the first time they've done a digital subscription redemption. Very smart lifestyle integration and huge trial opportunity for Snapchat+. Costco Wholesale upgraded its top-tier Executive Membership. It costs $120 USD, but Executive customers can access the store one hour earlier than other customers and an hour later on Saturday. Plus 2% cash back. A brilliant combination of convenience with middle-class exclusivity. Walmart rewarded pre-orders of the Nintendo Switch by ensuring all orders were delivered by 9am on launch day... and included surprise Pringles and Cokes. At such a heightened and anticipated moment, that retailer has left an deep emotional footprint. So next time you think loyalty, don't settle for ordinary. Put yourself in your customers' shoes. Think outside of the normal. Create lasting value and impactful moments. Don't expect to turn tech on and loyalty to happen. If worse comes to worst... add Pringles to all orders.

𝗔𝗜 𝘄𝗶𝗹𝗹 𝗻𝗼𝘄 𝗵𝗮𝗻𝗱𝗹𝗲 𝘆𝗼𝘂𝗿 𝗿𝗲𝗳𝘂𝗻𝗱 𝗿𝗲𝗾𝘂𝗲𝘀𝘁𝘀 𝗮𝘁 𝗔𝗶𝗿 𝗜𝗻𝗱𝗶𝗮 Air India is deploying Salesforce's Agentforce, autonomous AI agents that will handle their entire refund process from start to finish. I was skeptical at first. I mean this is Air India we're talking about - not exactly synonymous with cutting-edge customer service. Then I looked closer at what they're actually doing: → They identified their most painful customer friction point (refunds). → They're automating the ENTIRE process end-to-end. → They're starting small, proving the concept, then expanding to voice. Here's why this matters for every business leader: Most companies use AI to make bad processes slightly faster. Air India is using it to fundamentally reinvent the customer experience. What's fascinating is how they're approaching this - not with massive, risky transformation, but with a targeted strike at their biggest pain point. For Air India, this could be the difference between surviving and thriving in an ultra-competitive market. For the rest of us, it's a masterclass in pragmatic AI transformation.

You click "play" on Netflix. In 200 milliseconds, a recommendation engine just processed millions of videos. Most ML engineers know these systems exist. Few understand what's actually running under the hood. I spent the last 6 months building a complete deep-dive series on production recommendation systems — from first principles to the exact architectures running at YouTube, Spotify, and TikTok. Here's the complete roadmap: 🎯 Foundation Layer 1️⃣ RecSys Fundamentals — Content-based, collaborative filtering, and hybrid approaches that power every modern recommender 2️⃣ How Recommendation Systems Learned to Think — The evolution from matrix factorization to transformer-based generative agents ⚡ Retrieval & Ranking Pipeline 3️⃣ The 3-Stage Funnel — How two-tower models, vector databases, and cross-encoders work together at scale 4️⃣ How YouTube Finds Your Next Video in Milliseconds — Two-tower retrieval, in-batch negatives, and the engineering tricks that make it work 5️⃣ Vector Search at Scale — IVF, PQ compression, and making 100M+ vector search actually possible in production 6️⃣ From Candidates to Clicks — The complete ranking stack: from 1,000 candidates to the one item you actually tap 🔧 Production Reality 7️⃣ Solving the Cold Start Problem — Contextual bandits, meta-learning, and LLMs for new users and items (how Spotify, TikTok, YouTube do it) 8️⃣ Beyond Ranking — How diversity, freshness, and business constraints turn a ranked list into a product-ready feed Every post includes: → Production architecture diagrams → Real code examples (PyTorch, Faiss, ranking models) → Case studies from actual systems → The engineering tradeoffs that matter Full series: https://buff.ly/GKEvulv If you're building RecSys or joining a team that does — this is your blueprint.