Retail Technology Tools

I build dashboards backwards. And they work 3x better than the "right" way. Last year, a retail client asked for a "comprehensive analytics dashboard." They had a 47-page requirements doc. Every metric you could imagine. I threw it in the trash. Instead, I asked one question: "What decision do you make every Monday morning?" "Whether to restock our top 10 SKUs," the CEO said. That's it. That became the entire dashboard. One number: Days of inventory remaining. One visual: Red/yellow/green by SKU. One button: Generate purchase order. The data team was horrified. "Where's the YoY comparison? The regional breakdowns? The predictive models?" Here's what happened: **Traditional approach (their previous dashboard):** • 6 weeks to build • 23 different views • Used 4 times in 3 months • Zero decisions changed **My backwards approach:** • 3 days to build • 1 view • Used 5 times per week • Prevented 2 stockouts in first month alone The difference? I started with the decision, not the data. Most dashboards fail because we build what's possible, not what's needed. We show off our technical skills instead of solving business problems. My backwards process: 1. Identify the decision (not the data) 2. Find the minimum viable metric 3. Make the action obvious 4. Stop. Just stop adding things. That retail client? They saved $50K in lost sales from stockouts in Q1. Not because of fancy analytics. Because someone could actually use the damn thing. The best dashboard isn't the one with the most features. It's the one that gets opened every morning. What's the one metric that actually drives your business decisions? #DataVisualization #DashboardDesign #BusinessIntelligence #DataStrategy #PowerBI

How can retailers activate in-store experiences that can scale efficiently and measure incremental impact? 🤝 In-store media requires cross-functional collaboration across marketing, merchandising, and retail media teams. Merchant alignment is essential to ensure in-store media supports broader category goals, promotions, and pricing strategies. However, fragmentation between teams often leads to inconsistent execution. 💰 High upfront investment in digital screens, infrastructure, and maintenance makes scalability a challenge. Retailers must balance technology costs with expected ROI. Additionally, ensuring planogram compliance and optimizing store layouts for maximum visibility and shopper impact requires coordination across teams. 📊 In-store media success is evaluated through POS data, sales lift analysis, customer sentiment surveys, and match market tests. These methods help brands understand the impact on purchasing behavior, optimize budgets, and refine in-store strategies. 🐢 Crawl Phase: Retailers should pilot technologies, gather initial data, and build a scalable business model while training teams and refining measurement approaches. Early-stage collaboration with merchants ensures that in-store media aligns with overall store operations and merchandising priorities. 🚶 Walk Phase: Use data insights to optimize content, improve store-level targeting, and scale successful pilots. Refining planograms and integrating in-store media with category management strategies help maximize effectiveness. Introduce advanced features like interactive displays, mobile integration, and AI-driven recommendations to enhance engagement. 🏃 Run Phase: Fully integrate online and in-store strategies to create seamless in-store experiences that can measure omnichannel impact. Collaborate closely with merchants, store operations, and category managers to ensure store layouts, promotions, and digital touchpoints work together.

I'm excited to share my latest data analytics project: a comprehensive Retail Performance Analysis Dashboard. Problem: The retail company struggled with a lack of clear insights, making it difficult to track overall performance, understand customer behavior, and manage inventory efficiently. Solution: I developed and deployed an interactive, end-to-end Power BI dashboard. By connecting directly to SQL databases, the solution provides a real-time, holistic view of the business, analyzing key KPIs like sales, profit margins, customer segmentation, supplier performance, and stock health. 📊 Tools Used: Power BI | SQL | Excel | DAX | Data Modeling 💡 Key Insights & Highlights: • Total Sales: ₹5.34M • Profit Margin: 28.77% • YoY Sales Growth: 23.48% • Top Performers: The North Region (₹1.52M) and the supplier "Boat" (₹1.1M) were the primary drivers of sales. • Operational Health: Maintained a 65% delivery rate against a 9.17% return rate. • Actionable Inventory: Identified 3 critical products as "Low Stock" (Stock = Reorder Level), flagging them for immediate re-purchasing. Dashboard Link: https://lnkd.in/gHTPaTce #PowerBI #SQL #DataAnalytics #BusinessIntelligence #Dashboard #DataVisualization #RetailAnalytics #DataInsights

Did you know that 95% of urban holiday shoppers in India research products online before visiting a store? The question for luxury brands is: How do you convert these online visitors into loyal offline customers? For luxury brands, the challenge isn’t choosing between online and offline—it’s blending them to create seamless, personalized experiences that retain the exclusivity and allure of the luxury segment. Here are five strategies luxury brands in India can adopt:   1️⃣ The In-Store Experience Luxury shopping is all about the experience. While not every store can replicate Louis Vuitton (see pics), brands can still focus on creating immersive spaces. 🔵 Design stores as places where customers connect with the brand, not just the products. 🔵 Host art installations, pop-ups, or workshops. 🔵 Enable online fulfilment so customers can explore products in-store and complete purchases later online.   2️⃣ Use Technology Not every brand can afford cutting-edge AR or VR tools, but simpler technologies can also elevate the customer journey. Install tablets or interactive screens to offer customisation options like unique designs or personalised engravings. 3️⃣ Leverage Data Online data, like browsing habits and purchase history, can help create tailored in-store experiences. Imagine a scenario where a customer books an appointment, and the staff has pre-selected items based on their online activity. 🔵 Invest in CRM systems to collect and analyze customer data. 🔵 Train staff to use this data for personalized service. 🔵 Send timely notifications about new arrivals or events that align with customer preferences. 4️⃣ Omnichannel Integration The boundaries between online and offline are increasingly blurred. A customer might discover a product on Instagram, research it on your website, and then visit your store to complete the purchase. 🔵 Interconnect all channels—online and offline—for a unified experience. 🔵 Offer features like appointment booking, product reservations, and virtual consultations. 🔵 Provide flexible options, including in-store pickups and home delivery. 5️⃣ Redefine the Role of Sales Staff In the “phygital” era, sales staff are not just sellers—they are brand ambassadors and trusted advisors. 🔵 Train them to align service with the brand’s online interactions. 🔵 Equip them with tools to access customer profiles and preferences. 🔵 Focus on building long-term relationships rather than closing immediate sales. The future of luxury retail lies in combining the strengths of digital convenience and physical presence. By investing in technology, adopting data-driven personalization, and rethinking store roles, luxury brands can create unforgettable customer experiences that build lasting loyalty. In a world where expectations are constantly evolving, the brands that can master this digital-physical intersection will set the standard for the luxury market of tomorrow. #omnichannelretail #luxuryretail

𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗶𝗻 𝘁𝗵𝗲 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱, 𝗖𝗿𝗮𝗳𝘁 𝗮𝗻𝗱 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗙𝗼𝗿𝗲𝗴𝗿𝗼𝘂𝗻𝗱 I still remember those endless nights in SEPHORA, manually counting thousands of items. That’s why Starbucks’ announcement today resonated so strongly with me. They are rolling out AI-powered automated counting across all their North America coffeehouses: 11k stores. What’s remarkable is the technology mix: 👀 Computer vision to instantly recognize products on shelves. 🔢 3D spatial intelligence to capture placement and quantities. 🪩 Augmented reality overlays guiding partners through the process. 📈 AI analytics that flag low-stock items and will soon automate replenishment orders. The results are striking: ✅ Inventory now counted 8x more frequently. ✅ A process that used to take one hour, now takes minutes. They are reporting a saving of 16,500 hours per week. ✅ Sales people spend less time in the backroom and more time crafting and connecting with customers. Starbucks calls it “technology in the background, craft and connection in the foreground”. And that’s exactly why it matters: technology here is the enabler of efficiency, consistency, and focus on consumer experience. Starbucks is not alone. Walmart with robots scanning shelves, Inditex embedding RFID across its stores, and Amazon Go pioneering frictionless checkout all point to the same truth: the future of retail advantage lies in mastering the invisible backbone of operations. 👉 We’ve moved beyond pilots and “experiments.” AI, AR and computer vision are becoming part of operational infrastructure. Having lived both sides, the manual counts and the promise of automation, I guess this will become the standard for every retailer. #RetailInnovation #AI #AugmentedReality #Operations #CustomerExperience

AI is changing how we shop and how retail jobs are done. More than 15 million Americans work in retail (BLS). It’s one of the largest sectors in the economy and one where both consumers and frontline workers are starting to interact with AI in real ways. As the 2025 holiday season is in full swing, Rachel Brown on my team looked at new data on how AI is showing up in retail: from what shoppers are doing with it, to how it’s changing day-to-day work on the floor. Shoppers are using AI and converting at higher rates Nearly 60% of U.S. adults report using AI to help them shop this year. Some use it to compare prices. Others turn to tools like ChatGPT for gift ideas or product reviews. One signal that stood out: shoppers who land on retail sites via an AI assistant are 38% more likely to make a purchase (Adobe Analytics). That could reflect better targeting or that consumers are turning to AI when they already have high intent to buy. Even though most online purchases now happen on mobile, the vast majority of AI-generated traffic is still coming from desktops. That may change as interfaces evolve. AI is shaping how people expect to shop Consumers are getting used to more conversational search. Some even say they trust AI more than friends for product advice (Cian, 2025). But they also express concerns around scams, data privacy, and losing the “human touch.” That presents a real design and trust challenge for retailers. There’s a fine line between providing real value and being seen as using AI to optimize margin at the customer’s expense. On the retail floor, AI is starting to augment AI is showing up in inventory systems, virtual assistants, and mobile tools for frontline workers. Lowe’s, for example, is using its MyLow Companion to give associates real-time answers on products or stock without needing to radio for help. In addition to adding tools, AI is changing roles. A survey of employers found 62% plan to retrain or upskill retail workers for new tasks as AI adoption increases (TotalRetail). One case worth watching: Ikea. When call center jobs were automated, they retrained 8,500 workers to become virtual interior design advisors. That team generated $1.4B in revenue in 2022 alone (Reuters). What this tells us about AI and frontline work It’s early, but retail offers a useful testbed for AI’s broader impact on consumer-facing industries. The risks are real. But we’re also seeing evidence that, with investment in training and thoughtful role design, AI can support both better customer experiences and new forms of frontline work.

🛠️ ABOUT YOU Seller Center – the new all-in-one tool for marketplace sellers ABOUT YOU has redefined its marketplace model. Instead of a restrictive selection process, the platform is now opening its doors to all European fashion brands – supported by a single tool that covers the entire process: the Seller Center. Why is this exciting? 👉 The Seller Center combines all essential integration steps in one interface: from registration and the KYC process to product uploads and ongoing marketplace business management. 👉 Sellers can decide how to integrate their products - via Shopify, API, Excel, integrators, or manual entry. 👉 Logistics are flexible, with either Fulfillment by Seller or Fulfillment by ABOUT YOU (FbAY). In the coming months, the platform plans to expand both options to many more European countries. 👉 And the best part: brands can go live in just 4 weeks - with no listing or platform fees. Fees only apply after the first sale. This makes marketplace entry much easier not only for well-established brands but also for smaller labels. 📌 In our blog, we walk you through the complete 5-step onboarding process in detail – from registration to go live, including the key checklists. 🔗 Read more here: https://lnkd.in/drTqgzXj

⭐️Revolutionising Fashion Retail with IBM Sterling OMS⭐️ The fashion industry is dynamic, fast-paced, and customer-centric leading brands use IBM Sterling Distributed Order Management (OMS)—a solution designed to streamline omnichannel operations, enhance customer experiences, and optimise supply chains. Trusted by global names like Ralph Lauren, adidas, Marks and Spencer, NET-A-PORTER, Fossil Group, Inc., Pandora and John Lewis & Partners, Sterling is the backbone of modern retail. Here’s how IBM Sterling OMS Transforms Fashion Retail: 🛍️Omnichannel Integration: Synchronise inventory and fulfilment across online, in-store, and mobile platforms. Adidas uses OMS to offer services like buy online, pick up in-store (BOPIS) aka Click-and-Collect and ship-from-store. 🛍️Inventory Optimisation: Manage stock in real time to reduce waste and meet demand. Marks & Spencer minimises stockouts with OMS, while Eileen Fisher aligns inventory management with sustainability goals. 🛍️Flexible Fulfilment: Enable split shipments, drop-shipping, and ship-from-store to meet customer needs. Sally Beauty Holdings saw a 540% sales increase by deploying ship-from-store in 2,700+ locations. 🛍️Efficient Returns: Simplify returns to any store, improving customer satisfaction. Pandora doubled its online sales with OMS, handling returns seamlessly during high-demand periods. Pandora leveraged OMS to deliver real-time inventory visibility and optimise global fulfilment operations. 🛍️Fulfillment Speed: John Lewis & Partners migrated 5.7M orders to IBM Sterling OMS, reducing production times and enhancing fulfilment speed. 🛍️Frictionless Customer Experience: Aditya Birla Fashion and Retail Limited achieved 99.5% inventory synchronisation, ensuring a seamless customer experience. With IBM Sterling OMS, the world’s most iconic fashion brands are transforming their operations to meet the demands of modern retail while staying true to their values. #FashionRetail #IBMOMS #SupplyChain #Omnichannel #Sustainability #InnovationInRetail #CustomerExperience #RetailTransformation #PassionForFashion #Luxury #Fashion #Retail #RethinkRetailTopExpert #NRFRetailVoice RETHINK Retail #RethinkRetail National Retail Federation #NRF #ItsAGreatTimeToBeAnIBMer #IBMRetail #IBMConsumer More on IBM OMS: https://lnkd.in/eiJ4Rzxc More on our work with Pandora: https://lnkd.in/eQxSGp3Q 💬 Fashion and Lux will be a topic of discussion at the NRF. Speak to our experts like David Hogg or Colm O'Brien. Join us from January 12-14, 2025, in NYC to explore how IBM is transforming retail at Booth #4639. More here: https://lnkd.in/dzY42Bmf. See you there!

Grateful to be featured in the "Shoptalk Hot Takes" interview by Blenheim Chalcot and ClickZ.com alongside George Looker to unpack omnichannel commerce. 5 key takeaways and tactics from my conversation: 1. Design for Customer Continuity, Not Just Channel Expansion 💡 71% of customers expect brands to personalize interactions across every touchpoint. Tactical: Map out customer journey across channels, then design experiences that recognize and reward continuity—cart persistence, loyalty rewards, browsing history sync, etc. 2. Build the Infrastructure: Unify Data Streams Across All Touchpoints 🧠 Data fragmentation = missed opportunity Tactical: Integrate POS, e-commerce, mobile, social, and marketplace data into a centralized data lake or unified commerce platform. 3. Establish a Single Source of Truth for Customer Profiles 🔍 Brands with unified profiles see up to 2x better campaign performance. Tactical: Implement Customer Data Platforms (CDPs) to consolidate behavioral, transactional, and engagement data into unified customer profiles. 4. Partner Strategically for Scale, Not Just Stack ⚙️ A bloated tech stack doesn’t equal agility As I noted, Retailers are getting sharper about which partners can scale with them. Ecosystem efficiency matters more than ever. Tactical Step: Audit your tech stack and partnerships consistently. Prioritize partners that offer extensibility, future-proofing, and proven omnichannel success. 5. Measure What Matters: Unified KPIs Across Commerce 📈 You can’t optimize what you don’t measure holistically Tactical: Align your analytics stack to report holistically across channels—tie marketing to merchandising, CX to LTV, and inventory to revenue. 🧠 Bottom line: think holistically, move strategically, and build ecosystems that scale experience with agility, not just transactions. Complete list in comment 👇 #ecommerce #omnichannel #unifiedcommerce

There’s a concern that AI will adversely impact physical retail, replacing stores and people with automation, robotics and digital-only experiences. But that's not what I believe will happen. I believe in vibrant, viable spaces that draw people in, and where physical retail can thrive. But as the AI-first generation starts to reinvent shopping (at least as we know it), stores will certainly start to look, feel and work differently. AI isn’t about replacing stores; it’s about making them work smarter and more efficiently, and making them more engaging for both customers, colleagues and communities. These are 'Amplified stores'. Here’s how AI could redefine and amplify retail stores: ✅ Finally making omnichannel happen. It seems that the concept of omnichannel retail isn't going away anytime soon, so there are many ways that AI could help overcome challenges of data silos, integration, communication and more. AI and AI-enabled customers could unleash deeply connected, immersive shopping and hyper-personalised service across all channels. ✅ AI-powered personalisation through the visit. Imagine digital signage, product recommendations, or retail media tailored to you as soon as you walk by or into a store. Not just generic ads, but content relevant to your interests, purchase history, and even current needs in the moment. If you caught my earlier post on 'Anticipated Retail', you’ll know how this naturally extends into the physical world. ✅ Bespoke and on-demand production at scale. 3D printing is revolutionising manufacturing. But what happens when AI-first customers take control, instantly customising products across multiple materials and formats? Imagine this: - Perfectly fitting shoes, with innersoles printed in-store. - Clothing tailored to your preferences, all chosen on the spot. - Skincare formulated to your skin’s unique characteristics. AI will enable mass customisation at scale, giving customers creative control like never before. And this is just the beginning... more on this soon! ✅ AI will change store operations, but who will actually run the store? Today, there is still a lot of unproductive work for colleagues to do (e.g. admin, stock checks, reconciliation tasks etc). So of course, AI has the opportunity to streamline these, plus elements like forecasting, ordering and rota scheduling (AI is actually already doing all of this plus more), but what about the customer-facing role? And who serves customers? Digital assistants? Or people, empowered and more capable than ever with real-time insights to offer bespoke advice and expert viewpoints? I'm developing my thoughts on all of this, but I’d love to hear what you think. The AI-first generation will not usher in the 'end' of stores - but they will trigger a major reinvention of almost everything. How do you see AI (and AI-enabled customers and colleagues) shaping the stores and retail? #retail #retailinnovation #AI #retailtransformation #artificialintelligence