Retail Analytics Services

In retail, speed is no longer a competitive advantage—it’s the price of admission. The difference between leaders and laggards comes down to one thing: real-time data. You either see the moment as it unfolds, or you react after the market has already moved on.   When I sit down with retail leaders, I often talk about what I call the low-hanging fruits—not because they’re easy, but because they deliver disproportionate impact, fast.   - First, ERP integration. When buyers and suppliers operate on the same live version of truth, friction disappears. Decisions get sharper. Trust goes up. - Second, intelligent agents. Not dashboards that explain yesterday, but systems that think in the moment—forecasting demand, monitoring inventory, and optimizing logistics as conditions change. - Third, next-generation VMI. Inventory that manages itself—cutting stockouts without tying up capital in excess stock.   These aren’t moonshots. They’re practical, achievable today, and they build momentum quickly.   Recently, we partnered with a leading luxury retailer to bring this vision to life. Their reality was familiar: no real-time visibility, an overwhelming flood of OMS events, legacy infrastructure that couldn’t scale, and legitimate concerns about protecting sensitive data. We re-architected the foundation. A serverless AWS platform capable of processing millions of OMS events in real time. A secure, centralized data lake. AI and ML models embedded into the flow of operations. And live dashboards that put insight directly into the hands of business leaders.   The outcomes spoke for themselves: - Real-time and historical visibility across the enterprise - A scalable, cost-efficient technology backbone - A future-ready platform for advanced analytics and faster decision-making   This isn’t about operational efficiency alone. This is about competitive advantage.   The next wave of retail disruption is already here. The winners will be the ones who master real-time analytics and AI—not as experiments, but as core capabilities embedded into how they run the business. #AIinRetail

Most “sales dashboards” are just prettier spreadsheets. This one by Gandes Goldestan is a control panel for decisions. 🔍 Highlighting this Merchandise Sales Overview built in Tableau. Here’s what stands out: 1️⃣ Category tiles that tell a story in 3 seconds Across the top-left you get Clothing, Ornaments, and Other with:  • Revenue for the current scope  • % vs. last December  • A mini 12-month trend You don’t have to dig— you instantly see which category is sliding and which is stable. 2️⃣ Location + product view that actually plays nice On the right, a map shows where revenue is concentrated while the “Top Products by Revenue” bar list shows what is driving that revenue. Perfect combo for questions like: “What are people buying in this region, and which SKUs should we feature more?” 3️⃣ Row-level context without clutter The transaction history table gives:  • Order ID, type, date, revenue  • A clear satisfaction indicator for each order You can jump from “sales are down” to “which orders and experiences are causing it?” without leaving the page. 4️⃣ Customer voice front and center The customer rating widget (3.8 ⭐ with distribution by star level) anchors the whole thing in reality: revenue means less if satisfaction is tanking. This makes it way easier for a manager to say, “𝘞𝘦 𝘥𝘰𝘯’𝘵 𝘫𝘶𝘴𝘵 𝘯𝘦𝘦𝘥 𝘮𝘰𝘳𝘦 𝘴𝘢𝘭𝘦𝘴, 𝘸𝘦 𝘯𝘦𝘦𝘥 𝘣𝘦𝘵𝘵𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦𝘴.” 5️⃣ Smart demographic breakdown “Revenue by Gender & Age Group” shows who is actually buying, so marketing and merchandising can align on which segments to push and which to grow. Dashboards like this do what every retail team needs:  • Tell you what’s happening now  • Show you who and where it’s happening  • Hint at what to do next Awesome work, Gandes Goldestan—clean design, clear hierarchy, and built for action, not just aesthetics. #Tableau #DataVisualization #RetailAnalytics #MerchandisePlanning #AnalyticsDesign

10 years ago, mystery shopping looked very different. I remember walking into a client meeting—armed with folders full of audit reports, hand-written feedback, and survey charts. The insights were useful… but late. By the time store teams saw the feedback, the customer was long gone. The opportunity? Missed. Fast forward to today—and I can confidently say this: AI has completely changed the mystery shopping game. Here’s what I’ve learned while helping 500+ brands transform their retail experience with AI-powered insights: 1. AI call monitoring > Delayed feedback I used to see retailers wait 3 to 4 weeks for feedback on their customer service calls. Now? With AI voice analytics, issues like poor tone, long wait times, or missed sales cues are flagged in real-time. Lesson: It's no longer about what happened. It's about why it happened—and fixing it before the next customer interaction. 2. Computer vision > Manual store checks AI-powered cameras now track dwell time, customer flow, and even staff engagement—without needing a single mystery shopper on the ground. When I saw Amazon’s Just Walk Out tech, it blew my mind. But what’s even more exciting? Mid-sized retailers are now using affordable AI tools to monitor store hygiene, shelf gaps, and queue management... 3. Predictive insights > Rearview mirror thinking Traditionally, audits told us what went wrong. But AI now predicts which store will have staffing issues next week… which region is trending toward negative NPS… and which products are likely to go out of stock—before the store manager even notices. Why am I sharing all this? Because I’ve seen too many brands still relying on outdated systems—waiting for audits, debating subjective reports, and missing the real-time advantage. If you ask me what the future of mystery shopping looks like? It’s not one shopper per store per month—it’s 24/7 digital coverage powered by AI + human intelligence. And here’s the exciting part: This isn’t just for billion-dollar companies anymore. We’re helping brands of all sizes scale this affordably. So what’s the big takeaway? ▪️ AI doesn’t replace mystery shopping—it supercharges it. ▪️ Retailers that combine human empathy with machine precision will win on customer experience. ▪️ And the faster you act on feedback, the faster you build loyalty. If you're curious how this could work for your brand—let's talk. I’d love to share what we’ve learned at FloorWalk helping brands across 22+ countries unlock the full potential of AI in retail. Let’s reimagine the audit. Let’s reinvent retail. #AIinRetail #MysteryShopping #CustomerExperience #RetailInnovation #CXStrategy 

Retailers have no shortage of data - but are you surfacing the insights that truly matter? E-commerce leaders track AOV, ROAS, NPS, and churn, but knowing what’s changing isn’t enough—you need to know why. Traditional products analytics often leave teams reacting to trends instead of driving them. That’s where Loops comes in. Our AI-powered analytics platform helps large retailers uncover the real drivers behind KPI shifts and make data-backed decisions with confidence, with: 1️⃣ Root Cause Analysis: Automatically identify the reasons behind fluctuations in key metrics such as Average Order Value (#AOV), Return on Ad Spend (#ROAS), Net Promoter Score (#NPS), and inventory turnover. This proactive approach allows you to address issues before they impact your bottom line. 2️⃣ Real-Time Gen-AI Alerts Insight Summaries: Receive personalized alerts and insight updates on trends, anomalies, forecasts, and the impact of recent initiatives directly through Slack, Microsoft Teams, or email. This ensures your team stays informed and agile in responding to changes in your top KPI. 3️⃣ Product Release Impact Analysis: Measure the effect of every product change on your KPIs with over 90% accuracy of standard A/B testing but with minimal traffic, time, and resources. Loops' causal models account for variables like performance improvements, marketing promotions, seasonality, pricing adjustments, experiments, product errors, and user mix changes, providing a clear view of each change's impact. 4️⃣ User Journey Optimization: Identify and rank user paths that significantly influence your KPIs at every stage of the customer lifecycle. By understanding these journeys, you can optimize marketing strategies, landing pages, and the entire user funnel to drive conversions and retention. Proven Results with Loops: 🔥 ✅ 200% Increase in Conversions: Achieved through Loops' "User Journey" insights at Wahi Real Estate. ✅ $5 Million Revenue Saved: Through causal analysis of a core KPI drop at a major consumer goods retailer, enabling a partial release with a negative impact to be rolled back before it hit all users. ✅ 15% Increase in Day 2 Retention: Observed at 18Birdies, enhancing customer engagement and loyalty. Move beyond traditional dashboards, uncover hidden growth opportunities, and make data-driven decisions that propel your retail business forward. Discover how Loops can unlock your company's potential. #RetailAnalytics #AI #DataDrivenDecisionMaking #EcommerceGrowth #eCommerce #retail #CausalAI National Retail Federation, Shoptalk

Turning retail data into real business results can be a tough problem, but the solution isn’t more tech. It starts with grounding your data strategy in business outcomes and building from there. In this article, I break down how retail teams can move from disconnected dashboards and siloed analytics to a practical, value-focused data strategy. Key lessons include: 1️⃣ Start with the business problem not the tools + Clarify the goal first (like reducing churn or improving customer experience) 2️⃣ Empower better questions across teams so insights actually lead to action 3️⃣ Put data governance in place early to build trust in your numbers 4️⃣ Balance pace with capacity so you deliver wins without burning out 5️⃣ Build data literacy and ownership so everyone speaks the same language I also cover where the retail data push usually starts, how AI fits in practically (not hype), and what future trends are shaping smarter operations. If you work in retail or data and want strategies that actually move the needle, I hope this will help you: https://lnkd.in/gEubetHW

🚀 How can a Retail/CPG company can boost revenues using Sequential Market Basket Analysis 🛒 Did you know that understanding what customers buy next is just as important as knowing what they buy together? 🔍 Let’s take a look at how Company X, a leader in Retail/CPG, transformed their bottom line using Sequential Market Basket Analysis : 🎯 The Challenge : Company X noticed that while their traditional market basket analysis identified frequently purchased item pairs (e.g., bread & butter), they were missing insights about the order in which purchases happened. For example, customers were buying laptops, but accessories like mouse pads weren’t selling until much later—or not at all. 💡 The Solution : By adopting Sequential Market Basket Analysis, they started analyzing the temporal patterns of purchases: - Customers bought laptops on Day 1. - Many returned to buy laptop bags on Day 7. - Some returned for mouse pads on Day 15. With this insight, they : 1️⃣ Introduced timely recommendations on their e-commerce platform (e.g., “Customers who purchased a laptop often buy a bag within a week!”). 2️⃣ Sent personalized emails nudging customers to buy complementary items. 3️⃣ Optimized their promotion strategy by timing discounts to align with expected purchase windows. 📈 The Results : 1️⃣ 25% revenue increase for high-value accessory items. 2️⃣Improved customer satisfaction as buyers found relevant suggestions when they needed them. 3️⃣Inventory efficiency gains, reducing overstock of unsold items. 🔥 Why It Works: Unlike traditional market basket analysis, sequential analysis identifies purchase pathways, helping businesses predict and influence the next logical step in the customer journey. 👉 If you're in Retail/CPG Analytics, ask yourself : ✅ Are you leveraging purchase sequences to boost sales? ✅ Are your recommendations based on when customers buy, not just what they buy together? 💡 Pro Tip: Tools like sequence mining algorithms (PrefixSpan, AprioriAll) or Markov Chains can help unlock these insights. Temporal data analysis is a different ball game all together! #sequentialpatterns #marketbasketanalysis #retailCPG #experientiallearning #datascience #apriori

Using Computer Vision and Operational AI for Retail-Occupancy Analytics. Traditional retail analytics often fall short. Operational AI offers a smarter solution: 𝗚𝗮𝗶𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗱𝗮𝘁𝗮: - Understand foot traffic patterns and consumer behavior. - Identify peak traffic hours and make data-driven decisions. - Optimize store layouts and staffing levels. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮𝗻 𝗲𝗻𝗴𝗮𝗴𝗶𝗻𝗴 𝗮𝗻𝗱 𝗽𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝘀𝗵𝗼𝗽𝗽𝗶𝗻𝗴 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: - Tailor your offerings and promotions based on real-time data. - Improve queue management and reduce waiting times. - Provide a seamless and convenient shopping journey. 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲 𝗳𝗿𝗼𝗻𝘁𝗹𝗶𝗻𝗲 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆: - Analyze footfall trends, queue lengths, and conversion rates. - Improve staffing allocation and scheduling. - Optimize workflows and reduce operational costs. Video: Teknoir #ComputerVision #AI #Industry40 #DigitalTransformation #Retail #RetailTech #ConsumerInsights #SmartRetail #CustomerExperience #AIinRetail #RetailInnovation #QueueManagement

Building Better Retail Analytics: What We’re Improving at TASS Vision “Great products don’t just happen—they evolve. At TASS Vision, we’re always listening to retailers and improving our platform to make data more actionable, accurate, and easy to use. Here’s what’s new: ✅ FaceID Recognition – Personalizing customer experiences while ensuring security with white and black list in real-time. ✅ More Accurate People Counting in high traffic zones – AI update improves precision by 15%. ✅ Smarter Dashboards – Custom reports, real-time insights, and deeper conversion analytics. ✅ Shelf Analytics – Tracks product engagement and stock availability to prevent lost sales. ✅ Edge Computing – Faster processing directly on devices, reducing cloud dependency. ✅ Multi-Store Comparison – Easily benchmark performance across locations to spot trends. Every update brings us closer to helping retailers make smarter decisions—to drive more sales by 20%. What’s one feature you wish your retail analytics platform had? Let’s talk!” #AI #ComputerVision #RetailAnalytics #instoreAnalytics #EMEA

Lets talk: Unlocking Success with Retail Analytics When the ecommerce industry grew, pundits announced the death of Retail. One of our E-tail (Ecomm and Retail) clients sustained the wave, because their leadership used data at every step of their strategy, even with their store design. They said, our store is our website and the UI/ UX should be ‘top notch’. Until few months ago, they just knew ‘what’ their customers want, but not ‘when’ and ‘how’ they prefer to shop. Their campaigns were not personalized. Centralizing data and creating an attribution model helped them achieve those two insights. Now, we keep refining the model for various demographics and the leadership can’t seem to stop loving those insights. In addition, they started using data to: 📈 Optimize Inventory: Avoid overstocking or understocking by predicting demand with precision. 📊 Boost Profitability: Identify top-performing products and underperforming areas to allocate resources effectively. 🌟 Predict Trends: Stay ahead of competitors by forecasting market shifts and consumer preferences. Ultimately, analytics goes beyond just numbers; it's about enabling businesses to provide the right value to the right customer at the perfect moment. 💡 Let’s talk about how data-driven strategies can reshape the retail experience. The below image from Zuar sums up perfectly how data analytics can contribute to better Retail performance. Have you used retail analytics in your business? Share your thoughts below! #RetailAnalytics #DataDrivenDecisions #BusinessGrowth #CustomerInsights #SupplyChainOptimization #AI #BigData

🎄 AI + Holiday Retail: Why NOW Is the Time to Level Up Your Customer Experience 🤖✨ (Insights pulled directly from Chapters 3, 5, and 7 of my book AI for Retail Success, co-authored with Sharon Gee!) As retailers head into the holiday rush, shopper expectations are sky-high — faster service, effortless navigation, accurate pricing, and a seamless blend of tech + human touch. And with tighter staffing and higher operational pressures, this is exactly the moment where AI becomes your competitive edge. Here are three AI tools highlighted in the book — and the companies we recommend — that can make an immediate holiday impact: 🧭 1. Heat Mapping & Dwell Time Analytics From Chapter 3: The Smart Store Floor Heat mapping shows where shoppers move, pause, engage, and convert. This helps retailers optimize holiday merchandising and ensure top sellers are placed where they’ll perform best. Recommended in the book: • VusionGroup – real-time heat maps + shelf sensors • RetailNext – in-store behavioral analytics • Walkbase – traffic + zone analytics Perfect for: creating “holiday hotspot” displays, gift zones, and impulse add-ons that actually convert. 📊 2. Real-Time Traffic Counting From Chapter 5: Data-Driven Staffing & Efficiency Holiday traffic surges are unpredictable. AI counting lets you deploy your team exactly when needed — not overstaffing or missing conversion opportunities. Recommended in the book: • Dor Technologies – accurate, budget-friendly counters • Density – enterprise-level occupancy and traffic tracking • Trax Group – shopper flow + camera-based insights Perfect for: maximizing conversion during micro-rushes, aligning labor with traffic, and protecting sales when teams are lean. 💬 3. AI-Enhanced Customer Service Tools From Chapter 7: The Future of the Customer Experience AI doesn’t replace people — it empowers them. Holiday associates can access instant product info, loyalty lookups, inventory visibility, and personalized recommendations faster than ever. Recommended in the book: • Salesfloor – AI-assisted associate tools • Tulip Interfaces Retail – clienteling + guided selling • @Kore.ai – AI-powered service support and chat Perfect for: reducing wait times, boosting loyalty enrollment, and freeing staff to create moments of joy on your sales floor. ✨ Holiday shoppers have endless choices. They’ll stay loyal to the brands that make their experience seamless, warm, and memorable. AI isn’t the future — it’s the differentiator this season. Are you using AI tools in your stores this holiday? Which platforms have made a difference for you? Get your copy on Amazon today in digital, paperback, and hard cover versions and start today. We would love your comments and feedback and if you need help with strategy or implementation, DM us today. https://a.co/d/dRWKKXa #ai #TopRetailExpert #RetailVoicesbyNRF #thoughtleader #rethinkretail #keynote #consultant Sharon Gee Storytelling and AI for Retail Brands