Using Data to Drive Retail Decisions

This summer, in 45 days, I shopped in supermarkets in 12 different countries. I said "𝘨𝘳𝘰𝘤𝘦𝘳𝘺 𝘳𝘦𝘵𝘢𝘪𝘭𝘦𝘳𝘴 𝘢𝘳𝘦 𝘨𝘦𝘵𝘵𝘪𝘯𝘨 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘦𝘹𝘱𝘦𝘳𝘪𝘦𝘯𝘤𝘦 𝘢𝘭𝘭 𝘸𝘳𝘰𝘯𝘨". Now this article from MIT Sloan Management Review supports my argument. Grocery retailers are investing in in-store experiences, 3rd party delivery apps, and subscription programs to enhance customer engagement, drive omnichannel growth. While experiential tactics like adding bars boost foot traffic and sales by over 5%, partnerships with third-party apps often reduce impulse purchases and loyalty, and subscriptions risk profitability due to high service costs. The study revealed that customer behavior changes in unexpected ways, making it essential for retailers to align innovations with operational strategy, data insights, and profitability goals. 📍In-Store experiences still drive incrementality, sure. Stores that added cafes or bars saw: +6.82% increase in total spend +5.76% more transactions +15.49% increase in time spent in store My two cents: Food & beverage brands should co-invest in experience zones (like dessert pairings, beverage sampling). This fuels cross-department spend and impulse purchases. 📍Surprise, surprise; impulse purchases decline with delivery apps Partnering with last-mile delivery partners results in -21.2% drop in impulse purchases (esp. snacks, bakery) -6.6% drop in sales volume Relying on 3rd party delivery suppresses #FMCG impulse-driven categories. Brands must rethink digital shelf storytelling and premium placement. 📍No brainer here, of course, subscriptions fuel bigger baskets, but at a cost. For subscribed customers: +55.5% increase in items per order +113.4% increase in order frequency +30% increase in product sales But, approx. 50% of subscribers caused -108.4% profitability loss To resolve this, #CPG brands must help retailers optimize for SKU mix and basket value in subscriptions to avoid profitability erosion. 📍 Consumers shift behavior based on convenience, not loyalty. Shoppers using delivery apps make fewer, smaller trips, buying fewer SKUs, but higher-priced ones. Premium, limited-edition, or DTC-exclusive launches perform better in digital delivery environments. Core SKUs risk de-prioritization. ++ I expect to see more across retailers in 2026 & 2027 ++ 1. AI-based inventory will be mandatory. 2. Delivery platforms will morph into retail and media ecosystems 3. Offline experience zones will serve as sampling hubs (I talked about this at the MIT Platform Strategy Summit in 2022) 👍 4. Shelf-level loyalty programs will emerge, using in-store smart carts or mobile apps, and brands will push on-shelf loyalty triggers like instant coupons. I believe #retail innovation is no longer about features — it's about behavioral precision. Every new tactic must be measured by how it changes the why, what, and where behind each consumer’s purchase. That’s where real ROI begins. Article link 👇

100 people walked into your store. 10 made a purchase. What about the other 90? Most retailers track sales - some track inventory. But very few track who’s stepping inside. 👀 How many customers visited today? 👥 What age groups are they? 🚹🚺 What’s the gender ratio? Retailers spend lakhs on marketing to drive footfall. But without data, they’re guessing what works. At StorePulse AI, we built a Footfall & Customer Insights AI that: ✅ Counts every person entering a store (no more rough estimates) ✅ Identifies age groups & gender distribution for better targeting ✅ Helps retailers optimize staffing & marketing based on real data No new installations needed - it works with existing CCTV cameras. Retailers know their sales. Now, they can understand their customers. What’s one thing you wish more stores understood about their shoppers?

🛍️🎯 Personalization in B2C Marketing: Enhancing Customer Experiences In the realm of B2C marketing, personalization is a powerful tool that can significantly enhance customer experiences and drive brand loyalty. Let's delve into the importance of personalization and explore strategies for tailoring messages, recommendations, and promotions to individual consumer preferences: **1. Understanding Individual Preferences: Personalization starts with understanding your customers on an individual level. Collect data on their purchase history, preferences, and interactions with your brand across various touchpoints. **2. Segmentation for Targeted Communication: Use segmentation to categorize your audience based on shared characteristics. This allows you to create targeted marketing campaigns that resonate with specific groups, delivering more relevant content. **3. Tailored Messaging and Content: Craft personalized messages that speak directly to the interests and needs of your customers. Whether it's email marketing, social media posts, or product recommendations, tailor the content to match individual preferences. **4. Dynamic Website Content: Implement dynamic content on your website that adapts based on user behavior and preferences. This can include personalized product recommendations, content suggestions, or even a personalized homepage experience. **5. Personalized Email Campaigns: Leverage personalization in email campaigns by addressing recipients by name and recommending products or content based on their past interactions. Use dynamic content blocks to tailor the email content for different segments. **6. Recommendation Engines: Implement recommendation engines on your website and other digital platforms. These engines analyze user behavior to suggest products or content that align with individual preferences, fostering a personalized shopping or browsing experience. **7. Behavioral Retargeting: Utilize behavioral retargeting to reconnect with users who have visited your website but didn't make a purchase. Display personalized ads showcasing the products they viewed, encouraging them to return and complete the transaction. By embracing personalization in B2C marketing, businesses can foster stronger connections with their audience, increase customer satisfaction, and ultimately drive higher conversion rates. 🛒💻 #B2CMarketing #Personalization #CustomerExperience

Inflation can erode consumer purchasing power, forcing businesses to rethink their pricing and product strategies. #BigBazaar, one of India’s leading retail chains, turned to real-time sales data to make smarter, faster decisions—and here’s how they did it. 🔍 𝐓𝐡𝐞 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: With rising inflation, BigBazaar noticed: ✔️ A decline in premium product sales ✔️ More customers opting for smaller pack sizes ✔️ A shift toward private-label and economy brands Without clear data insights, adjusting to these changes would have been a guessing game. 📈 𝐓𝐡𝐞 𝐃𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Instead of reacting late, BigBazaar leveraged real-time analytics to track purchasing patterns at the SKU level. This enabled them to: ✅ Identify a growing preference for budget-friendly alternatives ✅ Adjust procurement and stocking strategies to align with demand ✅ Optimize promotions by offering targeted discounts on trending products rather than blanket price cuts 💡 The Result: ✔️ A 12% increase in sales for private-label products (Tasty Treat, Golden Harvest) ✔️ A 9% improvement in customer retention among price-sensitive shoppers ✔️ Reduced excess inventory of slow-moving premium items 🎯 Key Takeaway: In uncertain times, data beats intuition. Businesses that track real-time trends can pivot quickly—ensuring they meet customer needs while protecting profitability. 𝑯𝒐𝒘 𝒊𝒔 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒖𝒔𝒊𝒏𝒈 𝒅��𝒕𝒂 𝒕𝒐 𝒏𝒂𝒗𝒊𝒈𝒂𝒕𝒆 𝒊𝒏𝒇𝒍𝒂𝒕𝒊𝒐𝒏? #DataDrivenDecisionMaking #DataAnalytics #

Personalisation is talked a lot about in commerce, yet I am seeing very few SMB's walk the talk. Personalisation with purpose is key to investing time and resources which are finite in any SMB retailer and I suspect why it is rarely implemented. Segmeting your customers into four key groups is a crucial first step: Loyal customers - repeat, full price shoppers Discount customers - repeat, discount shoppers First time customers - single purchase shoppers At risk customers - haven't purchased in 6 months (adjust time frame to your average repurchase rate time period) Now build a strategy accordingly: Loyal customers - exclusive first to know when new product drops (don't scream sale to them) Discount customers - first to know when you go on sale First time customers - serve them the products second time customers purchase At risk customers - send them a really hot offer to see if you can entice them back, maybe even ask them why they haven't shopped again with you? How does a retailer "one up this", look at patterns in what your customer groups buy. A great example of this is a strategy we rolled out with a footwear brand which I shared with the Klaviyo team in Sydney this week... Before going on sale, segment your slow moving or end of season products into sizes. Build custom landing pages (this can be down using search filters as well) showing the styles and products in that customer groups size. You may just be blown away too that you end up selling through all your slow moving or end of season products at full price. A simple strategy targeting niche customer size groups with styles in their size will not just drive revenue and profit, but loyalty too. These customers likely struggle to find their size more often than not! How often have you gone to a store and found what you wanted was not available in your size... 🙄 What's your top tip for tackling personalisation?

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

Machine learning for dynamic pricing optimization offers businesses a competitive edge by enabling them to adjust prices in real-time, ensuring they remain responsive to market demands, customer behavior, and competition, ultimately maximizing revenue and profitability. Machine learning, a subset of AI, allows systems to learn from data and improve without explicit programming, identifying patterns and making predictions from historical data. In pricing optimization, it helps set prices strategically by considering demand, competition, costs, and customer perception. Fundamental data types used include sales history, market trends, competitor pricing, customer behavior, demographics, seasonality, and search trends. Standard algorithms, such as regression, decision trees, neural networks, clustering, and reinforcement learning, are applied to predict demand shifts. Dynamic pricing then adjusts prices in real-time, boosting revenue and competitiveness. For business implementation, ML models can be integrated with existing systems like sales, ERP, and CRM, allowing for real-time price adjustments. Challenges include maintaining high data quality, investing in technology and skills, and addressing ethical and regulatory concerns regarding dynamic pricing, customer perception, and compliance. #ai #MachineLearning #Pricing #CRO #COO

𝗪𝗮𝗹𝗺𝗮𝗿𝘁 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝘀 𝗥𝗲𝘁𝗮𝗶𝗹 𝘄𝗶𝘁𝗵 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗣𝗿𝗶𝗰𝗲 𝗧𝗮𝗴𝘀 𝗮𝗻𝗱 𝗔𝗜-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗣𝗿𝗶𝗰𝗶𝗻𝗴!🛒📲 Last Friday, I was asked after my masterclass how mass market retailers could improve customer experience (CX) as brands are currently doing in the fashion industry. We briefly discussed how Walmart is once again leading the charge in retail innovation. These types of retailers are more like convenience stores, and the approach should be to make the consumer shopping experience easier and seamless. A prime example of this innovation is Walmart's upcoming implementation of digital price tags. By 2026, 2,300 Walmart stores will replace traditional paper price tags with digital price tags, revolutionizing the way prices are managed and updated. This is a game-changer for CX and operational efficiency. 𝗞𝗲𝘆 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻𝘀 ⏱️ Rapid Price Updates:  Over 120,000 items can have their prices updated in mere minutes, compared to the two days it previously took with paper tags. All done with just a few clicks via the 𝗠𝗲@𝗪𝗮𝗹𝗺𝗮𝗿𝘁 𝗮𝗽𝗽 📈 Dynamic Pricing with #AI:  The AI analyzes market trends, demand, and competition to adjust prices instantly. This means prices can be optimised to reflect current market conditions, maximising sales and #inventory efficiency. 🚀 Enhanced Customer Experience:  Faster and more accurate pricing ensures customers always see the correct price, enhancing trust and satisfaction. 🛍️ Efficient Order Fulfillment:  Employees can pick items for online orders more quickly, improving the speed and accuracy of order fulfillment. 🌱 Sustainable Innovation: Reducing paper use contributes to Walmart's sustainability goals, promoting a greener retail environment. 𝗛𝗼𝘄 𝗔𝗜 𝗗𝗿𝗶𝘃𝗲𝘀 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗣𝗿𝗶𝗰𝗶𝗻𝗴? 🔮 Predictive Analysis:  AI analyzes historical and current data to foresee changes in demand and market behavior, enabling precise price adjustments, just as Amazon has been doing for ages. 🤖 Machine Learning:  Algorithms continuously improve by identifying patterns and trends to optimize prices. 📊 Big Data:  AI handles large volumes of data from various sources to adjust prices in real time. 📈 Real-Time Competition Monitoring:  It tracks competitor prices and adjusts Walmart's prices automatically to stay competitive. 🎯 Personalisation:  Offers personalised prices based on customer purchasing behaviour, this could be done only online of course. 💡 What are your thoughts on the adoption of AI-driven dynamic pricing in retail? #RetailInnovation #CustomerExperience #DynamicPricing #Walmart #DigitalTransformation #RetailTech #Sustainability #CX

𝗜𝗳 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗗𝗼𝗻'𝘁 𝗥𝗲𝗽𝗲𝗮𝘁-𝗕𝘂𝘆 𝗙𝗿𝗼𝗺 𝗬𝗼𝘂𝗿 𝗕𝗿𝗮𝗻𝗱, 𝗛𝗲𝗿𝗲'𝘀 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗜𝗺𝗽𝗿𝗼𝘃𝗲. Repeat rate below 30%? You're not running a business – you're renting customers. Here's the brutal truth most founders avoid. 𝗧𝗵𝗲 𝗥𝗲𝗽𝗲𝗮𝘁 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲 𝗔𝘂𝗱𝗶𝘁 𝐑𝐮𝐧 𝐭𝐡𝐞 90-𝐃𝐚𝐲 𝐓𝐞𝐬𝐭: Pull data. What % of customers who bought 90 days ago bought again? If it's under 25%, your product isn't solving a recurring problem – it's a one-time novelty. 𝐌𝐚𝐩 𝐏𝐮𝐫𝐜𝐡𝐚𝐬𝐞 𝐅𝐫𝐞𝐪𝐮𝐞𝐧𝐜𝐲 𝐑𝐞𝐚𝐥𝐢𝐭𝐲: Skincare lasts 60 days. Coffee lasts 30. If your reorder rate doesn't match product depletion cycle, either product quality is off or post-purchase engagement is dead. Fix one or both. 𝐊𝐢𝐥𝐥 𝐭𝐡𝐞 "𝐓𝐡𝐚𝐧𝐤 𝐘𝐨𝐮" 𝐄𝐦𝐚𝐢𝐥 𝐓𝐫𝐚𝐩: Stop sending "Thanks for your order!" Start sending "Here's how to get maximum results" guides on Day 3, "You're halfway through" reminders on Day 30, and "Reorder now, get 15% off" on Day 50. Time it to usage, not vanity metrics. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐞 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐀𝐬𝐤𝐢𝐧𝐠: Don't force subscriptions. Offer "auto-refill" as convenience. Pause anytime. Customers hate commitment but love convenience. Frame it right. 𝐓𝐡𝐞 𝐏𝐨𝐬𝐭-𝐏𝐮𝐫𝐜𝐡𝐚𝐬𝐞 𝐀𝐮𝐝𝐢𝐭: Call 20 customers who didn't reorder. Ask bluntly: "Why didn't you buy again?" You'll find patterns in 5 calls – price, quality, forgetfulness, competition. Data beats assumptions. Repeat customers cost 5x less to acquire than new ones. If you're only hunting new customers, you're choosing the expensive path to failure. Fix retention before scaling acquisition. #D2C #customerretention #business #strategy #repeatpurchase