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 👇

“We’re canceling… but it was great working with you.” Ever heard that from a customer? It stings — because if it was great working together, why are they leaving? I recently read a brilliant post by Jeff Moss, who nailed this paradox. It inspired me to reflect on what really drives retention in SaaS. Here’s my take: Over the years, we’ve dramatically upgraded customer experience — faster support, smoother onboarding, polished comms. But there’s still a trap in believing that: 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 = 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻. It doesn’t. You can be professional, responsive, even liked — and still lose the customer. Because retention doesn’t come from experience — it comes from progress. And here’s the irony: – Some of your most frustrated customers are staying, because they’re seeing progress. – Some of your happiest customers are leaving, because they’re not. So, the real question isn’t “Is my customer happy?” but 𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗶𝗳 𝘆𝗼𝘂𝗿 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗮𝗿𝗲 𝘀𝘂𝗰𝗰𝗲𝗲𝗱𝗶𝗻𝗴? Think D.A.T.A. — because success leaves data behind. 1. 𝗗𝗲𝗳𝗶𝗻𝗲 success in their language – What outcomes did they buy you for? 2. 𝗔𝗹𝗶𝗴𝗻 milestones – Break success into measurable checkpoints (adoption, ROI, value). 3. 𝗧𝗿𝗮𝗰𝗸 progress, not activity – Usage only matters if it ties back to outcomes. 4. 𝗔𝘀𝗸 perception vs. data – Validate with the customer: do they feel closer to their goals? Being liked isn’t bad. But 𝗯𝗲𝗶𝗻𝗴 𝘂𝘀𝗲𝗳𝘂𝗹 — that’s what makes you indispensable. #CustomerSuccess #Retention #SaaS #CX #Leadership

GLP-1 users are eating 40% less food. So why are they spending MORE on groceries? New data from Dan Frommer's The New Consumer Consumer Trends 2026 reveals something retailers need to understand: 428 current GLP-1 users report they're "trading up" to premium products across every category surveyed. Not some categories. Every single one. The net "trading up" scores are striking: Fitness/wellness products: +51% Energy drinks: +39% Beauty products: +35% Fresh fruits and vegetables: +35% Why? 56% say "I eat less overall, so I can afford higher-quality food." Another 56% say "I want to enjoy the meals I do eat more." This is the strategic inflection point most food retailers are missing. The conventional response: Cut costs to maintain volume as consumption shrinks. The Strategic Renewal response: Reframe your capabilities around value per transaction, not transactions per customer. Here's what the data shows: ~24% of US households now include a GLP-1 user. By 2030, these households will represent 35% of food and beverage sales (Circana). This isn't a niche. This is your customer base reframing what they value. And yet—most retailers are still optimizing for volume. More SKUs. Bigger pack sizes. Promotional pricing to drive cart size. That's competing on convenience in a market that's actively moving toward quality. The companies that will win aren't the ones cutting portions or launching "GLP-1 friendly" product lines. They're the ones who genuinely reframe their value proposition: from feeding people more to feeding people better. We will discuss this more in our Nearly Now 2026 coming out in the new year. What would that look like in your business? How would your merchandising strategy change if you assumed customers were making half as many food decisions—but were willing to pay twice as much for each one? #StrategicRenewal #RetailStrategy #CompetingOnQuality #ConsumerTrends

CStore Leaderboard 7-Eleven → 12,600+ locations Alimentation Couche-Tard (Circle K) → 7,100+ Casey's→ 2,890 Murphy USA → 1,757 bp / Amoco → 1,566 Wawa, Inc., QuikTrip, Sheetz, Maverik, Inc., RaceTrac → all 650–1,100 range That’s ~35,000+ locations across the top players alone — many added or optimized in just the last decade. This is not slow retail. This is infrastructure build‑out. According to NRF consumer trend and convenience retail data: Convenience + proximity retail continues to outperform traditional formats on visit frequency, especially among shoppers under 35 Gen Z prioritizes speed, access, and frictionless checkout over format loyalty Foodservice, private label beverages, and fresh grab‑and‑go are the #1 traffic drivers, not fuel WHY GEN Z IS ALL‑IN ON C‑STORE EXPANSION: Gen Z value math = Time ÷ Effort × Trust C‑stores win because they: ✅ Sit within 5 minutes of daily routines ✅ Remove cart math and aisle fatigue ✅ Offer single‑mission dominance ✅ Combine food, beverage, and necessity in one stop ✅ Feel owned by the neighborhood, not a corporation Younger shoppers reward formats that reduce cognitive load even at slightly higher unit prices. That’s not irrational. That’s design‑literate behavior. Convenience chains aren’t just adding boxes. They’re rewiring the store: Smaller footprints Faster food execution App‑based loyalty + payments Private label drinks & snacks Coffee programs rivaling QSR Fuel becoming the side hustle This isn’t a gas station story. This is a Gen Z retail power grab hiding in plain sight. C‑stores are becoming: 🧠 Daily routine anchors ⏱️ Time‑optimization tools 📍 Hyper‑local trust engines #RetailTrends #NRF #GenZ #ConvenienceRetail #StoreExpansion #PrivateLabel #Foodservice #RetailStrategy #Thrillzilla Walmart Target

Inflation often forces businesses into a dilemma—raise prices and risk losing customers, or keep prices stable and shrink margins. But what if data could help strike the perfect balance? 🚀 Challenge: Flipkart, one of India’s largest e-commerce platforms, noticed fluctuating customer retention rates and declining repeat purchases, especially during inflationary periods. Traditional deep-discount campaigns led to short-term sales spikes but failed to build long-term customer loyalty. 🔎 Solution: Data-Driven Discounting Strategy Flipkart’s analytics team uncovered a key insight: Small, frequent discounts (e.g., 5-10% on repeat purchases) led to higher engagement. Personalized offers based on purchase history encouraged repeat buys. A/B testing revealed that customers preferred consistency over occasional deep discounts. 💡 Implementation: Using AI-driven dynamic pricing, Flipkart rolled out: ✅ Tiered discounts for loyal customers. ✅ AI-powered coupon recommendations. ✅ Targeted email campaigns promoting small, time-sensitive discounts. 📈 Results: After three months of testing, Flipkart saw: ✔️ 17% increase in repeat purchases ✔️ 12% uplift in customer retention ✔️ Higher profit margins vs. deep discounting 🎯 Key Takeaway: In an inflationary environment, data-driven pricing isn't just about maximizing revenue—it’s about customer psychology. Businesses that personalize their offers and optimize discounts intelligently can boost retention while protecting margins. 𝑾𝒉𝒂𝒕 𝒑𝒓𝒊𝒄𝒊𝒏𝒈 𝒔𝒕𝒓𝒂𝒕𝒆𝒈𝒊𝒆𝒔 𝒉𝒂𝒗𝒆 𝒘𝒐𝒓𝒌𝒆𝒅 𝒇𝒐𝒓 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒊𝒏 𝒄𝒉𝒂𝒍𝒍𝒆𝒏𝒈𝒊𝒏𝒈 𝒕𝒊𝒎𝒆𝒔? #datadrivendecisionmaking #DataAnalytics #DiscountStrategy #BusinessStrategies

Understanding your customers’ behaviors and responding accordingly is key to sustained business success. In yesterday’s post, I introduced the Recency-Frequency Matrix, a powerful tool for customer segmentation that helps businesses identify and prioritize their most valuable customers. Today, I want to take it a step further by showcasing how this analysis can inform targeted marketing strategies to drive engagement and growth. Strategic Actions Based on the Recency-Frequency Matrix: Champions: These are your top-tier customers who purchase frequently and recently. To maintain their loyalty, consider offering early access to new products or services, implementing a robust loyalty rewards program, and sending highly personalized communications. Loyal Customers: Customers in this segment are consistent buyers but with slightly less frequency. Encourage more frequent purchases through special incentives, reminders of your product or service benefits, and targeted re-engagement campaigns. Needs Attention: These customers have shown steady engagement but may need a prompt to stay active. Reactivation campaigns with tailored offers, requesting feedback, and exclusive deals can help prevent potential churn. Churn Risk: These customers are at risk of disengagement. Win them back with significant incentives, reminders of positive past experiences, and personalized offers designed to reignite their interest in your brand. Already Churned: For customers who have not engaged for a while, occasional check-ins or updates, targeted ads for reintroduction, and a focus on acquiring new customers might be the most efficient use of resources. Leveraging a Recency-Frequency Matrix not only provides a clear view of where your customers stand but also empowers you to implement highly tailored strategies that maximize both engagement and ROI. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

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

Product is a key part of your competitive advantage, yet it’s often one of the most under-managed aspects of your business. Do you measure inventory health as frequently as you measure marketing performance? 🧠 Most brands we speak to say no, yet they want to be profitable. When we assess inventory health the pathway to generate revenue, free cash flow, and profits starts with how well you manage your product assortment. Here is a real life example of a $20m+ brand in Australia and when we onboarded them I immediately understood why the founder seemed stress. What is the data telling us: Revenue is around $20m and they are carrying close to $39m in inventory 3075/8246 are selling, that's only 37% 613/8246 are driving 70% of gross profit, that's under 8% The majority of stock are contenders, underperformers or dead! Insights are great, but what next? Segment your product feeds into A/B/C/D classes Make sure you convert C/D classes to cash ASAP Slim down holdings in your B class Boost holdings in your A class and make sure they never go out of stock That's what it takes to build a lean, efficient commerce machine!

Top U.S. sports retailer levels up with GenAI.  How they improved email personalization: Angela Jing & May Khine's infographic breaks down the opportunity, methodology, and results. Opportunity: Dick’s Sporting Goods (DSG) sends one to two daily emails to its subscribers. Previously, these emails were created manually with limited personalization. To enhance efficiency and personalization, DSG sought to combine Generative AI with its demographic, loyalty data, email templates, interactions, and transaction history. Here’s how they did it: 1\ Identify customer segments ↳ Cluster customers by purchase history to identify their content preferences. 2\ Generat email templates ↳ Create personalized email templates for customer segments using an LLM (DBRX) with Retrieval-Augmented Generation (RAG). 3\ Recommend templates for customers ↳ Rank LLM-generated templates and recommend the best for each customer. Results: Deliverables ↳ New LLM-based automated email generation pipeline. ↳ User-friendly web application. ↳ Clear prompt guidelines. Metrics ↳ 65% predicted increase in email relevance. ↳ 18% predicted increase in clicks. ↳ 29% estimated reduction in creation time. P.S. The graphic dives deeper on data scope and methodology. --- ♻️ Repost to help your network! 📌 Want to level up with Generative AI? 1. Just follow me Lewis Walker ➲ 2. Subscribe to my free newsletter. #generativeai #ai

A recent article by Progressive Grocer did a nice job of highlighting a generational shift away from traditional grocers, citing the growing irrelevance of a hi-lo focused pricing strategy. In our data, we see this shift happening for additional reasons, and it is especially acute for shoppers moving into and through the family life stage. ✅ What is at stake? While the number of people never having kids had been rising between 1980 and 2010, from 10% to 20%, that number has been coming back down lately, according to studies from both Pew Research Center and Gallup. As of 2023, 92% of people aged 18-40 hope to have children or already do. Also, the more mature the family, the more they spend on groceries. According to the dunnhumby Retailer Preference Index study, Millenials with no kids spend about $380 per month on groceries. That number jumps to $558 per month when they have their first young kids (under 6) and climbs up to $676 per month by the time those little kids grow to teenagers (over 12). ✅ What to do about it? Four consumer behaviors in particular increase in likelihood when people have their first young children: buying more organic, shopping online, using stores' apps, shopping around at different stores to get all the products they need. The only two of those behaviors that continues to grow in momentum as the family matures from little kids to teenagers are online shopping behaviors and app engagement. We also see a clear pattern between the market share lines in the chart below and channel strengths and weaknesses. Mass Merchants (including Walmart, Amazon and Target) tend to have price perception advantages (especially Walmart and Amazon) over supermarkets and the specialty channel, another channel that witnesses market share decline as families mature (that channel includes retailers like Whole Foods, Sprouts Farmers Market, Trader Joe's). Also, all three of the mass merchants mentioned occupy the top 3 spots in the Digital Pillar in dunnhumby's 2024 US RPI Rankings. ✅ The club channel channel displays an interesting trend in the chart below as well. Club stores, like Costco Wholesale and Sam's Club, see an initial bump up in market share as people start their families (bulk packs on diapers, formula and baby wipes probably have something to do with that...), but the channel gives this back to mass as families mature past this initial stage. This hits Costco harder than Sam's, most likely because Sam's Club has better online shopping and app perceptions. 68% of Sam's customers agree they have easy online shopping, versus only 56% of Costco customers. While 59% of Sam's customers agree their app makes shopping easier, compared to only 31% for Costco. ✅ A better app that makes information, products and savings easier to find, a seamless omnichannel experience and the right better-for-you SKUs in the right categories will carry the day with the most valuable grocery segment: families.