Retail & Merchandising

"Is $20/month too much for our product?" Instead of guessing, we used the Van Westendorp method to find our pricing sweet spot. 4 questions revealed exactly what users would pay (and we haven't touched our pricing since). Here's the framework any founder can steal: 1. Send a survey to actual users, not prospects We surveyed people already using Gamma. They understood the real value of our product, not hypothetical value. Too many founders survey their waitlist or randomly select people who have never used their product. That's like asking someone who's never driven about car prices. 2. Ask these 4 specific questions - At what price would this be too expensive for you to consider it? - At what price is it expensive but still delivering value? - At what price does it feel like a bargain? - At what price is it so cheap you'd question if it's reliable? These create bookends for perceived value. You're mapping the entire spectrum of price psychology, not just asking "what would you pay?" 3. Plot the responses and find where the lines intersect Graph responses from lots of users. Where "too expensive" and "too cheap" lines cross: that's your acceptable range. Where "expensive but fair" meets "bargain": this is your optimal price point. 4. Test within the range, don't just pick the middle The intersection gives you a range, not a number. We ran pricing experiments within that range to see actual conversion rates. A survey shows willingness to pay; testing reveals actual behavior. 5. Lean towards generous (especially for product-led growth) We chose to be more generous with AI usage than our "optimal" price suggested. Word-of-mouth growth matters more than maximizing initial revenue. Not everything shows up in the numbers. 6. Lock it in and stop tinkering Once you find the sweet spot through data, stick with it. We haven't changed pricing in 2 years. Every month debating pricing is a month not improving product. Remember: pricing is a signal, not just a number (Image: First Principles)

One image just disrupted a £22 billion fashion empire more effectively than a thousand sustainability reports. 🔥 This isn't an official SHEIN campaign gone wrong. It's artist Emanuele Morelli's AI creation—a haunting visualisation showing what fast fashion's "affordability" really costs us. The image speaks volumes: a SHEIN billboard where the model's flowing dress transforms into a cascade of textile waste. Art communicating what statistics alone cannot. 5 uncomfortable truths this image forces us to confront: 1. The scale of fashion waste is staggering → 92 million tonnes of textile waste produced annually  → The equivalent of one rubbish lorry of textiles dumped every second  → Most fast fashion items designed to be worn fewer than 10 times 2. The business model depends on our amnesia → Constantly changing trends keep us buying  → Ultra-low prices remove financial friction  → Digital marketing creates artificial scarcity and FOMO  → We're trained to forget yesterday's purchases 3. The true cost isn't on the price tag → Environmental damage from production chemicals  → Microplastics shedding into water systems  → Supply chain ethics compromised for speed and cost  → Communities near production sites bearing health consequences 4. Our definition of "affordable" is broken → When clothing is cheaper than a coffee, someone else is paying  → True cost spread across communities, environments, and future generations  → Psychological cost of constant consumption never factored in 5. Solutions exist but require systemic change → Circular fashion models gaining traction  → Rental and resale markets growing rapidly  → Consumer awareness rising but needs to translate to behaviour While SHEIN isn't the only culprit in the fast fashion ecosystem, Morelli's artwork throws a spotlight on an uncomfortable reality we've normalised. What we wear reflects our values more than our taste. What is your wardrobe saying about yours? Image: Emanuele Morelli ♻️ Found this helpful? Repost to share with your network.  ⚡ Want more content like this? Hit follow Maya Moufarek.

Loyalty is failing. Gen Z & long-term commitment. 22% of Gen Z consumers consider themselves loyal to one brand is a clear warning for legacy loyalty strategies. Unlike previous generations, Gen Z doesn’t see brand loyalty as a long-term commitment, they’re loyal to moments, not just names. +43% increase in engagement and sales conversions among Gen Z Beauty brands offering "limited-edition drops" and collaborative experiences. +71% Gen Z say they would rather spend money on an experience than a product. >>Loyalty is FAILING, but why<< +Transactional systems feel outdated: Point-based rewards for repeat purchases don’t excite this audience. They expect more than discounts or free samples. +They’re brand-agnostic but experience-driven: Gen Z freely switches between brands if the experience, aesthetic, or values feel fresher or more aligned with their identity. +They buy into stories, not just products: They want to align with brands that represent something, social causes, cultural movements, or communities they relate to. >>DYNAMIC LOYALTY<< What’s this? as it name indicates its a system that rewards interaction, aligns with their values, and constantly evolves. And that is what your brand needs. → Create experience-driven loyalty programs: Offer early access to limited drops, invite-only events, or backstage content. Think like a fan club, not a punch card. +Example: A loyalty tier that unlocks tickets to a pop-up experience or an exclusive AR filter. →Let them co-create: Invite Gen Z customers to co-develop product ideas, designs, or campaign themes. Give them ownership in your brand’s creative journey. +Example: Voting on packaging designs or joining beta tester groups. →Align with their values: Sustainability, inclusivity, and social good aren’t nice-to-haves. they’re expectations. Use loyalty programs to reward actions too, like recycling, sharing causes, or supporting small creators. +Example: “Earn loyalty points by returning empties or attending a sustainability workshop.” →Deliver constant novelty: Rotate limited editions regularly. Use scarcity and surprise to create FOMO and buzz. +Gen Z doesn’t commit to a single brand, but they’ll keep returning if each visit feels fresh and share-worthy. →Go omnichannel but social-first. Should live across TikTok, Instagram, pop-ups, and web. Let them earn or unlock rewards through social engagement, not just purchases. +Example: A user gets exclusive content or perks for creating UGC with your brand. Bottom Line. Loyalty must be earned over and over through experience, relevance, and emotional connection. Think dynamic loyalty: a system that rewards interaction and go for it. Find my curated search of examples and get ready for your next HIT. Featured Brands: Balmain Benefit Chanel Charlotte tilbury Cerave Fennty L’Oreal OGX YSL #beautypackaging #beautybusiness #beautyprofessionals #experienceretail #luxuryexperiences #genz

A very easy way to improve your Amazon ads efficiency by at least 10% Let’s say you’re spending ₹4–5 lakhs/month on Amazon ads. Your ACoS looks okay. Conversion rate seems fine. But your gut tells you—you’re still wasting some money on irrelevant traffic You’re not wrong At Atomberg, we had found that some of our Amazon spend was going toward search terms that had no business seeing our ads: - “cheap fan” -“rechargeable fan” - “usb fan under 1000” None of these users were in-market for a ₹3,000+ BLDC ceiling fan. But we were still showing up. And paying for those clicks. And it’s not just us. I’ve seen 6–7 brands' Amazon ad accounts across categories over the last few years—same problem, every single time The fix? N-gram analysis Takes less than an hour. You don’t need to be a performance marketing expert. But the results compound What’s N-gram analysis? It’s breaking down every search term into its word components—1-grams, 2-grams, 3-grams—and then identifying patterns that consistently drive waste… or conversion. Example: “cheap rechargeable fan for hostel room” turns into: 1-grams: cheap, rechargeable, fan, hostel, room 2-grams: rechargeable fan, hostel room 3-grams: fan for hostel, etc. When you do this across all your search terms, you start seeing the real picture. Why this matters more than just checking your search term report: Search terms ≠ keywords a) One keyword can trigger 100s of different queries. Some convert. Most don’t. You need to find the patterns. b) Waste is diluted across low-volume terms. Maybe “rechargeable fan for hostel” spent ₹300. You ignore it. But what if 12 other queries with “rechargeable” spent ₹6,000 in total with zero conversions? c) Long-tail is infinite. N-grams are finite. You can’t negate every bad search. But you can block the core terms—“cheap”, “usb”, “mini”—once and be done with it. d) It helps you scale campaigns too. You can find goldmine phrases like “white ceiling fan”, “silent BLDC fan”, “fan for living room”—with 5x+ ROAS. Those became exact match campaigns What you should do: a) Pull last 3 months of search term data b) Break them into unigrams, bigrams, trigrams c) Create a pivot with spend, orders, ROAS by N-gram d) Negate high-spend, low-conversion N-grams (e.g., “cheap”, “rechargeable”) e) Boost high-ROAS ones (e.g., “bldc”, “ceiling fan white”) f) Add exact match campaigns g) Rinse and repeat monthly Try it. Guaranteed to improve efficiency at whatever scale you are operating If you want to read an expanded version of the post, link is in the first comment

For the past two years, CPG brands have been coasting on price hikes to keep revenue numbers up. And now? That strategy is running out of steam. I spend a lot of time talking to CPG leaders, and here’s what I’m hearing as we head into 2025: consumer confidence is weak, volume growth still hasn’t bounced back, and brands can’t rely on price increases anymore. The question I keep getting is—what now? - Global CPG sales grew 7.5% in 2024, but that’s down from 9.3% in 2023 and 9.8% in 2022. - 75% of growth came from price increases—not volume. Better than the 90% in 2023, but still not healthy. - Developed markets are slowing fast. U.S. & EU growth dropped to 4.5% in 2024, and volumes stayed flat. - Emerging markets are driving almost all global volume growth. They saw an 11% sales increase in 2024—twice the growth rate of developed markets. (Bain & Company) For the first time in years, raw material costs aren’t the #1 worry. Instead, every executive I talk to is worried about: 1. More competition for shoppers – Too many brands, not enough differentiation. 2. Consumers spending less – 80% of U.S. & EU shoppers are actively cutting back. 3. Retailers pushing back harder – The pricing power shift is real, and brands are feeling it. And if you look at where consumers are actually spending, the trend is obvious: ✅ Premium brands and private labels are thriving. ❌ Mass-market and mid-tier brands are getting squeezed. ✅ Shoppers want ‘value’—but that doesn’t just mean ‘cheaper.’ It means better quality, stronger differentiation, and clear benefits. So, Where Do CPG Brands Go From Here? - Volume needs to make a comeback. Price hikes won’t cut it anymore—brands have to focus on innovation, relevance, and real consumer connection. - Emerging markets can’t be an afterthought. If you’re only focused on U.S. and Europe, you’re missing the biggest growth engine. - Retailer relationships will define 2025 winners and losers. Brands that offer real category value (beyond price negotiations) will have the advantage. - If you’re stuck in the middle, you’re in trouble. Premium and private label are thriving—where does your brand fit? I’ve had so many conversations lately with CPG leaders trying to figure out their next move. If 2024 was the year of price hikes, 2025 is the year to rethink strategy. What are you seeing in the market? What’s the biggest challenge (or opportunity) for CPG this year? Let’s talk. 👇 #CPG #IndustryTrends #ConsumerGoods #RetailStrategy #FMCG #Executives

Excited to share insights from Walmart 's groundbreaking semantic search system that revolutionizes e-commerce product discovery! The team at Walmart Global Technology(the team that I am a part of 😬) has developed a hybrid retrieval system that combines traditional inverted index search with neural embedding-based search to tackle the challenging problem of tail queries in e-commerce. Key Technical Highlights: • The system uses a two-tower BERT architecture where one tower processes queries and another processes product information, generating dense vector representations for semantic matching. • Product information is enriched by combining titles with key attributes like category, brand, color, and gender using special prefix tokens to help the model distinguish different attribute types. • The neural model leverages DistilBERT with 6 layers and projects the 768-dimensional embeddings down to 256 dimensions using a linear layer, achieving optimal performance while reducing storage and computation costs. • To improve model training, they implemented innovative negative sampling techniques combining product category matching and token overlap filtering to identify challenging negative examples. Production Implementation Details: • The system uses a managed ANN (Approximate Nearest Neighbor) service to enable fast retrieval, achieving 99% recall@20 with just 13ms latency. • Query embeddings are cached with preset TTL (Time-To-Live) to reduce latency and costs in production. • The model is exported to ONNX format and served in Java, with custom optimizations like fixed input shapes and GPU acceleration using NVIDIA T4 processors. Results: The system showed significant improvements in both offline metrics and live experiments, with: - +2.84% improvement in NDCG@10 for human evaluation - +0.54% lift in Add-to-Cart rates in live A/B testing This is a fantastic example of how modern NLP techniques can be successfully deployed at scale to solve real-world e-commerce challenges!

#payments rails across the globe and the models behind them have evolved in three major (but very different) patterns and yet they are converging in certain ways. Let’s take a look. About half a century ago, magnetic-striped cards triggered a payments revolution. Swiping plastic cards at POS merchant terminals conquered the west, with Visa and Mastercard managing the rails and becoming an almost mighty duopoly. Cards made a smooth transition into the digitized #economy by embedding in smartphones (and even turning them into processors) and becoming the springboard for the rise of the #ecommerce. While the west was transitioning from old cards to chips, China was driving its own local payments revolution that erupted at the beginning of the 2000s and transformed the country from a purely cash economy to a #digital frontrunner. Starting from high smartphone penetration and bank account ownership, China essentially leapfrogged the card-based (western) model moving directly to a digital set-up built on e-wallets and QR codes and driven by two private companies (Alibaba and Tencent) that managed to build vast (2-sided consumer and merchant) ecosystems that transformed them into ubiquitous SuperApps. In parallel, a third pole had been developing in other parts of the world: —     The payments revolution in Africa was led by telecoms (being the only infrastructure available) by means of an e-#money set-up based on mobile phones. Companies such as Kenya’s M-Pesa (launched in 2007) managed to provide long needed basic financial services (saving and transferring funds, making payments or accepting government subsidies) to large swaths of the population. —     Countries like India or Brazil developed over the past few years state-sponsored real-time payments infrastructures, powering multiple bank accounts into a single app under A2A and P2P models. India’s Unified Payments Interface (UPI) has over 300 mn monthly active users recording 60% y-o-y growth, whereas Brazil’s Pix, launched only in late 2020, has managed to become the most popular payments’ method with over 150 mn users. These parallel evolutionary developments could hardly have been more different: a robust decades-old, card-infrastructure in the west (monopolized by two private companies), against a digital, wallet-based closed-loop model in China (powered by 2 giant ecosystems), versus public, state-sponsored, open, real-time rails in India and Brazil. Despite their very different origins and set-up, digitization has been acting as a huge convergence driver lately: digital wallets, super-apps, real-time payments and CBDCs (Central Bank Digital Currencies) are only some of the common underlying elements. As payments evolve to their next phase, a new digital infrastructure is in the making, fast bridging seemingly big structural gaps. Opinions: my own, Graphic sources: Credit Suisse, Alipay, Matthew Brenan, BCB, Bacancy, Alicriti

When L'Oréal uses AI to create new hair colors based on social media trends, they're in salons within weeks. Kraft Heinz—dead last in our study—still takes months to tweak a formula. After analyzing 26 major CPG companies at IMD's Center for Future Readiness, I discovered what separates winners from losers: The most future-ready companies treat consumer data like insider trading information. BACKGROUND: CPG in 2025 is brutal. Inflation persists. Gen-Z demands sustainability without premiums. Tariffs reshape supply chains daily. McKinsey & Company identified 150+ AI use cases for CPG transformation. Only 5 of 26 companies actually execute them. THE REVELATION: Coca-Cola didn't randomly launch Topo Chico Hard Seltzer. Their AI spotted the trend through social listening while competitors debated in boardrooms. By launch, they'd secured distribution nationwide. That's not innovation. That's prediction. What separates the top 5: L'Oréal (#1): 3.5% of sales to R&D. AI analyzes preferences real-time. Virtual try-on apps. Creates products from social trends. A 110-year company with startup velocity. The Coca-Cola Company (#2): Democratized AI internally. Every manager accesses demand forecasting. They analyze weather + social sentiment + sales simultaneously. These aren't tech companies selling beauty and beverages. They're prediction machines that happen to make products. THE WINNER'S FRAMEWORK: 1. AI at scale, not in pilots Winners integrate into workflows. Losers run demos. 2. Supply chains that anticipate Real-time visibility + AI forecasting = competitive firepower 3. D2C as intelligence goldmine 73% use multiple channels. Mine every interaction. 4. Disrupt yourself first Coca-Cola launched Costa Coffee, hard seltzers. Grew. Kraft Heinz protected legacy brands. Shrank. 5. Sustainable without premium Gen-Z spending hits $12T by 2030. They demand action at everyday prices. —— The inconvenient truth: Most CPG companies treat data like reporting instead of radar. Winners don't predict trends—they're already shipping products while competitors debate. Technological patience (knowing when to scale) + organizational agility (pivoting fast) = market domination. Three years from now, every CPG company operates like L'Oréal. Or they don't operate at all. P.S. Full Future Readiness Indicator here: https://bit.ly/3YTBzbX

With most Q2 results in, we’re getting a picture of retail performance. 🔄 A bit like in Uno, the reverse card is being played. Some retailers that have been performing badly are starting to see declines bottom out or are moving into modest growth (think Best Buy, Target, Foot Locker, Peloton, Victoria’s Secret, Gap). 📉 In contrast, some of the traditional star performers are struggling to keep up the fast pace and are seeing a slowdown (think Lululemon, Ulta, Dollar General). 💰 Are economic dynamics playing a role here? Partly. But strategy and competitive forces remain critical. Ulta has more competition, so too does Lululemon which failed to inspire with its womenswear in Q2. Target has recently invested a lot in price and value. Foot Locker, Victoria’s Secret and Gap all have turnaround programs. 🤔 On this front, don’t always buy the narratives retailers spin. Dollar General blames its weaker numbers on pressures on its customers. There is truth in this, but it has been true for a long time. The issue now is that inflation is not flattering the growth as much and there is more price competition in grocery. Oh, and some stores are terrible and are preventing sales and repeat visits.  🖼️ The long-term picture remains vital because quarterly results fluctuate and create noise. An example is Nordstrom, which has 3.4% growth this quarter, versus Dillard’s which has a 4.9% decline. Look at the Q2 numbers compared to 2019, and Dillard’s has grown sales by 4.4% while Nordstrom’s sales have grown by just 0.2%. A long term view is sometimes a better signal of the health of the business model. 🏡 Home related categories remain very pressured. A lot of this is linked to the more sluggish housing market: moving is an important driver of demand. Some bigger ticket purchases are financed, so high interest rates play a role too. ↔️ The market remains polarized with a balance of winners and losers. Out of the selection in the graph below, 17 retailers are in growth and 18 are in decline. 🐌 Growth rates have, generally, deteriorated since Q1. From the retailers shown below, 21 have lower growth rates than in Q1, 14 have higher growth rates. The average, overall growth rate has dropped by a modest 0.5 percentage points since Q1. So no recession, but some modest slowdown. #retail #retailnews #earnings #consumer #economy #shopping

With the likes of B&M Retail, Poundland & Dealz and Primark coming under pressure, are we falling out of love with discounters? Britain isn’t, but our relationship is evolving. Consumers are savvier, competition is fiercer, and legacy players need to evolve to stay relevant against changing shopping behaviours. The surge during the cost-of-living crisis, when middle-class shoppers embraced value retailers, was always going to be difficult to sustain. Now, with discretionary incomes gradually recovering, we’re seeing selective spending on small indulgences and experiences. That said, middle-income families remain under pressure, squeezed by rising housing costs, rent hikes, and debt repayments. The least affluent households, who are core discount shoppers, are feeling the brunt of the squeeze. Their discretionary income remains lower than 2021 levels, reinforcing price sensitivity as the economy navigates a long and uneven path toward stable inflation and growth. But structural issues are also at play. Competition is brutal. Traditional grocers such as Sainsbury's and Tesco have aggressively defended market share with Aldi UK price matches and membership pricing to stave off German discounters. Meanwhile, SHEIN and Temu are rewriting the rules of discount retail in non-food, offering ultra-low prices with ultra-convenience that undercut traditional high street players. At the same time, discounters have struggled with rising prices, eroding their appeal. The omnichannel gap is widening. Primark’s strong click-and-collect performance of late highlights what high street discounters traditionally lack: seamless digital integration. Without it, they risk losing shoppers to cheap online rivals, particularly in clothing and homewares, leaving big box players with excessive store space. Recommerce is also surging. The cost-of-living crisis has accelerated pre-loved shopping just as technology has made second-hand retail more accessible. The likes of marketplace Vinted and parcel locker service InPost make fragmented second-hand spending easier than ever. This interest isn’t going away. We estimate UK recommerce is worth over £6bn today and is set to double to over £12bn by 2028 (Retail Economics, MPB). Concerningly, discounters face another squeeze: rising tax burdens. Retailers must decide whether to absorb costs, automate, or pass on higher prices. In any case, price alone is no longer enough. Long-term resilience depends on product proposition, agility, and digital integration. Great to discuss this with The Times’ Isabella Fish – article linked below. https://lnkd.in/eJUpqa6J ____________________________________ ⤴ Follow me for weekly retail, consumer and economic insights. ____________________________________