Impact of Retail Economics

UK retailers face a £5.6bn surge in costs this financial year – equivalent to 195,000 full-time retail jobs – forcing the industry to ramp up prices, cut costs, and take a profit hit.   From this week, retailers are grappling a combination of rising direct taxes following the Budget, including: ·      Employer National Insurance hikes (£2.48bn of additional costs in 2025/26): The biggest financial concern by half of retailers, disproportionately affecting small and medium-sized businesses. ·      Higher minimum and national living wages (up £2.36bn in 2025/26): Particularly worrying for food retailers reliant on lower-wage frontline staff. ·      Changes to business rates relief (rising £0.72bn this year): A bigger concern for large retailers, reflecting larger portfolios across stores, warehouses, and distribution centres.   With operating costs up, nine in 10 retailers have calculated the potential Budget burden, implementing strategies to mitigate against the impact. Based on interviews with 100 UK retailers (turnover between £10m and £5bn), businesses will use a range of different measures according to our analysis (Retail Economics and YOOBIC): ·      Cost optimisation (£2.08bn of cost savings): Investing in operational efficiency, automation, and restructuring to mitigate rising costs without eroding margins.   ·      Absorbing costs (£1.76bn hit to pre-tax profits): Accepting a reduction in profits rather than passing costs onto customers. Large retailers are more likely to absorb costs, leveraging financial strength. represents a 6.7% drop in industry profits year-on-year   ·      Price increases (£1.72bn of costs passed onto consumers): Adjusting pricing strategies to offset rising expenses. Online retailers are hesitant due to high price transparency, while store-based retailers are more likely to adjust pricing with localised strategies.   Retailers are prioritising cost optimisation, focusing on efficiency and productivity to offset rising costs. While no single solution dominates, digital transformation and automation is being pursued by a quarter of retailers, including almost half of food retailers, accelerating digital investment to redefine processes, colleague engagement and shopper interactions.   Great to discuss our research with The Telegraph’s Hannah Boland, Retail Week’s George Arnett, Retail Gazette’s Georgia Wright, Retail Sector’s Heather Sandlin, Drapers' Anne Bruce, ESM - European Supermarket Magazine’s Dayeeta Das, and The London Standard’s Jonathan Prynn.   The report is well worth a read, linked below, exploring how retailers are mitigating costs and investing in new processes ⬇️ https://lnkd.in/ehSK5JGU ____________________________________ ⤴ Follow me for weekly retail, consumer and economic insights. ____________________________________

Inflation isn’t just an economic challenge—it’s a test of agility for businesses. As costs rise and purchasing power shifts, companies that rely on gut instinct risk falling behind. The real winners? Those who use data-driven insights to navigate uncertainty. 1️⃣ Understanding Consumer Behavior: What’s Changing? Inflation reshapes spending habits. Some consumers trade down to budget-friendly options, while others delay non-essential purchases. Businesses must analyze: 🔹 Spending patterns: Are customers shifting to smaller pack sizes or private labels? 🔹 Channel preferences: Is there a surge in online shopping due to better deals? 🔹 Regional variations: Inflation doesn’t hit all demographics equally—hyperlocal data matters. 📊 Example: A retail chain used real-time sales data to spot a shift toward economy brands, allowing it to adjust promotions and retain price-sensitive customers. 2️⃣ Pricing Trends: Data-Backed Decision-Making Raising prices isn’t the only response to inflation. Smart pricing strategies, backed by AI and analytics, can help businesses optimize margins without losing customers. 🔹 Dynamic pricing models: Adjust prices based on demand, competitor moves, and seasonality. 🔹 Price elasticity analysis: Determine how much a price hike impacts sales before making a move. 🔹 Personalized discounts: Use customer data to offer targeted promotions that drive loyalty. 📈 Example: An e-commerce platform analyzed customer behavior and found that small, frequent discounts led to better retention than infrequent deep discounts. 3️⃣ Demand Forecasting & Inventory Optimization Stocking the right products at the right time is critical in an inflationary market. Predictive analytics can help businesses: 🔹 Anticipate demand surges—especially in essential goods. 🔹 Optimize supply chains to reduce excess inventory and prevent stockouts. 🔹 Reduce waste in perishable categories like F&B, where price-sensitive demand fluctuates. 📦 Example: A leading FMCG brand leveraged AI-driven demand forecasting to prevent overstocking of premium products while ensuring budget-friendly variants were always available. 💡 The Takeaway Inflation isn’t just about rising costs—it’s about shifting consumer priorities. Companies that embrace data-driven decision-making can optimize pricing, fine-tune inventory, and strengthen customer loyalty. 𝑯𝒐𝒘 𝒊𝒔 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝒂𝒅𝒂𝒑𝒕𝒊𝒏𝒈 𝒕𝒐 𝒊𝒏𝒇𝒍𝒂𝒕𝒊𝒐𝒏𝒂𝒓𝒚 𝒑𝒓𝒆𝒔𝒔𝒖𝒓𝒆𝒔? 𝑨𝒓𝒆 𝒚𝒐𝒖 𝒖𝒔𝒊𝒏𝒈 𝒅𝒂𝒕𝒂 𝒕𝒐 𝒓𝒆𝒇𝒊𝒏𝒆 𝒚𝒐𝒖𝒓 𝒔𝒕𝒓𝒂𝒕𝒆𝒈𝒚? 𝑳𝒆𝒕’𝒔 𝒅𝒊𝒔𝒄𝒖𝒔𝒔 𝒊𝒏 𝒕𝒉𝒆 𝒄𝒐𝒎𝒎𝒆𝒏𝒕𝒔! #datadrivendecisionmaking #dataanalytics #inflation #inventoryoptimization #demandforecasting #pricingtrends

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

“Offline is dying.” “Everything is moving to quick commerce.” Then why did Swiggy Instamart just open a physical store? That’s the real question. For years, the narrative has been simple: Speed wins. Convenience wins. Physical retail loses. But reality is more nuanced. If online convenience was enough, the biggest quick-commerce player wouldn’t invest in brick-and-mortar. Yet they did. Why? Because commerce is not just about delivery time. Even after 10-minute deliveries, customers still value: Touching the product Discovering new items serendipitously Immediate gratification without a screen Trust built through physical presence Online solves access. Offline solves experience. The future isn’t online vs offline. It’s online + offline, tightly integrated. Physical stores are no longer inventory hubs. They’re: Brand theatres Trust anchors Data collection engines Hyperlocal demand signals Swiggy didn’t open a store because online is failing. They opened it because online alone is incomplete. The brands that will win aren’t choosing sides. They’re building distribution moats across both worlds. Offline isn’t dying. It’s being redefined. And the smartest digital-first companies already know it. #FutureOfRetail #QuickCommerce #Omnichannel #RetailTrends #ExperientialRetail

U.S. Retail Sales Surge in March as Consumers Race to Beat Tariffs   American consumers continued to front-run tariffs in March, with retail sales posting their strongest monthly gain since 2023.   🔹 Headline retail sales rose 1.4% in March, matching lofty market expectations. The increase was largely fueled by strong demand for autos and construction materials—signaling a clear shift in consumer behavior as buyers moved to lock in purchases ahead of expected tariff hikes.   Crucially, the so-called "control group"—which strips out volatile components like autos, gas, and building materials, and serves as a better proxy for GDP—also showed impressive strength. It rose 0.6% month-over-month and 3.5% on a three-month annualized basis. This suggests resilient underlying consumer demand, offering a potential counterweight to recent concerns about slowing economic momentum.   🔻 Indeed, many forecasters had downgraded their GDP estimates for Q1 into negative territory, citing weak spending. But March’s robust retail performance may prompt some to revisit those projections. Still, uncertainty lingers: it’s not yet clear whether the retail surge was offset by a corresponding rise in imports. March’s trade data—due just one day before the first GDP estimate—is likely to provide more clarity.   While consumer confidence has plunged to multi-year lows amid growing anxiety over trade policy, falling gasoline and commodity prices have helped cushion the blow. That’s freeing up room in household budgets for discretionary spending—for now.   However, this window may be short-lived. With the bulk of new tariffs set to take effect in April and policy uncertainty remaining high, consumers could soon shift into wait-and-see mode, pulling back on spending as risks mount.  

Your FMCG pricing team spent weeks building that price architecture. An AI just changed it in milliseconds. Welcome to 2026. This is what's actually happening right now in FMCG pricing: Dynamic pricing has evolved into a primary offensive weapon; algorithms monitor competitor stock levels and price changes in mere milliseconds. If your competitor drops the price of a hero product:baby formula, shaving cream, laundry detergent; their A I has already matched or undercut you before your pricing team has opened their laptop. AI software spending in FMCG is expected to hit $4.3 billion by 2026. FMCG businesses taking a data-driven approach to revenue growth management are witnessing sales growth of 3% to 5%. At Unilever scale; that's billions. But AI pricing isn't just about margins. It's creating an entirely new competitive battleground. Agentic bots now lurk in the background, flagging consumers browsing competitor sites and serving them a one-time discount code in real time. This allows brands to lower prices for specific consumers without undermining their wider market price. Read that again. Your brand has a public price. And a private price. Determined in real time by an algorithm. For each individual consumer, the price on the shelf is becoming fiction. And the consumer knows it. FMCG consumers are becoming increasingly hypervigilant of shrinkflation and algorithmic pricing and when prices fluctuate wildly, trust erodes fast #FMCG #CPG #AIpricing #RevenueGrowthManagement #BrandStrategy #Pricing

March retail sales boosted by Pre-Tariff Auto Buying. Other sales show moderate growth. Retail sales in March had their strongest monthly gain in more than three years, rising 1.4%, according to today's advance report from the US Census Bureau. But auto sales represented 2/3 of the overall gain, as consumer moved up new auto purchases ahead of US auto tariffs. Other categories expanded at a more moderate pace. Total retail and food service sales other than for motor vehicles & parts rose about 0.5% on the month, slightly weaker than in February. Growth was strongest in building materials & garden equipment and food service & drinking establishments, but nearly all types of retailers saw some sales gains. Gasoline sales fell along with pump prices, and sales at non-store (mostly online) outlets were flat after a February surge. Pre-tariff buying likely played a supporting role in many of these non-auto categories, but it is impossible to know how much. (Retail sales are very volatile month-to-month, so attributing changes to particular causes should be taken with a grain of salt.) That said, the strong performance is welcome considering the sharp drop we have seen in consumer sentiment. Nevertheless, expect retail sales to soften in coming months as tariffs begin to filter into retail prices and as overall consumer spending slows. #retailsales #tariffs #motorvehicles #consumersentiment

FOMO works in B2B! Behavioural studies on scarcity show a clear pattern: when something is both desired and genuinely limited, people decide faster, assign it higher value, and are more likely to commit. When demand is weak, though, layering on urgency – countdown timers, “last few spots”, fake limits – tends to backfire, creating scepticism rather than sales. Humans don’t just respond to scarcity itself; they respond to what scarcity signals. Limited access suggests that others value it, that capacity is constrained for real reasons, or that the opportunity won’t be available in the same form again. In that context, FOMO doesn’t create demand from thin air; it nudges already-interested buyers out of indecision and into action. Practically, this means scarcity tactics are most effective when they sit on top of clear intent signals: people are visiting the page and returning, asking questions, joining a waitlist, or engaging with your content. In those moments, stating real constraints – a fixed cohort size, genuine capacity limits, a true deadline – helps buyers make a confident choice instead of endlessly circling the decision. What that means for your brand: FOMO should be a spotlight, not a smoke machine. Use scarcity to highlight real demand and real constraints, protect trust by avoiding artificial pressure, and design your campaigns so urgency accelerates good-fit decisions instead of trying to manufacture interest that isn’t there.

This morning’s U.S. retail sales report landed squarely in “never judge a book by its cover” territory. Headline sales for March rose +1.4%, surpassing both consensus expectations and February’s +0.22% figure, but a deeper dive into the data reveals some concerning details: (1) Sales growth was highly concentrated in motor vehicles and building supplies (see accompanying chart), two areas likely to be among the most heavily affected by new U.S. tariffs; (2) The retail sales “control group,” which excludes autos, building materials and gasoline, and is considered a more precise gauge of consumer spending for the purpose of GDP calculations, increased just +0.4%in March, failing to meet the +0.5% consensus. What do these devilish details mean for investors? We think March’s favorable headline retail sales print is more likely a result of consumers accelerating purchases to get ahead of U.S. tariff implementation than a true indication of a rebound in consumer spending. This view is supported by the dramatic decline in nonstore retail sales growth, which collapsed from +3.2% in February to a meager +0.1% in March. Additionally, we anticipate that “hard” data (quantifying actual economic activity, such as retail sales) will soon begin to show the negative impact of trending weakness in “soft” data (such as consumer sentiment surveys) — perhaps beginning with releases covering the month of April. This could translate into continued market volatility, as deteriorating consumer resilience poses a potentially serious headwind to the broader economy.

Paying pharmacies less than it costs to dispense a drug is one way to reduce pharmacy spend. But what happens if the pharmacy closes? --- MedPAC shared data a few months ago showing that independents close where alternatives don't exist, and that 33% of rural Part D beneficiaries already live in zip codes with no pharmacy at all. A new IQVIA analysis offers more data to what comes next. 📍 Rural pharmacies are not interchangeable with metro ones ↳ When a metro pharmacy closes, roughly 15% of that zip's patients had used it as their pharmacy ↳ When a rural pharmacy closes, that share is 54% ↳ Rural zip codes average fewer than 3 pharmacies. Metro zip codes average 9. 📊 Each rural closure in 2025 displaced ~3,000 patients and 35,000 prescriptions 💉 Flu vaccination rates collapsed after rural pharmacy closures ↳ Among rural patients who received a flu vaccine at a pharmacy that later closed, 63-70% did not get a flu vaccine the following season ↳ The comparable figure for metro patients was ~54% (honestly, still not great) 🚗 For rural patients who did find another pharmacy, the distance more than quadrupled ↳ Median distance to the next pharmacy: ~2.9 miles in the 2021-22 flu season ↳ That grew to 13.6 miles by the 2023-24 flu season ↳ Metro distances were steady at 3-4 miles This exact issue hit the independent pharmacy I worked at during school. It closed in 2023 and the next nearest pharmacy is 13.1 miles away now. --- The reimbursement picture behind these closures is not complicated. Dispensing fees often don't cover the cost of acquiring and dispensing a drug (it's supposedly already paid through the ingredient cost reimbursement). Clinical services pharmacists provide are largely not reimbursed at all. Filling more prescriptions at low or negative margins doesn't keep the lights on. --- The system captures short-term savings, but the long-term cost is access. Somewhere in the math of preferred networks and below-cost reimbursement is the assumption that if a pharmacy closes, another pharmacy will pick up the patients. In rural areas, that assumption is increasingly wrong. 🔗 Source: IQVIA https://lnkd.in/eRE9Fu9Z ♻️ Repost to share what rural pharmacy closures actually cost patients 🔔 Follow me for more on pharmacy economics and access (Bryce Platt, PharmD)