“Sorry, we don’t have any more in that size.”

Out-of-stock sizes rank as the top complaint among shoppers. Inaccurate stock purchasing across sizes is estimated to result in profit loss of up to 20% on average a month. In today’s retail climate, precision is everything. With shifting consumer preferences and compressed product lifecycles, the margin for error has never been smaller. One area where we consistently see brands leaving revenue on the table? Size allocation.

The Power of Localized Size Profiles

Too often, size profiles are applied broadly across regions—or worse, chain-wide—without accounting for localized demand signals. A best-selling medium in one district could be deadstock in another. Getting the right products in the right size, to the right store, at the right time is no longer optional—it’s essential.

Localized size profiles enable brands to fine-tune allocations down to the store or region level based on actual demand, not assumptions. But creating these profiles manually is time-consuming, and static models quickly fall out of sync with current selling trends.

That’s where AI steps in.

AI + Real-Time Data = Smart Allocation and Assortment Planning Software

Retailers are increasingly turning to AI tools to overcome challenges in balancing demand, availability and profitability. AI enables a more agile, responsive approach to assortment planning through granular insights on real-time data. Risk is reduced as production decisions are informed by what actually sells, cutting down on waste and markdowns.

Leverage advanced AI and machine learning models to analyze real-time POS data, identify emerging demand drivers and detect shifting size curves as they happen. This means brands can automatically adjust allocations based on what’s actually selling—down to the store level.

Our AI models factor in:

• Local climate and demographics
• Historical sell-through performance
• Category-level trends and seasonality

The result? More accurate demand forecasts, optimized size runs and fewer markdowns.

The Bottom Line

Localized size profiles powered by AI aren’t just a nice-to-have—they’re a competitive advantage. With today’s tools, retailers can stop relying on intuition and start making data-backed allocation decisions that drive full-price sell-through, reduce stockouts and increase margins.

Are you ready to turn your size profile strategy into a growth driver? Talk to the team at info@7thonline.com or book a demo. 

According to a recent survey conducted by 7thonline, 34% of retail leaders are concerned about declining consumer spending for this year—and this fear isn’t unfounded. May’s retail sales data was released this week, declining more than expected with the biggest drop in four months. However, apparel sales tell a different story. 

Excluding automobiles, gasoline, building materials and food services, May’s “core” retail sales increased .4%, after an upwardly revised .1% fall in April, suggesting a modest pick up in consumer spending this quarter; clothing sales rose by 10bps between April and May. However, downside risks to consumer spending are rising: slower labor market, student loan repayments resuming, tariff-induced stock market volatility, etc. While tariffs have had a clearer impact on large-ticket items, markets are signaling a slowdown for the second half of the year as tariffs begin to weigh on disposable incomes, according to Michael Pearce, deputy chief economist at Oxford Economics. 

7thonline’s survey of 100+ retail executives revealed that 73% of leaders are expressing concern over rising tariffs over the next year, with over 1 in 3 confessing their first response to new tariffs would be to adjust product pricing. Some retailers have been transparent about their plans to hike prices but others have not yet disclosed their strategies. 

“Past experience suggests the biggest price rises will come in July, though the full impact of the tariffs likely will emerge across the whole of the remainder of the year,” said Samuel Tombs, chief US economist at Pantheon Macroeconomics.

Despite distress around consumer spending, price adjustment is the go-to move due to low margins—over 75% of retailers said that they would be unable to absorb more than a 25% increase in tariff costs. 7thonline CEO, Max Ma, shared with Sourcing Journal that because margins are slim, navigating spending discretion amid increased tariffs is especially challenging but “many retailers…are pressuring their suppliers to lower prices, so they’re trying to do it on both sides.”

Here are five more strategies retailers and wholesalers can adopt to offset the cost of tariffs: https://www.7thonline.com/post/five-tariff-strategies-for-retail

While tariff news and fears may have come off their peak, the effects are still yet to be fully seen. To learn more about how your team can use AI to navigate shifting consumer demand, email us at info@7thonline.com or book a demo with our team.

Key Takeaways

• 33% of retail executives are currently using AI to analyze data/forecast demand.
• Over 1 in 5 retail executives lack confidence in their supply chain’s ability to handle disruptions.
• 73% of retail executives express concern about additional increases in tariffs over the next 12 months.
• 35% of retail executives say their first response to a new tariff increase would be to adjust product pricing. 

Evolving demand, rising tariffs and rapid advancements in AI are reshaping the retail landscape. This report analyzes how retail leaders are adapting their strategies in 2025, drawing on insights from a survey of over 100 retail executives. From supply chain confidence to technology adoption, the findings offer a look into the challenges and priorities shaping today’s retail strategy.

Demand Is Shifting—and Retailers Are Feeling the Pressure

While 36% of executives say demand has increased, a larger share (39%) report a decline. With 1 in 10 admitting their forecasting is poor and concerns mounting over consumer spending and rising costs, retail leaders are navigating a highly complex demand landscape.

As consumer demand shifts, retailers are seeing the strongest growth through branded ecommerce channels, with 33% reporting increased activity on their own sites. This suggests that more consumers are seeking direct-to-brand experiences, while traditional in-store retail and social commerce are capturing a smaller share of emerging demand.

Retailers Are Reinforcing Supply Chains—But Confidence Remains Mixed

More than 1 in 5 retail executives say they’re not confident in their supply chain’s ability to manage disruptions. To reduce risk, many are cutting inventory levels, diversifying suppliers and making infrastructure investments aimed at improving flexibility and resilience.

To reduce inventory risk, retailers are taking tactical steps like cutting inventory levels and diversifying suppliers—but their long-term focus is shifting toward smarter merchandise planning. More responsive pricing strategies (20%) and speed to market (14%) top the list of investment priorities, reflecting a push to become more agile amid ongoing supply chain uncertainty.

Tariff Pressures Are Forcing Retailers to Rethink

With 73% of retail executives expressing concern about rising tariffs over the next year, many are already weighing how to manage increased costs. From passing costs onto consumers to renegotiating supplier terms, retailers are navigating complex decisions in an uncertain economic environment.

Half of retail executives have yet to take specific action in response to rising tariff costs, but among those who have, the most common strategies include passing costs to customers (24%) and absorbing them internally (22%). Most retailers say they could only absorb a 25% tariff increase or less before needing to raise prices, and 35% say their first response to a new increase would be to adjust product pricing—highlighting how limited their flexibility truly is.

Retailers Are Cautiously Exploring AI—But Barriers Remain

A third of retail executives are already using AI to forecast demand, and 34% expect it to play a major role in sustaining or growing profits within the next two years. While most are maintaining their current tech investments, adoption is still limited by internal expertise gaps, budget constraints and uncertainty about ROI.

Retailers are exploring a range of AI applications, with marketing, inventory management and pricing optimization leading the way. Only 16% are currently using AI for demand forecasting—despite growing recognition of its potential. 

What’s Ahead for Retail Strategy

Retailers are balancing immediate pressures with long-term priorities—from managing tariff impacts to cautiously adopting innovative technology such as AI. As 2025 unfolds, building flexibility, improving forecasting and investing in strategic planning will be key to staying competitive.

Methodology

7thonline surveyed 105 retail executives about their retail strategy from June 2-11, 2025. Of the respondents that disclosed their job title, 53% were C-suite executives, 16% were owners and 8% were directors. 

7thonline is a leading AI-powered retail planning and forecasting software, enabling more effective planning, demand forecasting and inventory optimization for leading retailers and wholesalers. With embedded business intelligence and rich analytics, the solution offers complete demand visibility and planning capabilities at the most granular level. To learn more about our suite of solutions, book a demo or email us at info@7thonline.com. 

Merchandise assortment planning has undergone a major transformation over the past few decades—from manual processes and spreadsheets like Excel to various planning systems. Tech advancements in retail added some structure but many still relied on guesswork, labor-intensive processes and siloed data.

As the retail landscape became more complex (such as with the rise of omnichannel) and consumer expectations rose, the need for sophisticated tech solutions became even more pronounced. That growing complexity paved the way for artificial intelligence to transform how retail brands think about their merchandising strategy.

Why Retailers Still Struggle: Common Pain Points

Despite advances in technology, many retailers continue to face stubborn pain points leading to off-the-mark inventory decisions. Data is often fragmented and scattered across teams and systems, resulting in information overload without actionable insight. Adding to the challenge: the expansion of omnichannel operations, global supply chain disruptions, tariffs, market saturation, waning brand loyalty and more. The stakes are too high for patchy assortment strategies. 

In 2023, the fashion industry produced between 2.5 and 5 billion units of excess stock. That’s up to $140 billion in lost sales, according to Business of Fashion. Meanwhile, consumers are frustrated—brands are losing out on an average of 20 percent in monthly profit due to out-of-stock sizing, a shopper’s biggest complaint.

The AI Advantage: Balancing Art and Science

Retailers are increasingly turning to data-driven tools to overcome these challenges—and strike the right balance between demand, availability and profitability with AI-powered tools. A recent study found that 75 percent of fashion executives plan to adopt advanced analytics and AI to automate key processes, from forecasting to inventory allocation, in 2025. These proactive strategies are already delivering results for forward-thinking brands; they reported AI has improved stockouts by as much as 25 percent. AI enhances the art of merchandising and strengthens it through powerful data-backed insights. Creativity and brand identity still matter, but now they’re supported by real-time, data-informed decision-making.

Data-Driven Retail Decisions and AI-Powered Merchandising

AI enables a more agile, responsive approach to inventory planning. It processes vast datasets in real time, revealing insights that manual processes would miss or take weeks to uncover. Forecasting becomes more precise by analyzing historical trends at a granular level. Risk is reduced as production decisions are informed by what actually sells, cutting down on waste and markdowns. And with full visibility across channels, teams can better align around performance metrics for DTC, wholesale and ecommerce. A single source of truth empowers smarter collaboration across departments from design and production to planning and finance. 

As manual errors decline and efficiency improves with smarter planning, customer satisfaction rises. Meeting demand with the right products in the right sizes at the right locations ultimately drives profitability and strengthens brand performance.

Steps to Perfecting Merchandise Assortment with AI

Perfecting merchandise assortment with AI begins with smarter planning. Retailers must analyze past sales and behavioral data to uncover not just what sold, but why. AI uncovers deeper insights, including customer affinities and regional preferences, to guide more targeted assortment decisions.

Next, teams must align around common inventory goals, lead times and budget constraints. When all departments operate from the same playbook, planning becomes proactive rather than reactive.

Then, it’s all about placement, which products to put where, when. AI enables retailers to determine the most optimal localized assortment mix, determined by each SKU’s propensity to sell at each location, based on demand drivers like weather patterns. By combining push strategies, using preset rules like store size and sales volume, with pull strategies driven by real-time demand, retailers ensure each store has the essential stock.

Once inventory runs out, it’s time to replenish. AI also enhances replenishment strategies; when items sell, inventory can be shifted from other locations or reordered as needed. This adaptability reduces the risk of overproduction and keeps shelves stocked.

Continuous Optimization: Analyze, Forecast, Repeat

Assortment planning doesn’t end once the product lands in shoppers’ hands. AI thrives on continuous data feedback, improving forecasting models with every cycle. Over time, planning becomes more accurate, responsive and aligned with customer demand.

Perfecting your merchandise assortment with AI isn’t about removing human insight—it’s about unlocking its full potential. By turning complex data into clear direction, AI helps retailers thrive in a world where speed, precision and personalization are no longer optional—they’re essential.

Read the full article here: https://issuu.com/mannpublicationsmagazines/docs/fm_june_july_full?fr=sNzA3ZTg2MDI5NTU

7thonline is a leading AI-powered retail planning and forecasting software, enabling more effective planning, demand forecasting and inventory optimization for leading retailers. With embedded business intelligence and rich analytics, the solution offers complete demand visibility and planning capabilities at the most granular level. To learn more about our suite of solutions, book a demo or email us at info@7thonline.com.

In the complex world of supply chains, there’s a metric quietly shaping wholesale success. The fashion industry uses countless KPIs to assess performance: profit margins, cash flow ratios, cost of goods sold and more. But there’s one crucial KPI that’s often overlooked and is quickly becoming one of the most important in a loyalty-focused retail landscape: order fill rate.

Let’s start with the basics. 

Order fill rate isn’t just a measure of operational efficiency. It’s the metric that ultimately determines trust and revenue. It’s a powerful indicator of how well your business understands demand, manages inventory and serves retailers, distributors, franchisees, etc.. But the truth is, a lot of wholesalers don’t even really track order fill rate, let alone harness the power of AI to help solve the problems related to it. 

So, what exactly is the order fill rate?

The order fill rate simply refers to the percentage of retail orders that can be immediately and completely fulfilled using stock that is available to ship; from warehouse to store, it’s the ability to satisfy store distribution orders without delay and in its entirety. A high fill rate means lower lost sales and happy retailers whose orders ship quickly. A low fill rate means stockouts, shipping delays and shaky client relationships. These are problems no brand can afford in today’s competitive market.

This is where AI comes in. AI is revolutionizing how fashion brands manage multi-channel inventory, predict demand and maximize fulfillment without wasting resources.

Improving Order Fill Rates: The New KPI for B2B Wholesale Success

In B2B wholesale, improving your order fill rate is one of the most important measures of success. Why? Because loyalty today is built on reliability. If your business sells to department stores, independent retailers, franchises and ecommerce sites, every order matters as every sales channel matters. When a buyer places an order, whether it’s a big box retailer or a franchisee in another region, you need to ask “Are you able to deliver on time and in full?”

If the answer is no, that lost sale is just the beginning. Unfulfilled orders because of inadequate inventory levels, leads to clients fighting for the same inventory, damaging relationships and margins. Clients notice when their orders get delayed, short-shipped or canceled, and it impacts their trust. Building a strong rapport not only encourages repeat business but could also mean more shelf space for your products—winning higher priority as they expand multi-brand partnerships.  

The reality is simple: clients are happy when you don’t take their inventory away from them. Improving fill rates means efficient multi-channel management—having enough of the right inventory available, keeping every channel and every customer satisfied.

How AI Fits Into Market Week—and Why It Matters More Than Ever

Market Week is one of the most exciting times in the fashion industry, when buyers and wholesalers come together to network and negotiate, preview and place orders for the upcoming season. While exciting, this period is paramount and highly stressful—this series of events set the stage for fashion. Buyers need to plan as accurately and quickly as possible to place orders that account for potential demand in the next six months or so. Brands need to continuously run available-to-sell (ATS) reports and ensure buyers get the products they need.

For wholesalers, this is a high-stakes moment. They commit to producing garments in bulk based on projected orders, carrying the significant financial risk of manufacturing inventory upfront; accuracy is critical for cut-to-forecast processes. Underproducing leads to lower fill rates and lost sales. Overproducing leads to capital tied up in excess inventory and a hidden opportunity cost from products that might’ve been sold but weren’t produced due to budgets.

This is where AI is making a difference. By analyzing past sales patterns, real-time demand signals and cross-channel behavior, AI tools can help brands make smarter production decisions. Instead of relying solely on Excel or limited buyer feedback, brands can better track inventory, forecast with greater accuracy, make dynamic decisions and protect their bottom line.

AI Moves Beyond Forecasting: Smarter Distribution in Real Time

In wholesale, order fill rate measures how effectively a business fulfills client orders against the total demand it receives. A high fill rate reflects a strong ability to meet customer needs and protect retail relationships. While every business would love to hit a perfect 100%, in practice, healthy fill rates typically range between 90% and 95%, with top-performing companies reaching 97% to 99%; 1% of improvement results in millions in additional profit.

Success in wholesale fashion doesn’t have to be reserved for a select few. AI is helping level the playing field, giving even medium sized brands the tools to compete smarter, not just harder.

AI helps businesses move beyond rough forecasting and into real-time planning. Instead of guessing, AI models can continuously monitor order patterns, regional demand shifts and channel performance. Ultimately, AI empowers brands with actionable, real-time inventory optimization, giving them the power to serve every client better, protect their margins and grow more sustainably.

Integrated AI: The Key to Smarter, Seamless Wholesale Operations

Choosing the right AI solution is just as important as using AI in the first place. Efficient multi-channel management requires AI tools that address the needs of each wholesale route as sales channels have their own unique challenges. To see real results, brands need a fully integrated AI system, not just an add-on module. 

An integrated solution doesn’t rely on a team of analysts to interpret data and make manual adjustments. It continuously analyzes, predicts and optimizes behind the scenes, allowing staff to simply adjust and act on clear insights. By contrast, retrofitting AI into an outdated system usually leads to limited improvements and missed opportunities. A true AI-driven platform is built from the ground up, and fine-tunes over time by incorporating industry best practices, designed to connect seamlessly across wholesale operations from planning to forecasting to inventory management, so that every decision is faster, smarter and more aligned with client demand.

At the end of the day, the brands who succeed will be the ones who can deliver what retailers want, when they want it, without compromising relationships or profitability. Managing inventory well has always been a critical part of the business, but today’s market demands a smarter, faster, more precise approach. Order fill rate is a clear reflection of your ability to meet demand and build loyalty across every channel you serve. With the AI right tools in place, wholesale brands can go from surviving to thriving in an increasingly competitive industry.

Read the original article in the AI Journal here.

To learn more about how your team can improve order fill rates, email us at info@7thonline.com or book a demo with our team.