With insight into the fashion, apparel, beauty and retail markets, Corner of Fifth’s StreetTalk Podcast unpacks recent headlines and trends top-of-mind for retailers. Max Ma joins host Arthur Zaczkiewicz to discuss how fashion brands can escape the “dark cycle” of low margins and leverage technology to navigate today’s increasingly complex retail market. 

Some market background —

This year, Cyber Monday landed at the start of December, closing out November with the largest turnout the five-day Thanksgiving weekend has seen. According to the National Retail Federation, an estimated 202+ million U.S. consumers shopped over the long weekend, setting a new record. Defined as a time period spanning November and December, NRF estimates spending upwards of $1 trillion in 2025. Analysis from Adobe reported that while spending was up, inflation and tariffs pushed the volume of goods purchased down, indicating shoppers are being more frugal.

Against the backdrop of the latest, broader retail environment, Max and Arthur drill into the sobering reality of “Excel Hell” and the consequences of having a large tech stack that doesn’t integrate. Many retailers rely on Excel for their retail planning, leading to a fragmented approach to planning, slower decision-making and an increased risk of costly errors. But rather than managing spreadsheets, the right technology empowers them to run their businesses. 

The stakes are even higher as tariffs cut into margins, technology investment, and store renovations. As early inventory buffers are beginning to run out, and tariff costs are expected to fully materialize in 2026, retailers will need to fundamentally rethink their inventory strategies. Max’s perspective is clear: while tariffs are unavoidable, precision in inventory management is not. By moving to a centralized system to conduct planning, brands can eliminate silos and reduce manual errors associated with it—improving efficiencies and productivity to better understand production, supply chain and trending insights. Without the right technology in place, improving net margins becomes nearly impossible. Instead, it creates a dark cycle of costly decisions, low margins, no tech—Max has seen the retail industry stay in this loop for 30+ years.

As NRF 2026 approaches and excitement builds around the latest retail tech innovations, the real challenge lies beyond the conference floor. It’s critical that attendees not only get inspired, but also carry that momentum back into their organizations, and up to senior leadership. Turning excitement into action—and action into sustainable change—will be what separates retailers who survive from those who truly thrive.

Listen to the full podcast here: https://www.youtube.com/watch?v=VxCr8TKu54o 

For more industry insights, check out our blogs or contact the team at info@7thonline.com. 

Discover the secret to demand planning on this episode of the eCommerce Edge Podcast with Jason Greenwood and Max Ma. From data and the rise of AI to complex omnichannel processes, Max and Jason dive into why retailers need to stop treating demand planning like a monthly checklist, and the need to build real-time feedback loops across channels to grow. In an increasingly complex omnichannel world, the right tech can turn planning challenges into strategic strengths. Here’s a quick preview of the conversation:

“It all starts, typically, with a PLM process as a backbone of the product. Once we want to go to production with it, we then have to predict for that initial order (the sizes, colors and variations), and how much on that variation curve we want to produce. Then we have to track momentum, supplier performance of that product, how much we’re going to reorder and how frequently. It’s a complex and disjointed process in many respects. What point does 7thonline come into the supply chain planning process?”

Actually, 7thonline was designed to assist before product design—to analyze who are you designing for, what was sold, who bought your product at what price point, where, etc. We use the data to guide the product design team and determine the future assortment at a very high level. The system helps retailers understand localized demand and forecasts demand to provide production teams with pointed guidance. 

Essentially, we match consumer segmentation to micro demand signals of the products that brands and retailers offer. We’re in the AI age; we use data and analyze your target audience against product characteristics/attributes to bridge the gap between supply and demand from various channels. A lack of structure in product data is often a major challenge. When attribute commonality—such as color, size, style or hem length—is unclear or inconsistent, effective demand planning becomes extremely difficult. Even the most advanced analytics or AI tools cannot deliver meaningful insights without well-structured data.

Establishing strong disciplines around data integrity, data mapping and data validation is the first step we take with every new client. A trusted, well-governed source of master data is critical to enabling accurate analysis and decision-making.

“You see all types of levels of maturity for business, but what size and scale of business typically starts to see benefits from what you do? ”

7thonline is an enterprise software system, designed to support organizations operating at meaningful scale. Most of our customers are larger companies—often with revenues of $100 million or more—because success with a platform like ours requires more than just ambition. It requires the right foundation.

These organizations typically have the infrastructure and data maturity needed to fully leverage enterprise software. Over time, they’ve invested in building reliable systems, establishing governance and, most importantly, treating data as a strategic asset rather than an afterthought. One of the most effective practices we see among these companies is a deliberate focus on master data. Rather than relying on fragile integrations across dozens of disconnected systems, they’ve taken the time to centralize their data. By building and maintaining a unified data warehouse, they create a single source of truth that supports consistency, accuracy and scalability.

This approach doesn’t happen overnight. It’s the result of long-term thinking and disciplined execution. But the payoff is significant: cleaner data, fewer integration challenges and a foundation that allows enterprise platforms like 7thonline to deliver real value. In our experience, companies that prioritize centralized data and strong master data management are far better positioned to turn technology investments into operational and strategic advantages.

“What’s on your radar for the next 6, 12, 18 months, is there anything as you look out into the market of demand planning, inventory management, supply chain management software, that you see and recognize as gaps in the industry?”

High on our priority list is the development of expanded AI capabilities that can capture and scale an expert’s thought process. For years, even many of our most experienced retail customers relied heavily on Excel for demand planning. And to be fair, the industry still loves Excel. But reliance on spreadsheets also creates limitations. Knowledge remains siloed, assumptions are hard to track, and insights live in the heads of a few key individuals rather than being shared across the organization. Our goal is to increase visibility across the board and move beyond static tools toward systems that continuously learn and improve.

One example, we are using AI to determine dynamic classification that is currently human defined—it’s subjective. With AI, it becomes systematic. The result is not just better forecasts, but a more transparent, scalable and resilient planning process that evolves alongside the business.

Listen to the full podcast here: https://www.youtube.com/watch?v=haJknRGYX0Q&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_kc1LahTFMSsgWNYLb16-lcjBCBlMxpG_8LLSJ2Q1snoOfrOcaTJ86kmdcJ-R8ZXZCGKDB 

For more industry insights, check out our blogs or contact the team at info@7thonline.com. 

Max Ma sat down with Mark Lack on Retail Voices, a podcast where leaders from the world of retail talk about what really works: insight, innovation and the human side of the industry. In the episode, the industry veterans break down the real reason retail planning fails and how AI is transforming processes. From dirty data and omnichannel distortion to guardrails and balancing the art and science of merchandising, Max and Mark’s conversation dives into the heart of what makes modern retail operations succeed. Here are a few key insights:

“If you could print one KPI on every planner’s wall, what would it be and what’s the most overrated or underrated forecast signal you’ve ever seen?”

Print this above your computer screen as a daily reminder: increase net margins by 1% every other year. The margin challenge is a depressing reality for the retail industry—low margins restrict budget for new tools, a lack of tools keep retailers guessing and stuck in the same cycle. A percentage boost may not be realistic year over year but striving for that improvement, even in small increments, is still a positive trajectory toward the bottom line. 

The most overrated signal? Macrotrends. Businesses should look at their own data and microtrends to determine what they can conquer first. Once internal efficiencies and data quality are optimized, then retailers can look outward at other elements to improve planning. An underrated signal from planning efficiency is out-of-stock and availability; retailers tend to overlook the negative impact brought on by out-of-stock numbers: how much out-of-stock has caused in losses and the opportunity cost of it all. Nonavailability has been overlooked as consumers (reluctantly) accept the reality of out-of-stock items in favor of convenience—while purchasing the closest alternative isn’t ideal, they make due. But eventually, without the right products in the right place at the right time, customer loyalty falls and they become frustrated.

“Most retailers have really messy data. What do you think should be the first 2-3 steps that any retailer should take before investing in any AI planning tool?”

With retailers implementing many different systems, there are many different versions of data. The first step is to have a master sheet; master data to ensure data integrity and a single version of truth. The second step is to smooth out anomalies—the white noise that shouldn’t be considered in future decisions. Lost sales and out-of-stock needs to be backfilled into your data, and unproductive sales need to be filtered out to set an ideal base for decisions. 

“How do you keep store-level inventory availability honest when online and offline are competing for the same stock?”

7thonline is a unified planning solution, we pride ourselves on empowering an integrated approach that not only takes into account brick-and-mortar and ecommerce but also different distribution channels like wholesale and franchisees. Clients are able to look at the demand signals of all channels on a centralized, unified place to forecast demand more precisely. 

Our system is robust enough to account for different data formats. For instance, wholesale channels won’t display sell-through data, only sell-in data. So how do you forecast? For ecommerce, what about the media buying aspect? We have to consider the “4th dimension” to account for the promotional heavy strategy that influences the retail cube: product, time, location. A robust system can process all of these to provide a more accurate and comprehensive view of demand to precisely forecast based on the needs of individual channels. 

Listen to the full podcast here: https://www.youtube.com/watch?v=1YWmitUxzSc 

For more industry insights, check out our blogs or contact the team at info@7thonline.com. 

Retail is at an inflection point. The reign of the “one-size-fits-all” retail strategy is almost over. After decades of top-down merchandising and uniform planning cycles, consumer expectations and data capabilities have outgrown many planning, inventory and allocation models. 

For too long, the industry has operated with an approach that relies on generalized data, blanket decisions backed by gut-instinct, cumbersome Excel spreadsheets and blind hope that past mistakes won’t repeat. This model isn’t sustainable in a world of hyper-fragmented consumer choices, volatile demand and expensive misallocation. Retailers are experiencing huge markdowns and wasted inventory, but that’s all changing.

The Broken Centralized Approach

The conventional retail buying cycle is fundamentally broken. Oftentimes, the exact bulky winter coats offered in blizzard-expecting Boston are available in sunny Los Angeles. This is the industry’s most critical blind spot. 

Old school reporting tools can show you big picture trends, but they often miss regional patterns. While algorithms and AI models are setting a new standard for data accuracy, the real success in fashion merchandising comes from combining creativity and industry expertise with nuanced AI insights. When retailers understand local markets and customers, they are able to anticipate trends, adjust and connect with shoppers wherever they are. AI enhances this art by analyzing data at scale and providing performance-based recommendations tailored to each SKU, store and channel.

Shifting Away from a One-Size-Fits All Approach with AI Precision at Scale

Artificial intelligence is reshaping retail by enabling a level of precision and personalization that was previously unattainable with purely manual efforts. By analyzing a wide range of real-time internal and external signals from performance metrics and weather, AI is enabling retailers to operate more like thousands of micro-businesses—scaling precision. This level of insight enables retailers to anticipate shifts in customer behavior at a micro level, empowering planners to fine tune their strategies to reflect the specific preferences, behaviors and seasonal trends of local consumers. 

By leveraging real-time data and predictive analytics, retailers can shift from broad strategies to highly targeted, demand-driven operations that optimize turnover, minimize markdowns and protect profit margins. This tailored strategy ensures that retailers are responding effectively to specific consumer demand and each market’s unique trends and seasonality with dynamic open-to-buy budgets and agile allocation strategies. Shift from static forecasting models to adaptive approaches that ensure relevance—the future of retail inventory management lies in precision mixed with human instinct.

The Art and Science: Turning AI Insight into Localized Assortment

As retailers plan for 2026, the focus isn’t simply on managing inventory through a more targeted and accurate assortment—the technology exists to provide the precision needed to match products to demand at the store level. The impact is measurable. 

Real success isn’t about replacing the human planner’s creative instinct, because it’s that intangible that creates success, creativity and an exciting shopping experience. Better results come from enhancing that expertise with data. AI manages the complexity, giving planners and regional managers prescriptive, actionable insights. The data tells them what they should do next. Merchandisers, the experts who hold the brand’s DNA and deeply understand their community, apply their intuition to fine-tune assortments, ensuring they connect not just with a data profile, but with the specific needs of the local shopper.

Embracing the Data-Focused Future

As 2025 comes to a close, there’s a unique opportunity to move from a generic, centralized strategy to an efficient, demand-driven and data-focused way of working. This new strategy thrives by managing complexity at scale, seamlessly combining algorithmic speed with the nuanced interpretation of human planners.

Retailers need to stop viewing technology as a niche project for the IT team. It is now the essential tool for operational efficiency and survival in a volatile market. The future belongs to those who embrace the market’s complexity and manage their entire enterprise as a finely tuned network of thousands of responsive, demand-centric micro-businesses. It’s time to invest in the next generation of AI planning tools. That’s how we ensure every decision is made intelligently and profitably.

Find the full article in Fashion Mannuscript here: https://issuu.com/mannpublicationsmagazines/docs/fm_november_december_full/77

Talk to the team to find out how you can join the end of “one-size-fits-all” retail at info@7thonline.com or book a demo.

Every year, consumers are starting their seasonal shopping earlier—from back-to-school and summer-vacation prep to Halloween costumes and Holiday gifting. Each of these moments affect the retail calendar, requiring early demand forecasting, strategic inventory planning, promotional alignment and channel-specific strategies. To keep pace with the shift, retailers must respond by reworking their retail calendar, moving planning and execution cycles forward to capture demand before the peak seasons even begin.

The Early Shopping Trend Requires Agile, Early-Stage Planning

When shoppers start early, so should you. 

To stay competitive and meet customer expectations, brands must adopt intelligent, proactive planning processes that anticipate demand well in advance. Early shopping trends require synchronized, end-to-end planning that spans product development, supply chain and merchandising. 

According to the National Retail Federation’s 2025 survey, 67% of back‑to‑school shoppers had already started buying before early July—up from 55% last year. This early-shopping trend extends beyond back-to-school. NRF also revealed 49% of consumers prep for spooky season before October, versus just 34% a decade ago. Retailers who plan early are better positioned to reduce stockouts, avoid excess inventory and deliver a seamless customer experience during high-demand periods.

AI-driven platforms enable businesses to forecast earlier and with greater accuracy by analyzing emerging trends, historical data and real-time market signals. This ensures inventory is not only available but also optimized across all channels—before peak shopping begins.

What the New Retail Calendar Means for Retail

One major reason shoppers are shopping early? Cost.

“For consumers looking to balance their budgets, strategies such as buying early to spread out purchases or shopping at discount stores are just some ways they are being mindful of costs,” Prosper Executive Vice President of Strategy Phil Rist said.

Between tariffs, inflation, job market volatility, etc. shoppers are now more conscious than ever about pricing. But how should retailers adapt to the new retail calendar?

• Stretch the calendar: Traditional start dates for “seasonal moments” are giving way to multi‑week or even multi‑month promotional windows. Retailers are stretching their retail calendar to start buying seasons earlier. 
• Inventory planning matters more than ever: If your products arrive too late, you lose the early shopper. If they arrive too early without demand, they take up costly space.
• Tiered promotions: Campaigns, social media, email and visual merchandising need to launch earlier to match consumer intent. The first wave of early shoppers may respond to “pre‑season” offers or loyalty exclusives. Later shoppers may need deeper discounts. Retail calendars must allow for layered offers.
• Flexibility and agility: Because consumers are spread out in their timing, retail calendars must allow for responsiveness—quick pivots, flash deals and real‑time data adjustments.

Both shoppers and retailers are now guided by a more fluid retail calendar, shaped by consumer anxieties, desire to avoid last-minute stress and the eagerness to lock in deals. For brands that get ahead of that calendar—to serve both early planners and late deciders—the opportunity is richer than ever.

In today’s rapidly shifting retail landscape, success hinges on the ability to anticipate and act—not just react. As consumers continue to shop earlier for key seasonal moments, retailers must embrace a proactive approach to planning that is rooted in precision, agility, and data-driven insights. Those who start early, align their strategies across channels, and optimize inventory and promotions ahead of the curve will be best positioned to meet customer expectations and drive growth. The retail calendar has changed—now is the time to change with it.

To learn more about how AI can help you plan earlier and with more accuracy, email us at info@7thonline.com or book a demo.