Connect supply chain planning and execution across channels. 7thonline has been empowering multi-channel retail brands to make integrated inventory decisions that impact their bottom line. By acting on new opportunities that improve inventory productivity, retail brands are able to see ROI through improved order fill rate, additional margins from higher full-priced sell-through, reduced markdowns and more.
For over 25 years, 7thonline has revolutionized the demand planning process with frictionless multi-channel solutions and custom, AI-powered functionality for every point of sale.
Stay ahead in today’s complex retail landscape and seamlessly meet shoppers, anytime, anywhere. The 7thonline team conducted a concept study* based on various metrics such as revenue and gross profit margin, to show the impact of our platform for various brands. The concept study includes aggressive, likely and conservative scenarios to calculate the return on investment for ourmulti-channel and corporate demand planning solutions.
Using 7thonline’s demand forecasting and consumer-centric selling tactics, we ran the numbers for a conservative ROI analysis of a multi-channel brand generating $2B annual revenue:
The detailed analysis projects an additional $23.9M in revenue due to increased margins across wholesale and direct-to-consumer channels in the first year.
Using AI for operational efficiency saved the brand around $6.5M in SG&A (Selling, General and Administrative) and inventory carrying costs for the first year.
The annual net benefit of the platform jumps from $25.1M in year one to $34.1M in year two as the system refines its recommendations to maximize merchandising decisions.
Our AI-native platform leverages proprietary, vertical-specific algorithms and industry best practices to deliver value acrosswholesale,DTC andecommerce channels—no matter the brand’s size. As businesses grow, our system scales seamlessly and unlocks greater potential, maximizing returns for multi-channel brands.
*7thonline’s ROI model was developed by Kurt Salmon, part of Accenture Strategy, based on an independent study of 7thonline’s clients to serve as a benchmark for investment evaluation for retail executives.
To learn more about 7thonline’s AI-powered multi-channel and corporate demand planning solutions, email us at info@7thonline.com orbook a demo with the team.
In the retail industry, AI is now powering decisions once driven solely by instinct.Research Gate recently reported that AI-based assortment planning has helped some retailers cut SKUs by 22% while increasing sales by 15%. Through predictive AI, machine learning and real-time data processing, retailers are able to forecast demand with unprecedented accuracy, optimize product assortments and respond instantly to real-time market signals—managing inventory with surgical precision and growing sales by anticipating customer demand at scale.
The Power of AI, Turning Data Into Intelligence
AI’s ability to synthesize vast, multi-source data in real time to generate granular, predictive insights exceeds human capacity, transforming how decisions are made across complex environments and millions of data points.
Going beyond traditional number-crunching, AI-powered retail planning systems act as the engine behind data-driven merchandising strategies. They continuously synthesize inputs from sales history, online browsing patterns, social media sentiment and regional buying behaviors, creating hyper-granular recommendations tailored to every SKU, store and channel. These systems report what’s happening and predict what’s likely to happen next, enabling planners to adjust and optimize in real time, matching localized demand and responding to sudden market opportunities or disruptions.
When this analytical precision is paired with the nuanced judgment of experienced merchandisers, the powerful synergy ensures that strategy is both analytically sound and emotionally resonant, aligning commercial performance with authentic brand storytelling. AI optimizes retail operations and elevates them. At 7thonline, the philosophy has always been clear: AI is a force multiplier for human expertise, not a replacement for it. We build AI to deliver the art of merchandising at scale.
The Human + AI Model: Retail’s Competitive Edge
AI’s unmatched accuracy and speed give retailers a powerful decision-making engine, realized in lockstep with seasoned merchandising instinct. AI can identify the most statistically profitable product mix, but it takes human insight to interpret those findings through the lens of brand vision, trend trajectory and customer psychology. Together, they create a merchandising approach that is not only faster and more accurate, but also deeply attuned to the creative and emotional cues that drive fashion purchasing. From demandforecasting to in-season adjustments, AI is turning vast streams of raw data into actionable intelligence that directly improves both profitability and customer experience.
Algorithms excel at detecting patterns in customer behavior and past performance; human judgment applies brand DNA, storytelling and creative intuition to curate assortments that connect with shoppers on a deeper level. The planner who detects the start of a microtrend, the designer who senses a shift in aesthetic and the strategist who understands the subtleties of local customer behavior provide the interpretive lens that gives AI insights their commercial and emotional impact.
In fashion merchandising, this blend of science and art is critical. Many merchandisers have honed their craft over decades, learning how to anticipate what shoppers will want before they know it themselves. This involves not just picking the right styles, colors and sizes, but timing them perfectly for the market and presenting them in ways that evoke desire; processes that would have taken an insurmountable amount of time are now instantaneous. By embedding AI into this process, retailers ensure that the brand’s vision is brought to life with precision while creating assortments that resonate not only with a demographic profile, but with the communities they serve.
In practice, this human-AI partnership doesn’t follow a single formula. It adapts to each retailer’s goals, product categories and market dynamics. The most effective applications are those where AI’s scale and speed are paired with the merchandiser’s ability to recognize nuance and context that algorithms can’t fully capture.
Retail Data Science: Blending AI Precision with Merchandising Intuition
The balance between human expertise and AI intelligence is most visible in three critical areas: assortment planning, dynamic replenishment and trend forecasting. Each demonstrates how technology and creativity converge to deliver sharper, more profitable decisions.
Assortment Planning
AI-powered assortment tools analyze SKU performance, customer demographics and emerging trend signals to recommend the most profitable product mix for each store or channel. Merchandisers then refine these recommendations, filtering them through brand identity and their understanding of customer sentiment to ensure the selection aligns with both commercial goals and the brand’s creative vision.
Dynamic Replenishment
Predictive analytics and real-time sales monitoring allow retailers to make replenishment decisions based on precise demand forecasts. Merchandisers add value by incorporating context outside of historical data including sudden weather shifts, influencer-driven demand spikes or marketing campaigns, making allocation decisions that respond to both the numbers and the moment.
Trend Forecasting
AI scans massive volumes of data from social media, search trends and global sales to detect early signals of what’s gaining traction. Merchandisers interpret these patterns through the brand’s unique perspective, deciding which trends to lean into, adapt or pass on entirely, ensuring that what makes it to market is both timely and authentic.
Across each of these use cases, AI delivers the analytical horsepower, and human expertise ensures those insights are translated into actions that not only improve margins but also strengthen the emotional connection between brand and customer.
AI is a necessity in its ability to derive detailed, data-rich insights at both scale and depth that is fundamentally transforming how decisions are made. What once relied on gut instinct and reactive planning is now informed by predictive models, volumes of real-time data and adaptive machine learning algorithms that uncover patterns invisible to the human eye; AI enables retailers to operate with a level of precision, speed and contextual awareness that was previously unattainable.
As retail continues to evolve, those who embrace this human-plus-AI model will unlock a new era of intelligence-driven merchandising—where data doesn’t just inform decisions, it transforms possibilities.
We surveyed 100+ retail leaders to uncover how they are navigating today’s retail landscape—exploring tight wallets, higher tariffs, supply chain responsiveness and the role of technology in the center of it all.
In the heart of Manhattan’s Garment District—where fabric swatches rustle and buyers negotiate by the minute—a scrappy startup emerged on 7th Avenue at the turn of the millennium. In 1999, Max Ma, a software engineer at a fashion CAD company, started 7thonline after realizing that the industry needed more effective ways to boost inventory productivity. With only 40% of inventory contributing to a brand’s overall profit, he started 7thonline with a mission: break the cycle of low margins, limited resources and sub-optimal decision-making.
Named after the street that inspired its ideation, the platform was designed to directly impact the needs for apparel, footwear and accessories retailers with advanced technology—AI and machine learning models. Developed by a team of data scientists and retail experts with a shared mission, the industry soon started hailing them as “the science guys”.
Our Mission: Inefficiencies Bleeding Time and Money
“It was surprising to see multi-billion dollar companies with completely manual processes. I (specifically) saw an opportunity to use artificial intelligence to improve the inventory decision-making process. Ultimately, we believe that AI will improve quality of life as there is a more efficient use of time, better results and cost efficiencies.” – Max Ma
He sought to arm them with logic and algorithms, an approach that felt like pure science: data-driven, methodical, deeply analytical. Despite major strides in retail technology, Max points out a surprising truth: 70-80% of retailers still depend on Excel for critical, million-dollar inventory decisions. “It creates silos, errors and a total lack of control,” Max explains. “Our goal was toreplace Excel—without intimidating the user.”
The Science Guys of Retail, Gaining Momentum
“The science guys of retail” became a quiet badge of honor—an affectionate nod to a team focused on fusingretail and data, engineering and intuition—symbolizing the AI expertise built into the platform. The nickname showcased our team’s love for data and a knack for fashion, and the platform’s ability to crunch the numbers behind every SKU, season. and shelf—making sure assortments are stylish, smart and balanced.
The first prototype of 7thonline was a collaborative planning and buying platform hand-coded by Max. It quickly captured the attention of the retail industry, even securing an invite to the Department Store Consortium’s competition against two publicly-traded companies that facilitate buyer/seller collaboration. Against all odds, 7thonline won the competition as was chosen for the pilot. Following this defining victory, awareness picked up—signing their first big client, Liz Claiborne and other major brands such as Jones Apparel Group and Kellwood. Combined, these conglomerates accounted for over 50% of total US department store’s women’ s merchandise.
Although Max claims this was a ‘surreal experience’, he knew the value of his platform—massive savings and higher profit margins. In the next few years Max ensured that profits were reinvested in product development, solving increasingly complex scenarios that directly impacted the industry. Cultivating the product, focusing only on retail, gave the platform an unmatched depth backed by retail-specific AI models and best practices. Eventually, the company went on to sign additional brands such as Canada Goose, Patagonia, Michael Kors, Calvin Klein and more.
Nowa leading provider of inventory management and demand planning solutions for the retail industry, 7thonline is serving brands with end-to-end planning capabilities. To learn more about the platform, book a demo or email us at info@7thonline.com.
A leader in multi-channel inventory management and retail planning solutions, 7thonline has been empowering retailers to drive ROI across channels for 25+ years. With artificial intelligence and machine learning embedded into the core of the platform, 7thonline enables data-backed, integrated decisions that directly impact the bottom line:smarter allocation and replenishment tominimize markdowns and lost sales,reduced overproduction and excess inventory, dynamic in-season decisions and more.
Based on various metrics such as revenue and gross profit margin, our team is able to conduct concept studies to show the impact of our platform for various brands; the concept study includes aggressive, likely and conservative scenarios to calculate the return on investment for our direct-to-consumer and wholesale solutions. 7thonline’s ROI model was developed by Kurt Salmon, part of Accenture Strategy, based on an independent study of 7thonline’s clients to serve as a benchmark for investment evaluation for retail executives.
For brands withdirect to consumer channels, acting on new opportunities that improve inventory productivity amplifies ROI through proactive OTB decisions, maximizing full-price sell-through based on an item’s highest propensity to sell and smarter allocation/replenishment driven by localized demand. Using 7thonline’s demand forecasting and consumer-centric selling tactics for DTC operations, we ran the following numbers for a detailed ROI analysis.
According to the ROI analysis, a brand with an estimated $1.5B annual revenue is projected to see the following:
Over five years, the additional revenue realized could be up to $56.5 million (aggressively) due to more accurate demand forecasting and consumer-centric merchandising.
Conservatively, the brand is slated to see an additional $8 million in profit margin due to improved full-price sell-through rates set by localization, in the first year with a 6X ROI.
Using AI for operational efficiency saved the brand nearly $4 million in inventory carrying costs for just the first year in the conservative analysis.
For a $500M brand, we ran a conservative ROI analysis of using 7thonline’s DTC solutions to find the following:
By decreasing markdowns and minimizing lost sales through smarter allocation, the brand can (conservatively) expect $3.8 million in additional revenue within the first year.
Conservatively, the analysis projects a 242% ROI in the first year due to an increase in revenue and decrease in SG&A and inventory carry costs—valued at a net benefit of $2.8 million.
In year five, the brand has reached over 18X on ROI, with a cumulative benefit of $26.3M, while the annual net benefit has nearly tripled from year one.
Our AI-native system utilizes proprietary vertical-specific models and industry best practices to drive value for all brands and retailers acrosswholesale, DTC andecommerce channels regardless of size. As brands continue to grow, our platform not only scales to their business needs but also realizes more potential, boosting returns for multi-channel brands.
As demand from wholesale accounts and major retailers continues to fluctuate, maintaining a flexible and responsive supply chain becomes essential. Develop a comprehensive understanding of demand across divisions, accounts and geo-locales to simplify wholesale planning and forecasting, guide product development and empower proactive selling— ultimately promoting a responsive supply chain that improves customer satisfaction and increases order fill rate.
AI-powered unified planning solutions empower retailers to make informed decisions through actionable insights, aggregated data and accurate forecasts derived from real-time data at scale.
AI is a tool, not a replacement. For the merchandising world, it is a science meant to enhance the art of brand vision and retail expertise. AI enables speed, scale and structure but it’s the human element that brings meaning to those insights. It’s the planner, the designer, the strategist who recognizes emerging trends—who considers vision, context and creativity. So let’s reframe the conversation: AI doesn’t replace planners. It enables them. The future belongs to those who are ready to use it.
Mastering the Art of Retail Merchandising: Where Strategy Meets Storytelling
Merchandising is more thanproduct placement, it’s the art of telling a story that converts browsers into buyers and buyers into believers. It’s how brands connect with customers, influence decisions and ultimately drive revenue.
Knowing what products your customers want (even before they do) is an art form; it’s about instinct and insight—a skill refined over time much like mastering color theory. Placing the finishing touches to a masterpiece, having the right style, color,size in the right place at the right time is akin to shading and highlighting. It’s the strategic positioning of products, the timing of launches, the use of color and texture to bring the big picture to life.
Merchandising isn’t just about moving products. It’s about crafting experiences. And like all great art, it’s both intentional and intuitive.
Automating the Science with an AI-Powered Merchandising System
The science behind merchandising is thedata-backed analysis that guides decisions and provides details around your latest sales trends—all to say: Where’s the demand?
Is butter yellow still the color of the summer?How is ozempic impacting size profiles? Are skinny jeans back (with a vengeance)? What’s the lore around the latest -core: mermaidcore, balletcore, cottagecore?
AI comes in to enhance the art by analyzing data at scale, at a granular level, and improving operational efficiencies through automation.
With an AI-powered system catering to merchandising challenges, retailers are able to streamline data analysis, improve forecasting accuracy, minimize inventory risk and sharpen planning processes. AI systems digest massive amounts of data quickly and surface insights for an educated decision; it becomes a force multiplier for merchandising teams to make decisions that align with consumer preferences anddrive profitability.
Retail Reimagined: Balancing Passion and Precision
The real power comes when AI and people work together. At its core, merchandising blends creativity with data. People provide intuition, direction and inspiration. AI aligns teams, breaks down patterns and identifies opportunities/risks.
A demand-led, data-backed approach enables businesses to stay agile, plan with confidence and protect their margins. With AI-poweredretail planning software, retailers can seamlessly balance analytics with merchant intuition to deliver the right product mix—down to style, color, size.
To learn more about how your team can use AI to enhance the art of merchandising, email us at info@7thonline.com or book a demo with our team.
It’s no secret that artificial intelligence has changed the world, but the full power of what this technology can do has yet to be discovered—especially in the retail space. Many retail tech solutions are serving the industry with AI-powered demand forecasting and personalization capabilities, but true impact and ROI comes from embedding AI throughout the merchandising cycle, across channels.
According toNVIDIA’s report on the State of AI in Retail and CPG in 2025, 42% of retail firms are actively using AI in their operations, while 47% are still in the assessment phase. However, only a little over half of those using the technology are using it for more than six use cases stretching across their operations.
For retailers that aren’t using AI across their workflow, forecasting tends to be the one place where they are using it. Arecent 7thonline survey of 100+ retail executives revealed that 33% of leaders are currently using AI to analyze data and forecast demand. Of course, forecasting is a critical piece of the retail puzzle, especially as demand fluctuates and expectations rise, but it’s not the only piece. AI should also be embedded in inventory management, supply chain management, merchandising and planning, in-season open-to-buy, sentiment analysis and more.
Why AI Is Needed in Every Part of Multi-Channel Processes
While AI has many benefits, the true value of AI in retail comes from its ability to boost profitability and preserve margins through proactive, data-driven decisions. NVIDIA reported four out of five retailers using AI claim it has boosted their annual revenue, with 25% stating revenue increased by more than 20%. Success isn’t achieved by simply adding AI to a tool and hoping for results, it’s achieved by embedding it into every stage of the retail workflow.
Retailers using AI for forecasting have seen impactful benefits, but without end-to-end integration, its full potential remains untapped; forecasting is only the first step to AI adoption in retail. 7thonline’s latest survey revealed that while only 16% of those utilizing AI are using it for demand forecasting, 34% of retail leaders expect AI to play a major role in sustaining or growing profits within the next two years.
Here Are Some Ways to Embed AI into Different Steps of the Retail Process
AI for Supply Chain Management –
AI helps retailers navigate the complexities of global trade in response to tariffs, sanctions and other disruptions affecting various parts of the supply chain to better align production decisions and shopper demand. Utilizing AI-driven insights, such as “what if” scenarios, retailers are able to determine what might happen if they need to switch suppliers or where they get their products from.
AI Solutions in Inventory Management –
Pre and in-season inventory management is one of the most common AI use cases in retail, according to NVIDIA; retailers can stay ahead of the game with decisions that maximize inventory productivity and enhance customer satisfaction. Using AI, they can create detailed item-level plans across channels, make dynamic open-to-buy decisions and allocate based on localized demand for each store. Utilizing AI and real-time sales data, retailers are able to determine each item’s propensity to sell at different locations and predict when products will sell out during the season—enabling proactive reorder decisions to maintain the right assortment mix down to style, color, size. Deep demand insights empower data-driven decisions based on the latest selling trends, such as when to replenish stock, reorder best sellers or develop a promotional plan for slow-moving items.
AI-Powered Demand Planning –
AI improves demand forecasting accuracy and identifies risks and opportunities with robust visibility into what resonates with consumers, reducing inventory risk and driving strategic growth. NVIDIA revealed analytics and insights into areas like sentiment are a common use case for AI in retail—helping retailers understand consumer behavior based on all customer affinities: product, time, location and media consumption. AI can crawl for customer reviews and social media posts to uncover product sentiment and marketing contribution margins, enabling retailers to adjust their merchandising and promotional strategies. By analyzing the performance of past products, AI can also make predictions about how well new styles might sell based on the demand of previous products with similar attributes for smart expansions into new markets and product categories.
Making the Most of AI in Retail
Many retailers who have dipped their proverbial toe into the water of AI have only scratched the surface of what it can do; until retailers embed AI into every step of their operational workflow, they won’t be able to reap the full benefits. With AI embedded into every aspect of their multi-channel processes, that’s when their business will truly soar.
Before you know it, the biggest time of year for retail will be here: Black Friday/Cyber Monday, aka holiday shopping. But between tariff policies, tight wallets and teetering loyalty, retailers this year will have to navigate more than just bold discounts and eye-catching campaigns to boost holiday sales—they need reliable multi-channel demand planning strategies. Brands planning smarter will prevail, and combining AI and brand identity will be key.
Brand Loyalty vs. Bargain Hunting: What Wins Over Today’s Shoppers
According to the Wunderkind 2025 Tariffs Consumer Impact survey, 76% of Americans say they’re willing to switch brands for better prices—consumers are leaving loyalty behind for a 10-20% deal. This cost-conscious generation of shoppers puts concerned retailers in a sticky situation as prices increase and purchasing power diminishes with tariff policies, especially the66% majority that cannot afford to absorb the extra import costs.
June saw the first tariff-induced price hikes with goods seeing the highest cost increases in the past five months, with theConsumer Price Index increasing by 0.3%.
“Inflation has begun to show the first signs of tariff pass-through. While services inflation continues to moderate, the acceleration in tariff-exposed goods in June is likely the first of greater price pressures to come. The Fed will want to hold steady as it awaits more data.” – Ellen Zentner, Chief Economic Strategist at Morgan Stanley Wealth Management
Between wavering brand loyalty and declining purchasing power, retailers are having torethink demand for the holiday season.
Enhance Retail Holiday Planning Ahead of the Frenzy
Get ahead of the Black Friday/Cyber Monday frenzy with thoughtful planning.
Holiday demand can be unpredictable, and withongoing supply chain challenges, even top retailers can fall short with their inventory management—but the era of shopping showdowns is over. Gain a competitive edge with thoughtful planning andsmart allocation that minimize inventory risk.
For apparel and fashion brands, it’s not just about having enough product—it’s about having the right product,in the rightsizes, at the right locations. Smart allocation is critical. Thoughtful planning is non-negotiable.
A misstep can lead to missed sales, frustrated customers and excess inventory where it’s not needed. This season, precision in distribution andmindful assortment planning aren’t just a nice-to-have—it’s necessary to meet shopper expectations andpreserve your tariff-burdened margins. That’s where AI-powered solutions come in.
Multi-Channel Demand Planning: Combining AI and Brand Identity
The uncertainty and continuously-changing conditions of today’s retail landscape are changing the way people are buying, especially for the holidays. With AI-poweredretail planning software informing inventory decisions, retailers can seamlessly blend detailed analytics with merchant intuition and creativity to meet shopper expectations and demands—down to style, color, size.
Combining brand identity with AI enables retailers to deliver a more personalized and consistent shopping experience that aligns with customer expectations. By leveraging AI to analyze customer behavior, preferences and purchase history, brands can produce and stock products that reflect the brand’s aesthetic and align with their target audience. This fusion ensures that every interaction—whether online or in-store—feels authentic and tailored, reinforcing brand loyalty while increasing conversion through smarter, more intuitive product offerings across channels.
To learn more about how AI can help brands and retailers stay ahead of consumers during the busiest time of year in retail,book a demo or email us at info@7thonline.com.
In today’s fast-changing retail landscape, precision and agility are more critical than ever. Max Ma, CEO and founder of 7thonline, sat with CityBIZ for a Q & A. Max shares how his vision for data-driven, SKU-level planning is helping brands move beyond outdated forecasting models to fully integrated, AI-powered merchandising strategies. From founding insights to 7thonline’s strategy, this conversation sheds light on what it takes to thrive in modern retail.
What inspired you to establish 7thonline in 1999, and how has the company’s mission evolved since its inception?
I started working in retail as a software engineer, and quickly realized that the industry needed more effective ways to boost inventory productivity. It was surprising to see multi-billion dollar companies with completely manual processes. I (specifically) saw an opportunity to use artificial intelligence to improve the inventory decision-making process. We embraced the challenge; breaking the cycle of low margins, limited resources and sub-optimal decision-making. Ultimately, we believe that AI will improve quality of life as there is a more efficient use of time, better results and cost efficiencies.
We’ve been developing our AI solutions for 25+ years through continuous R&D and client collaboration to specifically address industry needs. Early on, we introduced AI tools for wholesale buying and planning, partnering with major wholesalers like Liz Claiborne, Jones Apparel Group and Kellwood. Over time, we added a whole suite of demand planning capabilities to addressdirect-to-consumer retail needs, servicing brands with both DTC and wholesale channels toalign supply and consumer demand, increase margins and reduce excess stock.
Today, 7thonline remains committed to helping the retail industry, which still relies heavily onExcel, by offering AI capabilities that enhanceprofitability and elevate inventory productivity. We’re always developing new functionality, expanding our algorithms and utilizing advanced AI and machine learning to help streamline retail and wholesale processes.
7thonline leverages advanced analytics, machine learning and AI to enhance retail merchandising strategy. Could you elaborate on how these technologies enhance demand planning and inventory management for your clients?
Using cutting-edge technology such as advanced analytics, machine learning and AI, we’re enabling retailers to better understand their customers and meet their expectations—from analyzing demand drivers to adaptive forecasting, the system considers all consumer affinities for the most accurate forecasts. Our system architecture is based on various AI methodology, and has laid a powerful foundation to support retailers in their planning and inventory management needs. Withthe latest LLM capabilities, we are taking the platform to the next level.
These technologies enhance demand planning and inventory management by analyzing data such as historical sales—down to style, size, color and store per week—to predict demand and inform decisions; by being demand-driven, retailers can make inventory decisions based on a product’s propensity to sell. With increasedtariffs, making the right inventory decisions is even more critical—the “wrong” decisions become more costly. By only importing goods necessary to fulfill demand, retailers can avoid the costs associated with excess inventory and preserve their margins. AI simply makes this process much easier.
The retail sector faces challenges like seasonal demand fluctuations and supply chain disruptions. How does 7thonline’s platform address these issues to support retailers effectively?
We understand that the retail industry is primarily focused on short lifecycle and seasonal products, and have taken the related challenges into consideration when building our AI-native platform. Using industry-specific algorithms to address industry-specific needs, our system helps retailers dynamically adjust their inventory strategies to shifting consumer demand.
For example, forecasting demand is hard, but forecasting demand for new seasonal items without a sales history is borderline impossible. 7thonline’s AI-based platform is able to address this gap in information by analyzing data from similar styles and their performance, to predict their future sales based on trends and granular insights. Because of the sheer volume of data—down to style, color, size, store location and weekly sales—this is extremely difficult without artificial intelligence. The system leverages a wide range of data sources such as POS data, shipment data, logistic and warehouse data and marketing data to analyze the demand signal from every single channel of distribution.
Your solutions have been adopted by notable brands such as PVH, Patagonia, and Canada Goose. Can you share a success story that highlights the tangible benefits a client experienced after implementing 7thonline’s solutions?
7thonline has been servicing the retail industry for over 25 years; we’ve had clients stay with us for decades because of the firsthand benefits they experience using the system.
For example, a multi-billion dollar wholesale client was dealing with growing supply chain costs and sought to improve its operational efficiency and production accuracy across 11 global brands. By using our AI-powered account planning system, they were able to expedite their production buy orders one week earlier than their competitors, resulting in a $1/garment cost reduction.
For another client, a major retailer operating 8,000+ stores, allocation was their main concern—they wanted to improve allocation productivity and reduce operational costs from imprecise allocation and replenishment processes. Using the AI-powered forecasting capabilities, they were able to improve inventory accuracy from 60% to 92%, efficiently aligning stock to consumer demand and reducing the reallocation efforts.
Want to learn more about what 7thonline could unlock for your brand? Let’s run a concept study to determine yourROI. Email us at info@7thonline.com.
As the retail industry continues to evolve, what trends do you foresee, and how is 7thonline positioning itself to meet the future needs of retailers?
Throughout the years, we’ve been fortunate to partner with leading global brands and retailers to conceptualize and develop new functionality that enhances our solutions based on industry needs. We’re constantly collaborating with clients to develop new tools that improve retail processes and inventory decisions as the industry’s needs evolve.
Recently, we’re seeing more and more retailers place an importance on data analytics and efficiency. The biggest tech trend: artificial intelligence. While brands are always searching for innovative tech, AI is what’s on everyone’s radar right now; we think that more brands will continue to adopt AI in order to stay competitive in a saturated market. We’re particularly excited by the AI boom as artificial intelligence is embedded into the core of our system, providing us with a new frontier to collaborate with innovative brands looking to adopt AI capabilities—we’ve been doing AI for the past 25+ years.
