JIMMY JAZZ

Planning Intelligence Helps Jimmy Jazz Increase Full-Price Sales

Business Challenges

Jimmy Jazz struggled with low product planning accuracy and limited demand forecasting capabilities for various regions and stores, resulting in missed sales opportunities and high markdowns. With a backlog of inventory and limited cash flow, they sought a solution to help them predict trending products and improve full-price sell-through of products. 

Solution

Through smart recommendations by the system’s sales forecasting capabilities, Jimmy Jazz was able to increase sales revenue and profit margins by improving the accuracy of product planning. The enhanced predictive ability helped the team improve assortment planning and revamped their inventory structure to reduce product markdowns. The new structure addressed their backlog challenge and enabled their team to free up enough capital to support the company’s expansion strategy. 

Company Profile

A premiere destination for leisure and sports footwear and apparel in the United States, Jimmy Jazz (a SNIPES company) is an authorized retailer for 74+ brands, including Nike, Adidas, Puma, FILA, etc. A well-known streetwear retailer, Jimmy Jazz operates nearly 170 stores in the United States. 

Patagonia

AI and Machine Learning Help Patagonia’s Global Business Multiply

Business Challenges

On a mission to reduce waste, Patagonia set out to improve their sales demand forecasting and allocation strategy to minimize overstocking and overproduction. The brand struggled with long sales cycles for some products, making assortment planning and inventory management difficult. While the brand is known for their industry-leading level of forecasting accuracy, they sought a technological solution to help them achieve a higher degree of consistency to positively impact financial plans and sales plans.

Solution

By integrating real-time data throughout their processes and fostering collaboration amongst departments, Patagonia was able to ensure order volume and shipment quantities aligned with company plans; AI models and machine learning capabilities recommend the quantity of goods to be allocated down to style, color, size. 7thonline’s platform empowered their teams to manage product plans across quarters and fiscal years by addressing concerns derived from long product lifecycles, and helped them focus on developing sophisticated product plans and supply chain management strategies.

Company Profile

Patagonia is an environmentally-conscious company specializing in outdoor sports equipment and apparel. A designer of outdoor clothing and gear for the silent sports, the company operates globally with over 100 stores worldwide and factories in 16 countries.

Calvin Klein

Multi-Channel Management Helps Calvin Klein Make Precise Business Decisions

 

Business Challenges

With a large global presence, diverse product range and heavy datasets, information processing is timely and complex. Calvin Klein struggled with high resource costs and inventory mismanagement for all channels—brick-and-mortar, ecommerce, wholesale distributors, etc—resulting from redundant and disjointed business practices between various functions and brand departments. They sought to unify business processes and improve their sales forecasting around product categories to make precise inventory decisions down to style, color, size. 

Solution

Using 7thonline, Calvin Klein was able to improve work efficiencies by obtaining complete order information spanning all regions. With real-time data and cross-department collaboration, their product planning, sales and product teams were able to enhance their workflow and standardize merchandise planning operations—closing the loop with a centralized planning system that fosters collaboration and strengthen communication.

The platform also simplifies data analysis from multi-dimensional data inputs to derive high-value insights and inform merchandising decisions; 7thonline’s localized size profiling feature even addressed their challenge forecasting sales down to style, color, size due to diverse size parameters for different categories, resulting in more precise inventory decisions for their numerous stores around the world. 

Company Profile

One of America’s largest brands, Calvin Klein sells products in over 20,000 stores worldwide across their four main sub-brands: CK Calvin Klein (premium ready-to-wear), Calvin Klein Jeans (denim), Calvin Klein Underwear (intimates) and Calvin Klein Performance (sportswear). With a legendary legacy, large physical global presence and diverse product range, Calvin Klein has a strong history in the apparel industry.

Reinventing Retail Tech—How 7thonline is Optimizing Merchandising with AI

7thonline Founder and CEO, Max Ma sits down with The PowerTalk Show and Navin Shetty to talk about transforming how global brands manage inventory, forecast demand and drive profitability.

“Retailers are still stuck on Excel. And Excel is the source of most inventory problems.” – Max Ma

While working in IT at a retail company, Max noticed systemic inefficiencies—millions in unproductive inventory, siloed decision-making and a heavy reliance on Excel. This sparked the idea for a smarter solution. Fast forward 26 years, and 7thonline is now trusted by brands like Calvin Klein, Tommy Hilfiger, Canada Goose and more.

The Problem: Excel is Still in Charge

Despite massive advancements in retail technology, Max highlights a reality few discuss: 70-80% of retailers still rely on Excel to make million-dollar inventory decisions. “It creates silos, errors, and a total lack of control,” Max says. “Our goal was to replace Excel—without intimidating the user.”

7thonline mimics the Excel interface while running a powerful AI-driven engine beneath the surface. The result? Fast adoption, deeper data insights and smarter forecasting.

The Solution: Smarter Planning Through AI-Based Retail Tech

Max and his team began integrating AI into their system over 20 years ago—long before AI became a buzzword.

“AI isn’t new. Our team has worked with it for 30 years. The difference now is people are finally paying attention.” – Max Ma

One standout feature? Test Buy Forecasting, which helps brands identify top-selling products within the first two weeks of launch. That agility alone has helped clients:

  • Increase gross margins by 30-35%
  • Reduce pre-season buys by half
  • Allocate budgets dynamically based on real-time demand

Real Results: Case Studies That Matter

7thonline isn’t just theory—it’s delivering real-world results. One client saved $1 per garment by placing production just one week earlier. With millions of units sold annually, that adds up fast.

In another case, a brand used 7thonline’s AI forecasting for a single product category of 30 styles. In just four weeks, they generated $320,000 in additional sales—a number that speaks louder than any sales pitch.

The Future: AI-Powered Trend Mining

The next big thing? Max is excited about new LLM (large language model) features that act like an intelligent co-planner for merchandisers. The platform will soon be able to:

  • Analyze macro trends from the internet and social media
  • Identify new product opportunities
  • Suggest seasonal forecasting based on current market shifts

AI will not replace people—but it will amplify their decisions. That’s where the future lies. Watch now to hear how Max Ma and 7thonline are not just forecasting demand—but creating it: https://www.youtube.com/watch?v=bEGnLYQSLbY 

7thonline is replacing Excel and saving retailers millions. To learn more about 7thonline’s platform, book a demo or email us at info@7thonline.com.

3 Takeaways from PI Apparel Merchandise Planning Show 2025

Retail trade shows and conferences are always an exciting time—full days of networking with leading experts, checking out innovative tech vendors and learning more about the industry’s needs. At PI Apparel’s Merchandise Planning Show, our team spent 2 days on the ground assessing merchant challenges and requirements. 

Here are three takeaways we uncovered at the PI Apparel show:

  1. Data, Data, Data

From big data and data analytics to data integrity and beyond, improving data quality and accessing actionable insights were top of mind for planners. Business of Fashion revealed in a report earlier this year that 75% of retail executives intend to prioritize data-driven tools in 2025—and the buzz at PI backed this up. 

A key benefit of using a system instead of 100s of spreadsheets is the elimination of data silos. Fractured systems give fractured results. Messy data and a lack of visibility was a recurring theme execs hope to address through retail tech; unifying plans and sub plans across brands/labels, regions, channels and departments on a single platform will especially improve the forecasting and reporting processes.

Having a master database not only comes in handy when planning and scaling, but also helps standardize global processes and connect internal teams: merchandising, product development, designers, etc. Manual processes slow down processes and limit the amount of accessible insights for dynamic responses. While brands recognize the importance of clean data and a unified system, the transition can be a daunting task, especially for heritage brands with decades of data or conglomerates acquiring storied brands left and right.

  1. AI Enhancing the Art

The resounding AI message at PI: AI will not replace planners, it will enable them.

Let’s talk about the art and the science of merchandising; the art is the human element to align products with branding and supporting designer vision, while the science is the data backing the decisions. AI comes in to enhance the art by analyzing data at scale, at a granular level, and improving operational efficiencies through automation. Another way AI can enhance the art of merchandising is by providing them with a smarter base for their planning processes, rooted in deep insights from robust analysis. While retailers are aware of the benefits of AI at this point, the challenge is with change management/trusting the system and being able to prove ROI. 

On the second day our team held a Think Tank around How to Perfect Your Merchandise Assortment with AI-Based Inventory Optimization, discussing how retailers can strike the right balance between demand, availability and profitability through merchandise planning. In our interactive session, we explored how AI-driven insights can refine assortment strategies, empowering retailers to stay ahead of the consumer with an agile, proactive approach to inventory management. More on this topic here: Why AI Data-Driven Retail is the Future—and How to Get There. 

  1. Tariffs

With the retail industry importing 97% of all goods from other countries, it’s not a surprise that retailers would be concerned about tariff uncertainty and the pressures associated with this supply chain disruption. As a result, flexible planning has become imperative to retailers, especially “what-if” scenario planning. To ease the pressure of volatility, retailers need to stay responsive. Visibility and accurate forecasting helps execs stay alert and nimble. 

In a previous post, we uncovered 5 strategies retailers can use to offset tariff costs. 

Short- and long-range planning is important. But needs accuracy. With a turbulent landscape, it’s nearly impossible to predict what will happen next—that’s where scenario planning comes in. Retailers need to be able to ascertain when to adopt a specific draft plan and when to pivot—tech simply presents the options in a streamlined way. 

The PI Apparel Merchandise Planning show focused on tech-enabled transformation; attendees could explore how different solutions would enable them to adapt to unpredictable trends and supply chain shocks that impacted their overall inventory strategies. 

To discover more retail trends, industry insights and innovative shifts in retail tech, read our blogs. Email us at info@7thonline.com to talk to the team.

Why AI Is Turning Order Fill Rate Into the Most Important KPI for Fashion Wholesalers

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.

7thonline Launches CoPlanner to Transform Merchandise Planning Through Smart Automation

Introducing CoPlanner, a new AI-powered tool that auto-generates merchandise plans based on historical success, helping retailers plan faster, smarter and with confidence.

7thonline, a leader in multi-channel, AI-based merchandise planning and inventory management solutions for retail, announces the launch of CoPlanner, a groundbreaking tool that auto-populates merchandise plans by analyzing historical data to identify what has worked best in the past. Leveraging large language models, CoPlanner streamlines the planning process, enabling planners to make adjustments using natural-language queries and visualize the impact of their changes in real-time.

CoPlanner elevates merchandise planning with conversational AI, granting quick access to actionable insights and stimulating results of various scenarios. The system will continuously refine recommendations, freeing retailers to focus on strategic decision-making rather than manual processes on Excel. Read more in WWD: https://wwd.com/business-news/technology/7thonline-launches-an-ai-powered-merchandise-planning-tool-1237692356/ 

From Data to Decisions: A Smarter, Faster Path to Profitability

CoPlanner integrates and evaluates data from multiple sources, including past sales, markdowns, inventory turnover, regional demand and seasonality, to auto-generate a smart, performance-driven merchandise plan. Using conversational AI, 7thonline’s CoPlanner identifies winning patterns through contextual generative AI and applies trending insights at scale across categories. 

“Our goal is to make merchandise planning more intelligent, data-driven and automated,” said Max Ma, CEO of 7thonline. “CoPlanner helps retailers start smarter by building on what already works, and then evolving those plans as conditions change. Automatically, planning gets more precise and better over time as the system learns which planner-made adjustments are most accurately reflected in real-time data.”

Designed for Merchandisers, Powered by AI

By combining automation with adaptability, CoPlanner allows retailers to:

  • Save hours of manual planning work and make sense of their data
  • Launch initial plans based on proven performance
  • Continuously refine and adjust plans in response to new data
  • Track plan-to-actual variance and update in real-time

CoPlanner is Built for a Multi-Channel World

CoPlanner fits seamlessly into existing 7thonline platforms, empowering retail brands to enhance decision-making and manage planning, assortments and allocation proactively across all channels. Whether for a single category or a multi-brand portfolio, the tool gives planning teams the clarity and control to act fast and profitably.

Backed by over two decades of dedicated AI R&D and continuous client collaboration, 7thonline has been empowering brands to make smarter merchandising decisions for 25+ years. 7thonline is a global leader in AI-native demand planning and inventory management solutions, offering retailers and wholesalers innovative functionality that optimizes their supply chains and drives profitability across all key channels. With a proven track record of breaking down silos between supply and demand, 7thonline provides unmatched flexibility, scalability and precision for businesses worldwide.

Built for today’s omnichannel world, 7thonline’s super-integrated platform offers bespoke solutions specific to multiple channels—direct-to-consumer brick-and-mortar, wholesale and ecommerce—to deliver better results out of the box. Trusted by industry leaders such as PVH, Birkenstock, Alexander Wang, Patagonia, Michael Kors and more since 1999. Rethink demand planning; place the right products in the right place at the right time.

To learn more about CoPlanner, contact the team at info@7thonline.com or visit www.7thonline.com.

5 Strategies Retailers (and Wholesalers) Can Use to Offset Tariffs

As global trade dynamics continue to shift, retailers and wholesalers are finding themselves in a new era of volatility. Once beneficiaries of globalization, the consumer goods sector is now facing increased uncertainty as protectionist policies and tariff expansions raise the stakes across supply chains. 

According to a recent PwC report, these tariffs could impact the consumer product sector by up to $134 billion. That’s five times the current tariff load of $27 billion. And the apparel industry is bearing the brunt of it. To remain competitive and profitable, businesses must embrace a more precise, tech-enabled and forward-thinking approach.

5 Tariff Strategies to Avoid the Cost of Getting it Wrong

One of the most underestimated consequences of tariffs is the cost of getting it wrong. Overbuying, inaccurate forecasting, or delayed inventory movement now come with a heavier price tag. Goods that were once slightly overstocked and marked down for clearance are now inventory liabilities that were more expensive to import in the first place.

As Arielle Knutson, CEO of athleticwear brand Oiselle, said to a Reuters reporter, “Ordering the right amount of product—and not being stuck with too much cash tied up in inventory—is key. It’s an almost impossible needle to thread.”

It might feel impossible, but it isn’t. Here are five tariff strategies wholesalers and retailers can take to offset the impact of tariffs:

1. Ditch “Excel Hell” for a Dynamic AI Platform

Managing critical functions through disconnected spreadsheets is no longer sustainable. Excel may have once worked for forecasting and inventory planning, but it can’t keep up with the pace, complexity and volatility created by shifting tariff policies and global supply chain disruptions. Relying on siloed data leads to misalignment across teams, delayed decisions and costly mistakes. If merchandising, planning and supply chain teams are all working from different files or outdated reports, it’s nearly impossible to respond in time to tariff-driven cost increases or sudden inventory shifts. Integrated, AI-powered platforms replace “Excel hell” with a centralized system of truth—eliminating manual processes and enabling faster, smarter decision-making.

These tools analyze real-time data across departments including merchandising, demand planning, sourcing and logistics, to generate predictive insights that help retailers buy smarter, reduce overstock and respond swiftly to market changes.

2. Nail Down Forecasting Accuracy

Historically, imprecise forecasting has plagued the industry, leading to overstocking, stockouts and wasted resources that impact profitability. With tariffs, the cost of being inaccurate is magnified. To succeed, retailers must embrace planning tools that offer better insight into what sells, where and when. Advanced inventory planning systems, powered by AI, allow retailers to align supply with demand precisely. By analyzing sales data and market trends in real time, AI-driven systems can accurately forecast demand and ensure inventory is purchased with purpose. 

3. Start Earlier

Timing is everything. Beginning the product lifecycle earlier gives businesses more room to negotiate with suppliers and avoid price shocks. One 7thonline client saved an average of $1 per garment simply by starting the production planning process one week earlier than competitors.

Early actions also allow businesses to diversify sourcing, reroute logistics and hedge risk before it becomes a crisis. If one supplier faces an increase in tariffs, retailers have more time to react; they can negotiate, find cost savings elsewhere or go with an alternative supplier.

4. Don’t Let Excess Inventory Drain Your Margins

Tariff-inflated products that don’t move fast enough get marked down, wiping out margins even further. Excess inventory takes up space, ties up capital, increases carrying costs and in a tariff-laden landscape, represents money spent on goods that may never sell at full price.  The key to reversing this trend is smarter buying from the start, backed by real-time visibility into demand signals. With integrated inventory management platforms, retailers can continuously monitor sales data and adjust open-to-buy budgets accordingly. 

5. Give People What they Want

Rather than planning for supply, retailers need to plan for demand. That starts with better buying strategies that prioritize precise assortment planning and allocation; the ability to identify the right products and match them to the right store locations, in the right sizes, is critical for the consumer experience. Inventory management solutions ensure retailers are stocked with high-demand products and can adapt to shifting consumer behavior. AI provides smarter allocation recommendations based on the propensity to sell for each product at each store location. 

Read the original article on Fashion Mannuscript here.

To learn more about how your team can use AI to offset increased tariff costs, email us at info@7thonline.com or book a demo with our team.

Retail Direct Marketing Offer Planning & Analytics Solution

Determine campaign ROI and refine offer planning with 7thonline’s AI-based catalog and direct marketing solutions that outline attribution down to page space, placement and circulation to determine the optimal operating profitability for each SKU. 7thonline’s powerful direct marketing suite assesses campaign contributions down to style, color, size, media and week.

Retail Marketing Analytics and Forecasting Solution for Catalogs & Direct Marketing Campaigns

Streamline catalog planning with AI-powered retail analytics solutions that offer impact and insights for optimal contribution margins. 7thonline provides direct marketing retailers the performance tracking needed to effectively plan, forecast demand and maximize conversions. 

Planning and forecasting solutions include:

  • Merchandise Planning
  • Assortment Planning
  • Offer Planning
  • Open-to-Buy
  • Embedded Forecasting & Reporting

AI-Powered Offer Planning for Direct Marketing Retailers

Make smarter decisions and increase contribution margin with data-driven insights. AI-powered offer planning leverages artificial intelligence to analyze customer behavior and historical data to predict what offers resonate best with specific segments down to page space, placement and circulation—reducing guesswork and manual effort.

7thonline’s AI-based system analyzes data based on all customer affinities: product, time, location and even media consumption (the why). This 4th dimension to the retail cube is a powerful approach to fully understand consumer behavior and make dynamic decisions.

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

Reducing Retail Tech Debt: Why AI Stack Selection Matters

Retail is in its AI era. From streamlining operations and optimizing supply chains to increasing personalization for shoppers, retailers have been eagerly jumping on the artificial intelligence bandwagon to modernize their brand and workflows. As the industry continues to embrace digital transformation and adopt innovative AI solutions, it’s important to remember—fragmented systems and duplicative functionality contribute to increased tech debt. 

person looking at a report on tablet to analyze store measurement

Be wary of bolting new AI tools onto already complex tech stacks as it could create a sprawling mess of disconnected platforms and overlapping capabilities; simplify your AI stack before it becomes tech debt. Managing technical debt is crucial for maintaining agility and delivering exceptional customer experiences. Technical debt refers to the long-term costs associated with choosing suboptimal solutions that require future rework such as additional implementations. Accumulating technical debt can hinder innovation and agility, making it challenging for retailers to adapt to market changes effectively. 

Duds & Dupes: Your AI Tech Stack

Many retailers are expanding their technology stacks with a variety of AI platforms to support current and future business needs. As businesses grow, and needs change, retailers will seek out more solutions that address new concerns; however, sometimes this leads to patchy workflows and/or duplicative functionality. Streamline your technology stack by adopting a single AI system that aligns with your business needs and scales as you grow—analytics, personalization, forecasting, inventory optimization and more—not only simplifying your AI stack but also enhancing operational efficiency.

In order for AI to be truly impactful, it must be embedded into every step of your workflow. Instead of piecing together a patchwork of specialized AI tools, or worse—fake AI modules, select a system that offers comprehensive functionalities to avoid the pitfalls of managing multiple disparate tools: outdated data, low visibility, inaccurate forecasting, limited collaboration, etc.. 

Eliminating redundant components and embracing multi-purpose services also simplifies your AI stack. You don’t need separate assortment management systems for ecommerce and physical retail, or isolated demand planning for stores and wholesale accounts. Simplification not only cuts down on the resources needed for system upkeep but also accelerates the implementation of new features, ultimately enhancing your ability to respond to market demands and meet shopper expectations. As retailers continue to embrace digital transformation, choosing an all-in-one AI system can be the smartest way to stay ahead—without drowning in complexity.

The takeaway: you don’t need more AI tools. You need a better, unified one.

While adopting AI is essential for staying competitive, retailers must approach its integration thoughtfully—choose integrated and comprehensive solutions that closely align with business needs from the start. Unified AI platforms reduce complexity and technical debt, paving the way for sustained innovation and ensuring that your systems grow in tandem with your business objectives.

7thonline is a leading provider of cross-channel merchandise planning and assortment management solutions, empowering retailers and wholesalers to make smart decisions at every step of the retail workflow. With artificial intelligence and machine learning embedded into the core of the platform, 7thonline has been enabling leading retailers and wholesalers to optimize planning processes, demand forecasting and inventory productivity. To learn more, email us at info@7thonline.com or book a demo with our team.