AI Shopping is in the Cart: Rewriting the Rules of UX

Despite the buzz around AI in retail, many shoppers are still on the fence. The three core reasons shoppers are hesitant to use AI shopping assistants: they don’t see the need, simply prefer human help or are concerned about privacy/data security. But as major industry players continue rewriting the rules of UX for AI-assisted shopping, making it more embedded and intuitive in the buyer journey, what feels foreign today is fast becoming tomorrow’s norm. Soon, the sentiment around AI-assisted shopping will shift from skepticism to everyday expectation. And retailers need to embed intelligence into their digital commerce experience to stay ahead.

AI Shopping is Getting Smarter & Quieter

Many retailers are investing in AI to enhance shopping across channels—reshaping both backend operations and consumer-facing experiences. Statista revealed that customer service was the leading use case for AI among ecommerce businesses, with 61% opting for chatbots; the global AI for customer service market was estimated to be $13 billion in 2024 and is expected to reach $84 billion by 2033. But Prosper Insights and Analytics revealed in Forbes that over 70% of American shoppers 18+ would prefer to speak to a live sales associate rather than an AI bot, suggesting retailers may have jumped the gun regarding AI chatbots.

So what do shoppers want? Speed, simplicity and confidence. AI has been quietly delivering on all three, becoming the backbone of modern commerce, not through bots but through embedded predictive infrastructure that shifts how brands approach customer experience, operational efficiency and personalization at scale. 

Behind the scenes, AI has been influencing the buyer journey for shoppers in the research phase—think tailored product feeds, predictive search and recommendations based on browsing history. As generative AI becomes less of a novelty and more of a silent engine behind digital experiences, the paradigm is shifting. When it’s so seamlessly integrated into the shopping journey, customers don’t even realize they’re interacting with it. And maybe that’s the key to shifting consumer sentiment around AI from skepticism to trust: frictionless use cases that quietly (and accurately) get the job done.

The Rise of Embedded AI in Retail: Rethinking UX, Trust and Personalization

For brands and retailers, the opportunity for AI-assisted shopping isn’t in building technology that looks futuristic—it’s in deploying AI that feels natural, builds trust and delivers measurable impact without disrupting the user experience. 

The biggest names in AI and commerce have leaned into this shift by redefining UX and hyper-personalization with a streamlined, end-to-end approach. OpenAI’s latest partnerships with Salesforce, Stripe, Etsy and Shopify mark a significant advancement in the AI for shopping space; Instant Checkout is turning the popular ChatGPT program into a storefront, seamlessly closing the loop with a shopping experience that simplifies the buyer journey from research to purchase. No redirects. Just intent, met instantly, personalized to the user’s conversation with Chat. 

While the general population is curious but hesitant toward AI-powered shopping, this UX upgrade may fundamentally shift how consumers view AI-assisted shopping experiences. By turning ChatGPT into a fully shoppable interface—powered by trusted platforms like Salesforce’s Enterprise Work and Commerce arms, Stripe, Etsy and Shopify—OpenAI is seamlessly bringing AI shopping to over 700 million users per week. On a mission to meet customers where they are, these partnerships empower merchants to offer seamless, secure transactions and capture demand when shoppers search for products—while keeping full control of their processes, data and customer relationships. 

AI is No Longer a Feature—It’s the Foundation of Modern Shopping

As generative AI becomes more embedded across commerce platforms, retailers are shifting from chatbot-based experiences to full-scale, AI-driven infrastructure. What was once experimental will become essential. AI is quietly redefining digital UX; the next evolution of AI in retail won’t be about bots replacing associates—it’ll be about intelligence embedded so deeply into the user experience that it becomes invisible.

As systems get smarter, more contextual and better aligned with consumer behavior, hesitation will give way to habit. For retailers, the challenge now isn’t to prove the value of AI, but to design it so seamlessly that shoppers never have to think twice.

Email us at info@7thonline.com or book a demo to talk to the team about AI-assisted shopping.

Consumer Insights: Planning Ahead for the New Retail Calendar

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.

Boosting Retail Sales Through AI-Improved Inventory Management

Artificial intelligence is now touching every industry, including retail, and retailers of all sizes are tapping into the technology to improve their operations. While AI can give all aspects of a retail business a boost, there’s one particular area that’s capturing the limelight right now: inventory management.

Improved Inventory Management: The AI Boost

Improved inventory management starts with accurate demand forecasting and real-time visibility into product locations; AI gives retailers a dynamic edge. With deeper insights into shifting customer behavior and real-time demand signals, forecasting becomes more precise—allowing inventory levels to be adjusted in the moment, not after the fact. The technology grants them deeper insights into how customers are behaving and what demand is looking like. As a result, demand forecasting becomes more precise, enabling retailers to adjust their inventory levels in real time.

“AI enhances demand forecasting and inventory management by rapidly analyzing large data sets from various sources in real time to deliver accurate forecasts and data-driven inventory recommendations. With faster insights—down to style, color, size—brands and retailers are able to make agile inventory decisions that align with demand in real-time and optimize stock levels across channels by predicting what products are needed, where and when.” – Max Ma

By improving inventory management, retailers can hold the right number of products in the right colors and sizes at the right locations, enabling them to better meet customer demand while minimizing warehouse costs and maximizing profitability due to reduced stockouts.

Using AI to better forecast demand leads to improved accuracy and customer satisfaction, making this technology a critical part of today’s inventory management systems.

The Future of AI in Inventory Management

Going forward, we can expect AI to improve more and more over time, both in general and for retailers using the technology. Retailers have already been reaping the benefits of using AI in inventory management, reporting actual numbers demonstrating the improvements they’ve seen. But the more a retailer uses AI for things like demand forecasting, the better it will get at predicting customer flows and demand. Those that start early will gain a competitive advantage, as the gap between adopters and laggards is only going to widen.

Read the full article on Retail Insider here: https://retail-insider.com/articles/2025/10/how-ai-is-boosting-sales-for-retailers-through-improved-inventory-management/ 

To learn more about how AI for inventory management, book a demo or email us at info@7thonline.com.

How AI Helps Retailers Protect Holiday Margins Without Resorting to Markdown Madness

The 2025 holiday season is shaping up to be one of careful calculation for retailers. According to the National Retail Federation (NRF), holiday sales in November and December have averaged about 19% of total retail sales over the last five years, though for some retailers, the figure is even higher. For retailers, the holiday season is a critical period of heightened sales, fierce competition and strategic opportunity. In order to maximize profitability as holiday gifting peaks, it’s important to protect gross margins before markdowns come into play. 

Holiday sales are often more profitable because the surge in purchases occurs without significantly increasing retailers’ fixed operating costs—retailers can maximize margins through scale. For 2025, consumer spending is expected to remain cautious as economic uncertainty shapes buying behavior. Against this backdrop, retailers face the challenge of striking the right balance between promotional activity and profitability. Prioritizing margin over markdown has emerged as the strategic focus. 

Multi-Channel Demand Planning: Combining AI and Brand Identity

The uncertainty and ever-shifting dynamics of today’s retail landscape are reshaping how consumers shop, especially during the holiday season. To stay ahead, retailers are turning to AI-powered demand planning software that combines detailed analytics with merchant intuition and creativity. This powerful pairing enables retailers to anticipate shopper expectations at a granular level—down to style, color, size—and make smarter inventory decisions that drive both sales and satisfaction.

Blending brand identity with AI-driven insights allows retailers to deliver tailored shopping experiences that meet demand across every channel. By analyzing customer behavior, preferences and purchase history, brands can curate assortments that reflect their aesthetic and resonate with their audience, creating an authentic and personalized shopping experience that reinforces brand loyalty while boosting conversions through more intuitive, margin-protective product offerings.

Protecting Holiday Margins & The High Cost of Markdowns

A key distinction in holiday planning lies between discounts and markdowns. Discounts are temporary promotions used to spark urgency and drive sales during specific events, while markdowns represent permanent price reductions designed to clear out excess or slow-moving inventory.

The financial stakes are high. Markdowns have long been a drain on profitability, cutting into margins with estimates showing they cost U.S. retailers about $300 billion in lost revenue. That’s roughly 12% of total sales according to a report from Coresight Research. While that figure predates by almost a decade, with the current economic environment, it remains a telling indicator of how damaging reliance on markdowns can be to the bottom line.

The risks of over-relying on markdowns are clear:

  • Diluted brand value: Frequent markdowns condition customers to wait for sales, weakens loyalty and diminishes the brand’s perceived value. 
  • Eroded margins: Each markdown directly chips away at profitability. Not even accounting for the increased operational costs with storing and holding unsold inventory. 
  • Inventory glut: Excess stock leads to overcrowded racks of outdated merchandise, fueling a markdown dependency to clear cluttered storefronts. 

Brand Loyalty vs. Bargain Hunting: What Wins Over Today’s Shoppers

Today’s consumers are showing a clear willingness to trade loyalty for savings. According to the Wunderkind 2025 Tariffs Consumer Impact survey, 76% of Americans say they’re ready to switch brands for a better price, often for as little as a 10-20% deal. This cost-conscious mindset puts retailers in a difficult position as rising tariffs drive prices higher and shrink purchasing power. In fact, two-thirds of retailers report they cannot afford to absorb the extra import costs themselves.

The impact is already visible. June marked the first tariff-driven price hikes, with goods seeing the sharpest cost increases in five months and the Consumer Price Index rising by 0.3%.  Between weakening brand loyalty and declining purchasing power, retailers must recalibrate holiday strategies. 

Enhance Retail Holiday Planning Ahead of the Frenzy

Getting ahead of the Black Friday/Cyber Monday rush demands thoughtful planning and precision execution. Holiday demand remains unpredictable, and with supply chain challenges still in play, even leading retailers risk stumbling when it comes to inventory management. The era of relying on shopping “showdowns” is over. The winners will be those who gain a competitive edge through smarter allocation and proactive planning that minimize inventory risk and maximize profitability.

For apparel and fashion brands especially, success relies on having the right product, in the right sizes, at the right locations. Missteps in allocation can mean lost sales, frustrated customers and unsold inventory where it’s least needed. That’s where AI-powered solutions come in, enabling retailers to forecast with greater accuracy, optimize allocation in real time and ensure that every unit of inventory is working toward the bottom line and a successful holiday season.

Read the original article in Fashion Mannuscript here: https://issuu.com/mannpublicationsmagazines/docs/fm_october_2025?fr=sZDY2ZTg2MDI5NTU 

To learn more about how AI can help brands and retailers preserve margins without resorting to markdowns, book a demo or email us at info@7thonline.com.

Demand Volatility: Smart Brands Are Turning to AI for Their Core Retail Strategy

Artificial intelligence is quickly becoming the foundation of efficiency in the world of retail—from demand forecasting and sales analysis to localized allocation and personalization. The technology is arriving on the scene just in time, promoting agile strategies as shopping behaviors shift faster than ever. In response, retailers are building more responsive planning strategies to meet shoppers where they are, with products they are looking for, and AI is becoming central to that effort. Using AI, retailers can more accurately forecast sales trends, quickly respond to shifting consumer behaviors and preserve loyalty—making it a core part of their strategy as they face volatile demand.

Why Chatbots Shouldn’t Be a Top Area of AI Spending for Retailers

Given consumers’ familiarity with generative AI and the cost savings associated with using AI for customer service functions, some retailers are spending heavily on generative AI chatbots in an effort to increase personalization for online shopping experiences. According to Prosper Insights & Analytics, more than 70% of Americans ages 18 and older would prefer to speak to a live person rather than a generative chat program. 

“Of course, this isn’t the only use case for AI in retail, nor is it necessarily the most effective use of budget; consumers are very familiar with AI, but that doesn’t mean they want to deal with it when shopping, and until sentiment around AI for customer service changes, spending may be better focused on optimizing inventory and supply chains or enhancing merchandising strategies. These are use cases that directly impact the bottom line,” commented Max Ma, CEO and Founder of 7thonline. 

Staying Ahead of Shoppers & Driving Loyalty with AI

According to a recent 7thonline survey, one-third of retail executives are already using AI to forecast and analyze demand, while 34% expect it to play a major role in sustaining or growing profits over the next two years. Retailers aim to use AI to stay ahead of shoppers by predicting and capturing emerging trends. The ability to analyze mass amounts of historical and current data in real time down to style, color, size is invaluable to stay ahead of shoppers. 

Retail success has come to depend on AI tools that are able to identify exactly what shoppers are looking for, when they are looking for it—improving the customer experience and fostering loyalty. Brand loyalty is a challenge in the current environment, especially among younger generations who are more likely to switch brands based on price and other qualifications, like value alignment. Forrester estimates that brand loyalty will decline 25% in 2025, adding that saving money is one of the top five reasons consumers in the U.S. will try a new brand. Additionally, a recent Prosper Insights & Analytics survey, found that 39% of Americans age 18+ are buying more store brand or generic products due to price increases. Customers are also shifting away from traditional, transactional programs toward more personalized, value-driven and emotional shopper experiences.

Improve Demand Forecasting—AI at the Core of Retail Strategy

AI’s ability to analyze massive amounts of real-time data in a snap is the crux of its ability to accurately predict sales all the way down to style, color, size, by location. By delving deep into both internal and external data, and current and historical trends, AI models can spot patterns that a human would probably miss when looking at a large number of spreadsheets.

Unlike human analysis, AI technology can easily and quickly incorporate external data like weather conditions, social media sentiment, sales put on by competitors and impact from brand promotions. As a result, retail executives who know the best places to spend their AI dollars will be better prepared to weather the current storm.

Read the full article on Forbes here: https://www.forbes.com/sites/garydrenik/2025/10/07/ai-becomes-a-core-strategy-for-retailers-facing-volatile-demand/ 

To learn more about how AI can help brands and retailers with their merchandising, book a demo or email us at info@7thonline.com.

Vote Now: 7thonline in Final Ballot for Best of America, Small Business Award 2025

We’re thrilled to announce that 7thonline has been named a finalist for a Best of America, Small Business Award! The BASA awards celebrate exceptional small businesses in the United States, recognizing businesses and individuals who are leaders and innovators in their sector. Following judge’s selection, each finalist is admitted to a round of public voting—leaving the decision in the hands of the masses.

For 25+ years, 7thonline has remained committed to helping the retail industry, which still relies heavily on Excel, by offering AI capabilities that enhance profitability and elevate inventory productivity. With only 40% of inventory contributing to a brand’s overall profit, 7thonline embarked on a mission: break the cycle of low margins, limited resources and sub-optimal decision-making. In a world where accuracy, speed and adaptability define retail success, 7thonline stands out as a transformative technology—delivering measurable impact at every step of the supply chain.

Our mission is to modernize retail planning, spread industry best practices and enhance retail processes through science and technology. By leveraging advanced AI/ML models to provide granular demand visibility down to style, color, size, retail businesses are able to align supply with shifting customer preferences and market trends. 

From a 800 sq ft office to signing some of the most reputable retail brands and expanding our product from a small part of supply chain planning to now covering the full spectrum of multi-channel inventory planning and production decisions, and more, 7thonline has scaled while maintaining their small-business model, rooted in boutique customer service and client experiences.

7thonline is committed to building long-term partnerships, putting client success at the forefront by creating best-in-class innovations that directly address industry challenges. We’re always developing new functionality to directly address industry needs, working hand-in-hand with top retailers to expand our algorithms and embed retail best practices into the system. Each client is provided with a dedicated team for full training services prior to launch and new functionality; the company offers robust training and implementation support tailored to end users business processes, ensuring adoption and alignment with merchandising objectives.

Thank you to the BASA team for this honor, and congratulations to the other finalists! It’s an honor to make it to the final ballot alongside other small, but mighty, companies.

To learn more about 7thonline’s platform, book a demo or email us at info@7thonline.com. 

AI in Commerce News: Instant Checkout in ChatGPT

The AI in commerce market ended Q3 with big news: shoppers can now buy products directly in ChatGPT. With Instant Checkout, ChatGPT isn’t just a guide—it’s a storefront.

Earlier this week, OpenAI announced a partnership with Stripe, Etsy and Shopify that connects people and businesses to the next era of commerce—using AI as a key interface for how people discover, decide and buy. While conversational AI has already proven its value in product discovery and customer service, the ability to complete purchases directly within a chat interface marks a major leap forward. 

While the general population is curious but cautious about AI-powered shopping, over 700 million people use ChatGPT every week. So, chat, is this partnership the turning point for how people will feel about using AI to shop?

Click From Chat to Checkout: Full-Funnel AI Shopping

Until now, conversational AI has helped shoppers discover products, ask questions, and compare options. But one critical step remained outside the AI loop: the transaction itself. This seamless integration of discovery, decision-making and transaction radically simplifies the buyer journey. It eliminates friction, closes the loop and turns intent into action in a matter of seconds. 

This isn’t just a user experience upgrade; it’s a fundamental shift in how consumers interact with brands and make purchases.

While Americans still have hesitations around AI-assisted shopping—for various reasons found here—we believe this is the feature that will unlock consumer acceptance of AI in commerce. Why? Because it offers something every shopper wants: speed, simplicity and confidence. That’s the kind of efficiency today’s consumers demand—and tomorrow’s AI-native shoppers will expect. 

The Market Has Spoken: Retailers on AI in Commerce

For retailers, this marks a new chapter—one where traditional product journeys are compressed into a few lines of dialogue, and AI doesn’t just influence conversions, it owns them. For brands and retailers, this shift changes the game. We’re entering an era where brand visibility, product discoverability and conversion will increasingly be influenced—or entirely driven—by AI systems.

“Bringing Shopify merchants into ChatGPT lets indie brands to household names reach customers in entirely new ways, meeting high-intent shoppers in relevant conversations. From search to social media and now to agent-assisted shopping, our goal is always to make sure our merchants are at the forefront.” – Vanessa Lee, VP of Product at Shopify

Merchandising strategies, inventory planning and assortment decisions need to evolve to account for AI-driven demand signals. Retailers can’t just think in terms of website traffic or social ads anymore. They need to think in terms of chat visibility. AI is curating the chaos of the digital shelf, making product discovery more intuitive, more relevant and more human. 

“It’s Etsy’s job to help shoppers discover special items our sellers offer—even when they don’t think to come to Etsy. ChatGPT helps us meet buyers where they are.” – Rafe Colburn, Chief Product and Technology Officer at Etsy

The recent partnership between OpenAI and major commerce platforms is a clear signal that the retail and tech markets are aligning around a new shared vision: AI will become a core sales channel. And that bet is backed by more than hype. It reflects a maturing ecosystem that’s ready to deliver value.

By turning ChatGPT into a fully shoppable interface—powered by trusted platforms like Stripe, Etsy and Shopify—OpenAI is helping redefine AI in the commerce space. For retailers and brands, this is the moment to rethink visibility, discoverability and conversion in a world where AI is no longer just assisting the shopping experience—it’s becoming the channel itself. 

To discover more retail trends, industry insights and innovative shifts in retail tech, read our blogs. Share your thoughts with the team by emailing info@7thonline.com.

Forget the Retrofit: Super-Integrated AI for Multi-Channel Success

The culmination of necessity and innovation, artificial intelligence has become a cornerstone of retail growth by helping brands understand customers, forecast demand and deliver seamless, personalized shopping experiences across channels. But simply retrofitting AI onto outdated systems won’t cut it. True multi-channel success depends on super-integrated AI and solutions that are built with connectivity and adaptability at their core. When AI is deeply embedded across sales, inventory and customer touchpoints from the start, it delivers faster insights, smarter decisions and the agility retailers need to thrive in today’s dynamic market.

All-in-One AI Wins: Unlocking AI’s True Potential

The true value of AI lies beyond a standalone module—it must be integrated throughout the system to provide context and end-to-end analyses that impact your bottom line. 

AI’s power is in identifying risks/opportunities by accounting for multiple variables at an incredible speed. For multi-channel retail brands, this means embedding AI in every part of the process while also adapting to the unique demands of each channel—all within a unified platform. An all-in-one AI system not only enables smarter decision-making for each channel, but also shows how they each fit into the broader strategic goal; brands are able to analyze performance from the lens of channel-specific KPIs and make informed business decisions based on comprehensive insights from complete demand. 

Wholesale account planning is different from DTC store planning or ecommerce marketplace planning—your processes and AI usage should reflect that. With super-integrated AI solutions, multi-channel brands are able to drill in on the nuances of different channels and seamlessly understand how they contribute to the big picture. 

The Pitfalls of Retrofitting

Retrofitting AI solutions for each channel can offer quick wins, but often at the cost of complexity, fragmented processes and missed potential. An overlooked risk when applying AI across retail channels is the misalignment between assumptions baked into the model and the realities of the channel it’s being applied to. 

AI-native systems for DTC needs are optimized for direct consumer behavior and needs, analyzing real-time demand for each SKU at each location—data is plentiful, feedback loops are fast and decisions are granular. AI for ecommerce adds another layer to consider digital marketing promotions, algorithmic search optimization and product placement on the page. AI systems for wholesale have a different foundation, where the crux of the need is centered around bulk orders for department stores, independent retailers, franchises, etc., including the lead times for accounts and the seasonality of products.

 

Retrofitting AI limits its accuracy, as the system learns from behaviors that don’t align with the channel’s realities—resulting in mismatched optimization recommendations due to differences in:

  • Demand Patterns: frequent transactions vs fewer transactions in large quantities
  • Forecasting Horizons: daily/weekly adjustments vs seasonal adjustments months in advance
  • KPIs and Optimization Goals: conversion rate vs order fill rate

This misalignment due to channel-specific nuances leads to poor planning decisions and inventory mismanagement, underrealizing AI’s full potential.

Integrated AI Powering the Next Generation of Multi-Channel Retail

The next generation of multi-channel retail success depends on a retailer’s ability to deliver consistent, personalized experiences across every channel from ecommerce marketplaces and mobile apps to brick-and-mortar stores and wholesale partners. Utilizing AI-native platforms that consider the state of the union across functions, revenue streams and more, it’ll be easier than ever to meet shopper demands. Truly integrated AI systems connect data from all touchpoints to improve forecasting and real-time merchandising decisions across the retail workflow—it’s not fragmented or layered on as an afterthought. 

Integrated AI platforms, like 7thonline, make this possible by unifying pre-season and in-season data streams across the entire retail ecosystem: sales, stock levels, lead times, production orders, SKU demand and more. With bespoke functionality tailored to different selling channels, the platform helps retailers forecast demand with greater accuracy, plan more effectively and adjust quicker as market conditions change. With end-to-end visibility, retailers can reduce inefficiencies, improve margins and deliver a seamless experience for customers, no matter where or how they shop.

The future of retail won’t be defined by patchwork AI add-ons but by end-to-end, super-integrated platforms that analyze patterns, anticipate market shifts and recommend actions. Integrated AI solutions are able to empower decisions that align with the overarching strategy. It’s up to the retailers to apply the data-backed insight with their own expertise in order to maximize results. 

Read the original article in the AI Journal here: https://aijourn.com/forget-the-retrofit-super-integrated-ai-for-multi-channel-success/ 

Unlock the secret to multi-channel success. Discover how 7thonline’s super-integrated solutions can help by booking a demo or emailing us at info@7thonline.com.

7thonline Named a Finalist for Retail Tech Innovation Hub’s 2025 Omnichannel Award

We’re thrilled to announce that 7thonline has been named a finalist in the Omnichannel Retail Initiative category at the 2025 RTIH Innovation Awards! The RTIH Innovation Awards celebrate the most transformative and forward-thinking work in retail technology, and being shortlisted alongside such impressive companies is an honor. As an Omnichannel Retail Initiative finalist, 7thonline is being recognized as a leading provider of tech-centric solutions that integrates shopping experiences across brick-and-mortars, online, mobile and everything in between.

retail tech innovation hub, the future of retail awards

Our nomination reflects the work we’ve done to break down silos and create a truly unified experience across physical and digital touchpoints. 7thonline empowers brands to make integrated inventory decisions based on insight into emerging trends and visibility across stores, ecommerce websites, wholesale accounts, marketplaces and more to unify retail planning and rethink demand. From enhancing customer journeys by leveraging real-time data to reimagining how channels work together seamlessly, we’re proud of the impact our omnichannel approach is making—and this finalist spot confirms we’re on the right path.

Today’s shoppers move seamlessly between channels; blurring traditional channel lines demands a unified, agile approach to inventory, fulfillment and customer engagement. Retailers can no longer afford fragmented systems or siloed operations that slow down response times or limit visibility. This agility not only improves operational efficiency but also ensures better product availability and an overall enhanced shopping experience. As consumer loyalty becomes more fleeting, the ability to adapt quickly and serve customers wherever and whenever they shop is now a key driver of long-term sales and brand success.

7thonline is uniquely positioned to provide a holistic view of global demand, leveraging advanced AI and robust data from wholesale and direct-to-consumer retail channels with channel-specific functionality. Through artificial intelligence, 7thonline is able to analyze historical sales and external data points to obtain trend information and forecast future demand as it pertains to the channel’s unique needs. 

By using 7thonline, brands are able to make integrated inventory decisions across key selling channels—wholesale, brick-and-mortar retail, ecommerce—with deep demand visibility into what is selling, where. Stay ahead in today’s complex retail landscape and seamlessly meet demand across key channels with an integrated, end-to-end planning platform. 

Thank you to the RTIH team for this honor, and congratulations to the other finalists! We’re excited to celebrate your achievements in the retail tech space. Winners will be announced later this year—stay tuned.

To learn more about 7thonline’s platform, book a demo or email us at info@7thonline.com. 

Enhancing Fashion Merchandising Instincts with Data Science

McKinsey & Company recently reported that retailers using AI-based assortment planning solutions have cut SKUs by 36% while lifting sales 1-2%, a leaner merchandising strategy driven by data science. Thanks to AI-driven inventory planning, machine learning and data science, smart retailers are able to better manage SKUs, grow sales and meet customer demands to enhance decisions.

fashion merchandising meets tech

Making The Data Work for Multi-Channel Fashion Merchandising

While algorithms and AI models are setting a new standard for data accuracy, the real success in fashion merchandising comes from combining creative expertise and industry insight with automation and AI insights. Retailers understand the nuances of their markets and customers and they are able to anticipate trends and adjust, to 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.

By taking massive amounts of data in real-time and turning it into precise, actionable insights, AI systems are enabling retailers to make smarter, faster decisions at a granular level. Between dynamic open‑to‑buy decisions, allocation based on localized demand and real‑time decision-making, AI-powered inventory management is making the data work for multi-channel retailers through accurate demand forecasting. 

Best Practices: Blending Science and Art in Retail

7thonline has always reinforced the message that AI is a tool, not a replacement for retail expertise or the human eye. It’s the planner, the designer and the strategist who recognizes emerging trends and applies insight. The most successful retailers approach AI‑driven merchandising as a partnership between technology and people, seamlessly blending the art of merchandising and the science of data.

While algorithms excel at analyzing data and forecasting trends, it’s humans who interpret those insights through the lens of brand vision and creative intuition. AI analyzes customer behavior, regional preferences and past performance to recommend the most optimal product mix, while merchandisers apply their intuition to curate assortments that connect the brand with their shoppers. Merchants carry the brand’s DNA into every assortment decision, ensuring that what’s on the rack resonates not just with a data profile, but with the community it serves. Combining data-driven insights with human creativity, enables retailers to make smarter, faster product decisions. 

The retail industry, particularly in fashion, is driven by individuals with a deep passion for their craft. Many have spent their careers mastering how to anticipate what shoppers will want, before they even want them. Both a learned skill and a purposeful instinct, selecting the right styles, colors and sizes for the right stores at the right time, is an art baked into the shopping experience. The strategic blend of timing, positions and sensory elements, bring a brand’s vision to life and AI helps to ensure that experience will resonate with the target audience.

Use Case Scenarios

In today’s dynamic landscape, blending the art and science of retail can look different in practice. It all depends on your own business needs. The following use cases illustrate how retailers can harmonize creative judgment with advanced technology:

Assortment Planning

Blending data and creative curation, AI-powered assortment planning ensures the product mix reflects both customer demand and brand identity. The data science behind AI systems analyzes the “what” (what product mix, what store, what channel) while merchants fine-tune the “why” using the extensive knowledge they’ve gained on which trends are still in their early stages, compelling storytelling and how shoppers will react. 

Dynamic Replenishment

While predictive analytics and real-time sales data empower dynamic replenishment decisions, such as reorders, these systems only account for seasonality, past trends and product lifecycle stages. It’s up to the merchants to detect shifts before algorithms, such as weather changes, large marketing pushes, influencer buzz and more. Using detailed insights for efficiency and precision, retailers are able to make context-aware decisions, at scale, with specificity, that react to the nuances of real-world events beyond historical data.

Trend Forecasting

AI systems can read the signals, but merchants can read between the lines. With AI systems picking up massive amounts of data from various sources, retailers are able to see early signals on trending products, long before the results hit their sales numbers by bringing breadth and speed to trend detection. Experienced merchants are the ones that know how to interpret these signals through the lens of their brand and customer, to turn the signals into differentiated product decisions. 

In each case, human expertise turns AI’s recommendations into market‑ready decisions that impact the bottom line.

Read more in the September 2025 issue of Fashion Mannuscript here: https://issuu.com/mannpublicationsmagazines/docs/fm_september_2025_full?fr=sYTRjMzg2MDI5NTU

To learn more about enhancing the art of merchandising through data science and AI-powered solutions, email us at info@7thonline.com or book a demo with the team.