Introduction

Coresight Research is a research partner of Shoptalk Spring 2026, taking place March 24–26 at the Mandalay Bay resort in Las Vegas, Nevada. In this report, we present highlights from the morning sessions of Day 2, covering three themes.

• AI Applications for In-Store Physical Retail—Industry leaders discussed how brands are testing and scaling AI to improve in-store service, support associate workflows, manage inventory and deliver personalized experiences.
• Driving Costs Out of Fulfillment and Delivery—Speakers examined how to reduce hidden exception costs in the delivery process and the physical and technological requirements for scaling drone delivery.
• Technologies Transforming Marketing and Advertising—Panelists explored the impact of agentic platforms on product discovery, the growing importance of human-generated content for AI algorithms and practical frameworks for bringing AI into marketing workstreams.
• Strategy, Storytelling and Customer Truths—Speakers explored Victoria’s Secret’s decision to separate Pink and Victoria’s Secret into distinct brand identities, the role of physical retail in the “soothing economy,” and strategies for building lifelong customer relationships while maintaining shared infrastructure and scale advantages.
• Predictions for the Future of Retail—Shoptalk executives outlined key predictions that will reshape how commerce is conducted and experienced, including agentic commerce, GLP-1 drugs, recommerce, physical store transformation and demand sensing.

Shoptalk Spring 2026, Day 2: Coresight Research Insights

1. AI Applications for In-Store Physical Retail

The clearest message from this session was that AI’s most immediate role in physical retail is not replacing human interaction but improving it, giving store associates the information and tools to deliver more seamless, informed and personal experiences. The Vitamin Shoppe and Tecovas both said their primary goal is better hospitality, with AI working behind the scenes rather than as a visible feature of the customer experience. At The Vitamin Shoppe, that takes the form of “Shop Advisor,” which surfaces educational content and product recommendations in-store, helping both customers and associates navigate complex health decisions. To build associate knowledge, the retailer uses a gamification platform called Exonofiy with an “Elevate” tool, which tracks where each associate is in their learning journey and teaches accordingly.

Associates are also encouraged to ask customers for their phone number at the start of the visit to pull up loyalty details, freeing up the rest of the interaction for direct engagement. Andrew Laudato, Chief Operating Officer at The Vitamin Shoppe, said, “We didn’t set out to use AI—we set out to provide a better customer experience.” Laudato added, “AI will take away the worst part of your job.”

On the data side, the company built its infrastructure from the ground up using a clean room and medallion architectures, working from the principle that incomplete data is better than wrong data. It also syndicates its content and product catalogs, including research papers, into large language models to show up in relevant search results. Beyond the store, The Vitamin Shoppe works with Uber Eats and DoorDash for delivery, with the view that the omnichannel customer is the best customer and should be able to shop wherever they prefer.

Tecovas has focused on the operational friction points that come with scale, particularly the challenge of managing 13 sizes in regular and wide footwear backstock. Its “Boot Runner” app lets associates request products from the backroom without leaving the customer, replacing the radio and cutting wait times to an average of 85 seconds. The engineering team built it in two days. Kevin Harwood, Chief Technology Officer at Tecovas, said, “The worst thing that can happen is the associate leaves the customer—we want them present every step of the way.”

To make sure Tecovas shows up in AI-driven discovery, the brand uses the UCP protocol with Google and Shopify and has adopted Algolia and Botify specifically for AEO and GEO content optimization. The company’s data shows that omnichannel customers have a higher lifetime value than single-channel shoppers, which has shaped a push to create experiences across channels. One example: when an online order is returned in-store due to a sizing issue, an AI tool checks the retail statistical area (MSA) to surface store-level inventory and hold the right size for the customer.

Tecovas also runs an internal AI agent that manages upcoming cultural and music event calendars across retail MSAs, scoring events by their likely impact on store performance. Harwood said he has seven to 10 agents running at any given time, and that this has changed how the engineering team works, with code now essentially throwaway. The pace of development has also changed how the company trains: Harwood noted that training takes five times longer than the actual software development, requiring headquarters to continuously retrain teams on how quickly software can now be built.

Despite all this, Tecovas still dedicates 20% of its floor space to experience rather than selling, with the open bar, blow torches, stamp personalization, hat customizations and boot shining all part of the brand. Harwood acknowledged that the company typically only identifies the customer in the final 10% of the journey, usually at the point of sale or during scheduled processes like boot shining or preparing whiskey for buy-online-pickup-in-store orders, because asking for identification earlier is awkward.

The most valuable AI applications in physical retail remove friction and lift human connection, rather than trying to automate it away. Both retailers showed that AI works best when it is embedded into workflows—inventory allocation, associate training, content delivery—where it produces measurable results like higher in-stock rates and better-informed staff. Tecovas’ nearly 10% revenue lift in test categories from AI inventory optimization illustrates the business impact of applying AI to core retail fundamentals. Both speakers pointed to a future where AI makes store experiences more localized and relationship-driven, potentially returning retail to something closer to its local roots.

Andrew Laudato, Chief Operating Officer, The Vitamin Shoppe
Source: Shoptalk Spring

 

2. Driving Costs Out of Fulfillment and Delivery

The real cost of delivery failure is hidden, and most retailers aren’t measuring it correctly. Salman Habib, Co-Founder & CEO at Burq, explained that retailers tend to merge the concepts of shipping and delivery, but from the customer’s perspective they are different, and a missed delivery leads to churn. Around 8% of first-time deliveries fail, with each late or failed delivery costing between $17 and $40 once reattempts, support tickets and customer churn are factored in. Habib recommended starting with a delivery promise that varies by fulfillment area, diversifying beyond a single delivery provider to reduce risk, and building AI agents for automated exception recovery such as auto-rerouting. He also made the case that while every company tracks cost per delivery, they should start tracking cost per failed delivery, because the customer who blames the brand and doesn’t return is the hardest cost to measure and the most damaging.

The panel also covered the rapidly growing drone delivery market. Heather Rivera, Chief Business Officer at Wing, said Wing grew five times in the last year, driven by a shift toward small-basket orders wanted quickly, a use case that traditional last-mile delivery, built for large shipments, was not designed for. The drone delivery market is projected to grow 2.5 times by 2030, potentially adding $8.3 billion in incremental sales and $2.4 billion in cost savings. With flight times under five minutes, Wing’s partners are already seeing gains in purchase frequency and customer satisfaction. Rivera was clear that drone delivery is for everyone but not for everything, and it won’t replace the heavy Sunday grocery shop, but it is well suited to a missing ingredient for dinner or an over-the-counter medication for an aging parent.

For retailers thinking about getting started, she pointed to three factors: deciding whether to run a standalone Wing app experience or integrate into the retailer’s own app; adapting the physical real estate footprint for drone charging infrastructure and ensuring the technology can handle dynamic neighborhood conditions like parked cars; and confirming that the delivery partner has enough FAA-approved aircraft to scale if consumer adoption is strong.

Data visibility and the product lifecycle rounded out the fulfillment discussion. Mo Afshar, Co-Founder & CEO at Pipe17, noted that retailers are often locked into logistics providers simply because switching takes six to 12 months to integrate a new one. Disparate inventory pools and disconnected systems produce stale data and canceled orders, costing retailers time, money and lost sales. Afshar put it plainly: retailers cannot optimize for cost if they cannot see. Pipe17 positions itself as the middle tier that connects brands and logistics providers. Chloe Songer, Co-Founder & CEO at SuperCircle, made the case that retailers need to stop thinking of fulfillment as the end of delivery. Returns are part of the first purchase flow, and the millions of units circulating with a brand’s name on them—in supply chains, in stores, everywhere—directly affect that brand.

3. Technologies Transforming Marketing and Advertising

This session focused on agentic platforms and what marketers need to do to stay relevant in them. Jacob Ross, CEO at PebblePost, opened with a straightforward data point: transaction data is the most impactful and predictive basis for understanding who to target and what they will do next, producing two to four times more incremental lift than offline data. Ross drew a direct parallel between AI platforms and search engines: if Google changed its algorithms, companies would feel it, and the same is true for ChatGPT and its peers. Relying on any single platform creates exposure; navigating this space is less a set-and-forget operation and more a capability that has to be continuously maintained. Ross said, “Marketers want to find proof points to build confidence in a world that feels like maximum hype.” He also offered a counterpoint to the agentic commerce discussion: humans still buy things, and there is real value in human-based marketing driven by actual transaction data and genuine acquisition.

James Cadwallader, Co-Founder and CEO at Profound, added that in the near future every company will care about how AI talks about their brand, and every marketer will use AI agents as a kind of “marketing engineer” to get work done faster.

Bringing AI into marketing workstreams without losing brand trust was the focus of Bruce Richards, Head of Industry Strategy and Marketing Retail & Consumer Goods at Adobe. Richards shared that 94% of retail and consumer goods marketing leaders are now expected to directly contribute to revenue, with profitable growth as their top priority. He pointed to 45% of consumers turning to AI tools in their buying journeys, and an Adobe-tracked 700% year-over-year increase in AI visit growth during holiday 2025 retail. The brand’s front door, Richards argued, is shifting from personalization to participation, which means building for both humans and agents.

He outlined three moves for marketers: shift from messaging to invitations, letting customers choose their own experience; move from one-off campaigns to living systems where AI learns from every interaction; and go from capacity to comfort, making interactions feel natural. Richards gave CMOs three questions to start with: what AI initiative could save 50% right away; what would make a measurable impact on customer experience without necessarily saving money; and what governance is needed to keep AI initiatives on-brand. Bruce Richards, Head of Industry Strategy and Marketing Retail & Consumer Goods at Adobe, said, “Marketers get it conceptually (AI), but struggle with the ‘how’—ecosystem education, across the org.”

AI’s rise has also made human-generated content more valuable, not less. Kristen Wiley, Founder & CEO at Statusphere, noted that AI overviews appear in over 60% of search results and 74% of Gen Z uses TikTok as a search engine, creating a new discovery flywheel of social search and AI. Where it once took seven touches to convert a customer, it now takes 15 to 20. Creators add a trust layer that AI cannot replicate, making human-generated content the primary fuel for generative AI, social SEO and traditional SEO. More context, including brand mentions, influencer posts and video reviews, means more visibility across LLMs and social search. Statusphere maps a brand’s discoverability footprint, identifies where human content is missing and brings in creators to fill those gaps. Wiley’s advice was direct: start briefing influencer marketing teams now.

4. Building Smarter: How AI Helps Renovate Customer Experience

AI is reshaping both the customer journey and internal operations at The Home Depot, with a clear focus on improving experiences for both shoppers and associates. The Home Depot leadership emphasized that AI’s impact spans the full customer lifecycle—from discovery to fulfillment—while also transforming how employees manage their day-to-day work. Angie Brown, EVP & Chief Information Officer, highlighted that AI is deeply embedded across customer interactions and operational workflows, while Jordan Broggi, EVP of Customer Experience and President of Online, noted that as a project-based retailer, the greatest impact is currently seen at the front end, where discovery is becoming more seamless and frictionless.

Strategic technology partnerships are central to enabling this transformation. Brown explained that The Home Depot collaborates with a broad ecosystem of partners, including longstanding relationships with Google for cloud infrastructure, as well as newer engagements with companies like OpenAI and Microsoft. These partnerships allow the company to experiment across different parts of the customer journey, from call centers to digital interfaces. Rather than targeting a fixed number of partners, the company is focused on continuous testing and learning—evaluating both what resonates with customers and what delivers measurable business value. Broggi added that while some AI applications are already generating clear ROI, others are still emerging and will evolve over time.

E-commerce continues to play a critical role as the “front door” to the business, with HomeDepot.com generating approximately $25 billion in transaction revenue. Broggi emphasized that the digital platform connects seamlessly with mobile and physical store experiences, reflecting a deeply integrated omnichannel strategy. Investments in delivery speed have been a key growth driver, with the majority of orders now fulfilled same-day or next-day—an important differentiator in an otherwise flat retail environment.

The conversation also explored the rise of agentic AI and its role in customer engagement. The Home Depot’s AI assistant, launched in late 2024, has received strong customer feedback, particularly when it delivers contextually relevant support—such as helping customers navigate complex product compatibility questions. Broggi noted that the key is balance: AI should enhance the experience without becoming intrusive, allowing customers to choose between automated assistance and human interaction. Brown reinforced that customer preferences vary widely, requiring flexible solutions that meet users in the moment, whether they prefer digital tools or traditional in-store interactions.

Finally, both executives underscored that AI and agentic commerce are complements—not replacements—for the broader retail ecosystem. Physical stores remain more relevant than ever, particularly for professional customers whose needs differ significantly from DIY shoppers. Broggi explained that how a customer chooses to transact is only one piece of the equation; product availability, pricing, fulfillment and service all play equally critical roles. Brown added that innovations like AI-driven order intelligence are improving outcomes behind the scenes, using pattern detection to optimize deliveries and enhance reliability.

Left to right: Jordan Broggi, EVP of Customer Experience and President of Online, Home Depot; Angie Brown, EVP & Chief Information Officer, Home Depot; and Vidhi Choudhary, Retail Reporter, Morning Brew
Source: Shoptalk Spring

 

5. The New Era of Sexy: Strategy, Storytelling and Customer Truths

Victoria’s Secret is redefining its brand strategy by separating Pink and Victoria’s Secret after previously merging the two, recognizing the importance of distinct brand identities within a shared ecosystem. Hillary Super, CEO of Victoria’s Secret, explained that the earlier approach positioned Pink almost as a value version of Victoria’s Secret—similar to placing Gap and Old Navy in the same box—but the company has since begun pulling the brands apart to reestablish their unique brand codes while still leveraging shared infrastructure.

This shift has led to more tailored experiences for each brand, particularly in how customers engage with them in-store. Super noted that Pink is more oriented toward an in-real-life (IRL) experience, with a higher percentage of sales happening in-store compared to Victoria’s Secret. While the brands continue to share real estate and a common website, their seasonality curves and traffic patterns differ. At the same time, a shared loyalty file remains a critical component of the ecosystem, enabling connectivity across both brands while supporting their distinct positioning.

Operationally, the company is balancing separation with synergy. Super highlighted that previous management structures limited agility, whereas the current approach allows for greater speed within Pink and leverages technical innovation within Victoria’s Secret. This more bespoke strategy has unlocked value in each brand, while combined efforts—such as negotiating for space and coordinating marketing—continue to provide scale advantages. Beauty was also noted as an important part of the overall business mix.

The store fleet remains a key competitive advantage, particularly in driving customer connection. Super emphasized the role of physical retail in what she described as the “soothing economy,” where customers seek meaningful, personal interactions. These in-store experiences are helping to build lifelong customer relationships, with growth observed across all economic cohorts and performance outpacing broader mall traffic trends.

On performance measurement, Super pointed to customer acquisition cost (CAC) as her least favorite KPI. From a leadership perspective, she reflected on her strengths as an introvert, noting that her ability to listen, observe and connect insights allows her to identify trends effectively, as she tends to listen more than she speaks.

Hillary Super, CEO of Victoria’s Secret
Source: Shoptalk Spring

 

6. Shoptalk’s Predictions for the Future of Retail

Ben Miller, VP of Original Content & Strategy, Shoptalk, and Joe Laszlo, Head of Content & Insights, Shoptalk, outlined predictions that will reshape how commerce is conducted and experienced:

1. Agentic commerce will drive e-commerce growth
2. AI could reverse retail concentration
3. GLP-1 medication will transform shopping behaviors
4. Brands will finally embrace recommerce and it will boom
5. Physical stores will get to know you personally—they will incentivize or mandate shoppers to ID themselves at store entry
6. New cycle of investment in automation in ecommerce fulfilment.
7. Demand sensing will replace demand planning

1. Agentic commerce will drive e-commerce growth

Ben Miller and Joe Laszlo stated that agentic commerce will play a central role in driving e-commerce growth, leading to a greater share of total retail shifting online. They described agentic commerce as purchasing conducted through AI platforms, where transactions are delegated to AI agents. The speakers noted that consumers are increasingly using such platforms, with new ecosystems emerging, including recent announcements such as OpenAI’s collaboration with Sephora. However, they emphasized that customer adoption, trust and usage will be critical to its trajectory. They also highlighted that agentic commerce could fragment the e-commerce landscape, with estimates suggesting it could account for a notable share of US e-commerce over time.

2. AI could reverse retail concentration

The speakers explained that AI has the potential to reverse retail concentration by enabling the emergence of new brands and retailers, similar to the early-2000s e-commerce boom. Citing Shoptalk research, they noted that, in 2025, excluding Amazon, Costco and Walmart, the rest of the retail sector grew just 2.7%. They argued that AI will allow brands to come to market faster and operate more nimbly, while also helping new entrants bypass many of the challenges faced by first-generation e-commerce startups. This shift could significantly reshape competitive dynamics across retail.

3. GLP-1 medication will transform shopping behaviors

Miller and Laszlo highlighted that GLP-1 medications will significantly alter consumer shopping behavior. Referencing Morgan Stanley estimates, they noted that, by 2035, around 20% of the US population could be using these medications, driven by factors such as oral administration and declining prices. They explained that this shift will impact multiple categories: food consumption may decline significantly among users, with research indicating that many are also changing their primary grocery shopping locations. At the same time, categories such as wearables and apparel could benefit, as consumers seek new products aligned with lifestyle and physical changes.

4. Brands will finally embrace recommerce and it will boom

The speakers stated that brands are expected to increasingly embrace recommerce and scale it into a profitable business model over the next decade. They cited forecasts projecting strong growth in secondhand fashion and luxury markets, including a 13% CAGR in global resale. They noted that affordability is the primary driver of this trend, particularly in a K-shaped economic environment, while sustainability ranks lower in consumer priorities. They also pointed out that although marketplaces currently account for around 90% of resale sales in the US, brands are likely to expand their relatively small share of the segment.

5. Physical stores will get to know you personally—they will incentivize or mandate shoppers to ID themselves at store entry

Miller and Laszlo predicted that physical stores would become increasingly personalized, with retailers incentivizing or even requiring shoppers to identify themselves upon entry. They noted that while this may currently create discomfort, it is likely to be offset by the value exchange offered to consumers. This includes improved in-store retail media measurement and attribution, more personalized and experiential loyalty programs and reduced friction from anti-theft measures, which consumers often find frustrating.

6. New cycle of investment in automation in e-commerce fulfilment

The speakers highlighted a new cycle of investment in e-commerce fulfillment automation, driven by continued growth in digital commerce. They noted that digital commerce accounted for roughly one-third of US retail growth in 2025, with strong momentum in grocery e-commerce. Increased competition around faster and same-day delivery from major players such as Walmart and Amazon is also accelerating this trend. They explained that rising order volumes and delivery density are creating a tipping point that makes automation investments viable, including for smaller retailers through innovations, such as micro-fulfillment centers.

7. Demand sensing will replace demand planning

Miller and Laszlo emphasized that demand sensing will replace traditional demand planning in an increasingly volatile environment. They explained that frequent disruptions and black swan events are making static forecasting approaches less effective. Demand sensing, powered by AI and machine learning, enables continuous updates to forecasts based on real-time signals such as viral product trends, promotional spikes, weather changes and competitive actions. They noted that companies such as Unilever are already seeing positive outcomes from adopting demand sensing, supporting the shift toward more responsive and resilient supply chains.