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Online shopping changing general merchandise retail

This research explores how general merchandise retail is changing due to online shopping. It will examine shifts in shopping behavior, retail operations, and competitive dynamics driven by e-commerce.

Last updated May 21, 2026 04:02

Intelligence Brief

The current state and what matters now

Actors

The field is still led by Amazon, Walmart, Target, Costco, and a long tail of marketplace sellers, category specialists, and private-label operators. The actor set is widening further: AI shopping assistants, search and browser agents, retail media networks, commerce infrastructure vendors, and subscription membership ecosystems now shape discovery and conversion. Amazon is increasingly acting as both retailer and shopping interface, while also routing shoppers to other stores when its own catalog is not the best match. Walmart is using marketplace assortment, unified app experiences, and AI integrations to extend general merchandise online. Target is formalizing membership, same-day delivery, creator commerce, and store-based fulfillment as an integrated operating layer. Google is becoming a major upstream commerce actor by embedding agentic shopping into Search, Gemini, YouTube, and Gmail. Stores, clubs, and value chains matter more because they are blending assortment, fulfillment, and digital merchandising into one system.

Moves

  • Delegated shopping is moving from novelty to utility: assistants can recommend products, compare options, track prices, and increasingly complete purchases.
  • Auto-buy and price-triggered execution are emerging, with shoppers setting conditions and letting systems purchase when thresholds are met.
  • Cross-merchant routing is becoming more explicit, with Amazon and Google-style surfaces surfacing products outside their native catalog and sending shoppers to merchant sites or assisted checkout flows.
  • Shared cart infrastructure is emerging across surfaces, so a shopper can collect items in one place and complete checkout later in another.
  • Agent-led discovery is accelerating as retailers test natural-language search, conversational assistants, and AI-guided decision support.
  • Structured product feeds are becoming core infrastructure for AI shopping, because assistants depend on clean metadata, pricing, and inventory.
  • Membership-led convenience is growing, with delivery bundles and partner access turning retention into a system rather than a perk.
  • Store fulfillment is expanding, with stores increasingly serving shipped online orders, same-day delivery, pickup, and returns demand.
  • Retail media integration is deepening, with on-site, in-store, and offsite media tied more tightly to sales outcomes and verified identity.

Leverage

Advantage now comes from controlling the full commerce loop: discovery, trust, assortment, fulfillment, and monetization. The strongest players combine traffic, first-party data, inventory density, and delivery reliability. Physical stores still matter when they reduce last-mile cost, support returns, and improve immediacy. The newest leverage point is AI-mediated intent capture: whoever influences the assistant, ranking, or recommendation layer can shape demand before the shopper reaches a retailer’s website. Control over product feeds, identity linking, catalog quality, and inventory accuracy is now a source of bargaining power. Retailers that expose clean inventory and pricing data across channels gain an edge because digital convenience is now a core battleground even in value-oriented general merchandise. Cross-service identity graphs, such as linking shopping to media behavior, are becoming a new personalization asset. A further advantage is emerging in interface control: retailers that can separate discovery from checkout without losing the customer can monetize routing, not just transactions.

Constraints

  • Thin margins still limit how much price competition and free shipping can be absorbed.
  • Fulfillment costs remain structurally high for bulky, low-value, or high-return general merchandise.
  • Product-data quality is now a hard constraint: if catalogs, attributes, pricing, or availability data are wrong, AI search and marketplace conversion degrade quickly.
  • AI adoption is outpacing execution, creating a gap between strategic intent and operational readiness.
  • Merchant defenses against bots remain a friction point, because retailers must distinguish helpful agents from malicious automation.
  • Attribution conflicts are intensifying as media teams, creators, merchants, and store operators optimize for different outcomes.
  • Checkout fragmentation persists: shoppers may discover products in one interface, compare in another, and complete payment on a different surface.
  • Platform control disputes are rising as retailers block or limit shopping bots that threaten traffic, pricing power, or customer ownership.
  • Attention is more distributed, so retailers must win earlier research moments without losing efficiency at the point of purchase.

Success Metrics

Success is increasingly measured by profitable digital penetration, not just online sales growth. Key metrics include gross margin after fulfillment, repeat purchase rate, order frequency, basket size, conversion rate, and customer lifetime value. Retailers also track on-time delivery, pickup adoption, return rates, inventory turns, and retail media revenue. In the AI era, new metrics matter too: assisted conversion rate, recommendation accuracy, search-to-purchase time, the share of traffic influenced by agents, the percentage of orders completed through conversational or delegated surfaces, and the share of purchases triggered by price alerts or auto-buy rules. For membership-led commerce, retailers are watching subscription attach rate, partner usage, and retention lift. For marketplaces, seller quality, take rate, API integration depth, and trust signals remain central. For grocery and essentials, replenishment frequency and share of household spend are becoming more important. Awareness-stage engagement and early-funnel community research are also becoming measurable inputs to conversion.

Underlying Shift

The deeper shift is from a store-centric distribution model to a data- and AI-orchestrated commerce system. Online shopping has already changed general merchandise retail by making assortment, pricing, logistics, and media continuously adjustable. The new phase goes further: shopping is becoming mediated by assistants, recommendation engines, membership ecosystems, creator networks, and unified operating layers that blur the line between browsing, buying, and fulfillment. The retailer is less a shelf owner and more a platform operator coordinating demand across digital interfaces, stores, and delivery networks. In this model, the store is a node, the app is a control surface, and AI is becoming the front door and, increasingly, the checkout layer. Commerce is also becoming more interoperable, with merchant data and transaction flows exposed to agents through shared protocols rather than only proprietary retailer stacks. The interface is shifting from keyword search to intent interpretation, and now also from direct purchase to routed purchase and delegated execution.

Current Phase

The market is in a late adoption, early transformation phase. Omnichannel is no longer novel; it is table stakes. The next competitive wave is about who can operationalize unified commerce, agentic shopping, and marketplace-led assortment without destroying margin or trust. The profit pool is still contested among retailers, marketplaces, brands, creators, and retail media businesses, but the battle is shifting toward who owns the customer interface, the AI layer, and the transaction rules. The winners will be those that turn complexity into a simpler customer experience while also reducing internal friction and improving inventory truth. The evidence now suggests online shopping is not just supplementing general merchandise retail; it is increasingly setting the operating logic for it. The newest phase is a contest over who owns the first question, not just the final click.

What to Watch

  • Agentic and conversational commerce adoption, especially whether AI assistants become a meaningful source of traffic and conversion.
  • Auto-buy and price-alert usage, including whether shoppers trust delegated purchase execution for repeatable categories.
  • Merchant acceptance of AI checkout, including whether retailers monetize assistant traffic or keep blocking it as bot risk.
  • Universal cart and cross-surface checkout, especially whether carts can persist across search, video, email, and chat.
  • Membership ecosystem growth, especially whether delivery bundles and partner access improve retention and spend.
  • Marketplace operating models, especially whether marketplace becomes a core assortment and growth system rather than a side channel.
  • Unified commerce execution, especially whether retailers can truly collapse channel silos for customers and operations.
  • Retail media integration, including whether on-site, in-store, and offsite media become one measurable system.
  • Inventory and catalog accuracy, since AI ordering and availability tools only work if product data stays clean.
  • Upstream research behavior, including whether community platforms and search agents become standard first stops before retailer search.

Latest Signals

Events and actions shaping the domain

Walmart says marketplace is now mostly general merchandise

Full signal summary: Walmart’s prepared remarks say more than two-thirds of its marketplace assortment is general merchandise. That suggests online general merchandise is increasingly being routed through marketplace infrastructure instead of store inventory alone.

Amazon Business adds fresh groceries to one-cart buying

Full signal summary: Amazon Business said customers in over 2,300 cities and towns can now add fresh, perishable groceries alongside millions of business essentials in a single cart with same-day delivery. That expands online retail from discrete replenishment into bundled cross-category purchasing.

Google opens agentic carting across major retailers

Full signal summary: Google said its new Universal Cart can work across merchants including Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair, and Shopify brands, while the brand remains the merchant of record. That signals shopping is moving toward a cross-retailer transaction layer rather than a single-store checkout flow.

Google ties shopping to AI agents and shared protocols

Full signal summary: Google said it is building the foundation for agentic commerce using Universal Commerce Protocol and payments infrastructure for seamless agentic checkout. That indicates a structural shift toward standardized machine-to-machine shopping infrastructure.

Amazon personalizes shopping around editable consumer profiles

Full signal summary: Amazon said customers can now view and edit the personal details that shape recommendations, and that shopping is personalized through purchase history, Alexa conversations, reviews, Lists, and searches. That signals a deeper shift toward identity-based merchandising and recommendation control.

Dominant Patterns

High-density signal formations shaping the current domain landscape

Loading cluster map

Aggregating signals by recency and strength

Editable Personalized Shopping Profiles
Bundled Business Grocery Buying
Marketplace General Merchandise Shift
Agentic Commerce Protocols
Cross Retailer Shopping Layer

Weak Signals, Rising Patterns

Less visible signal formations that may gain significance over time

Loading cluster map

Aggregating signals by recency and strength

Cross Retailer Shopping Layer
Agentic Commerce Protocols
Marketplace General Merchandise Shift
Bundled Business Grocery Buying
Editable Personalized Shopping Profiles

Analysis

Interpretation of what’s changing

Retail Is Turning Into a Policy Layer for Agents

Agentic commerce is pushing retail platforms up the stack. The store is no longer just a place to search, compare, and check out; it is becoming the system that tells an agent who the shopper is, what they usually want, what they can afford, and when they...

Full analysis summary: Agentic commerce is pushing retail platforms up the stack. The store is no longer just a place to search, compare, and check out; it is becoming the system that tells an agent who the shopper is, what they usually want, what they can afford, and when they should buy . That is the real shift hiding inside personalized recommendations, price-history tools, Universal Cart, and agentic checkout protocols. Once shopping is delegated, the key object is no longer the product page. It is the machine-readable shopper profile —purchase history, preferences, constraints, trigger rules, and permission settings. In other words, retail starts to look less like a shelf and more like an operating system with access controls. Amazon already exposes pieces of this logic through personal details that shape recommendations, Rufus price tracking, and Auto Buy. Google is building a cross-surface cart and payment layer that can follow the user across Search, Gemini, YouTube, and Gmail. Both are converging on the same prize: not just facilitating transactions, but governing the decision policy that precedes them. The implication is uncomfortable for retailers that treat personalization as a marketing layer. If agents become the primary buyers, then the platform that best standardizes identity and consent may control conversion more than the platform with the best assortment. The moat shifts from catalog depth to decision authority . There is a catch. This only becomes durable if shoppers trust the profile layer enough to let it act on their behalf, and if merchants are willing to expose enough data for agents to make useful decisions. Fragmented permissions, privacy concerns, and inconsistent product data could slow the transition. But if the rails hold, the competitive battlefield moves upstream: whoever owns the shopper model owns the transaction outcome.

When the Cart Becomes the Control Surface

Retail media is starting to look less like advertising and more like a thermostat: the same system that nudges demand can now also turn the purchase dial. That is the real shift behind agentic commerce. If a shopper can ask an assistant, set a price rule,...

Full analysis summary: Retail media is starting to look less like advertising and more like a thermostat: the same system that nudges demand can now also turn the purchase dial. That is the real shift behind agentic commerce. If a shopper can ask an assistant, set a price rule, and let the system auto-buy when conditions are met, then the old separation between media, merchandising, and checkout starts to break down. Amazon’s price history and Auto Buy features make this concrete. Google’s Universal Cart pushes the same logic across Search, Gemini, YouTube, and Gmail. Microsoft is exposing catalog, pricing, promotions, inventory, carts, and fulfillment as callable commerce functions. These are not just convenience upgrades. They are signs that shopping is becoming a closed loop: discovery feeds selection, selection feeds execution, execution feeds back into the next optimization cycle. That changes the measurement problem. Traditional funnel metrics assume a sequence: impression, click, conversion. But if an agent can choose the offer and complete the order without a visible click path, attribution becomes less like reading a receipt and more like debugging a machine. Brands and retailers will care less about traffic volume and more about whether their products, prices, and promotions are legible to the agent at the moment of decision. The implication is uncomfortable for anyone still optimizing retail media as a standalone channel. Media spend, pricing strategy, inventory availability, and promotion design are converging into one control system. The winner may not be the loudest bidder, but the merchant whose offer is easiest for the agent to trust, compare, and execute. There is still a constraint: agentic commerce is unevenly real. It depends on user trust, merchant participation, clean data, and enough inventory and pricing discipline for automation to work. In categories with low repeat purchase or high emotional friction, the funnel may collapse more slowly. But the direction is clear: the path from persuasion to purchase is getting shorter, and the platforms that own that path will own more of the economics around it.

Commerce Is Becoming a Routing Problem

The most important shift in retail is not that platforms want to sell less. It is that they are learning the sale is no longer the only prize. Amazon letting off-Amazon products surface in search, Google building a Universal Cart across its surfaces, and...

Full analysis summary: The most important shift in retail is not that platforms want to sell less. It is that they are learning the sale is no longer the only prize. Amazon letting off-Amazon products surface in search, Google building a Universal Cart across its surfaces, and Walmart leaning into AI-mediated shopping all point to the same re-architecture: the platform is turning into a traffic controller, not just a store. The new asset is the ability to intercept intent early, shape the options, and send the shopper onward. Checkout becomes a handoff, not a moat. That changes the economics of power. If a platform can own the moment a customer asks, “what should I buy?” , it can monetize the decision layer even when another merchant closes the transaction. Think of it less like a mall and more like an airport: the gates matter, but the real leverage sits in the security checkpoint, the signage, and the routing logic that decides where people flow next. The mechanism is simple but consequential. Shopping is becoming more cross-surface and more agentic, so consumers are less attached to any one catalog. The platform that can combine search, context, history, and purchase criteria can preserve trust by showing broader results while still extracting value through referrals, data, and orchestration. In that world, closed inventory is less valuable than being the place where intent gets sorted. There is a catch. Routing only works if users believe the platform is helping them, not merely monetizing their attention. If results feel biased, or if the handoff breaks, the whole system loses credibility. And this shift is uneven: categories with high trust, high substitution, or complex comparison will move first; others may still reward a tighter closed-loop checkout. Still, the strategic implication is clear: the battleground is moving from owning the cart to owning the path to the cart .

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Terminal Overview

Terminal Owner
Whatnot
Core question
Online shopping changing general merchandise retail
Current shift
What’s new: The brief was updated to reflect a sharper shift from online shopping as a browse-and-buy channel to an agentic, delegated commerce layer. I added the latest signals around Amazon’s price-tracking and auto-buy features, Amazon’s routing of shoppers to other stores, Google’s Universal Cart and task-handling agents, Walmart’s marketplace expansion into higher-consideration general merchandise, and the growing role of recurring delivery economics. I also tightened the leverage, constraints, and watchlist around shared shopping infrastructure, cross-surface carting, and AI-mediated discovery because these are now the clearest structural changes in the domain.
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