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PayPal powers Perplexity's Instant Buy, browse realtime catalogs from Ashley, Fabletics, Adorama in chat, checkout with buyer protection.
Launch promo: 50% cashback (up to $50) on your first buy thru Dec 1. Retailers stay in control, you stay chill! Tag your deal hunter pals. đ
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Agentic commerce is the future of retail. Here are five ways you can use this emerging technology to boost your business.
Soon, people won't shop for themselves. Their AI will do it for them.
Not recommend. Not suggest. Actually go out, compare products, check prices, read reviews, and buy on behalf of the shopper.
When that becomes normal, your product isn't competing for a human's attention anymore. It's competing for a machine's trust. And machines don't care about your brand photo or tagline.
 They read your product data and either understand your product clearly enough to recommend it, or move on.
The brands building for this now are going to have a real head start. Here's what to do:
Netcoreâs E-commerce Agentic Trends Report 2026: Why Agentic Commerce Is Becoming the New Operating System for Ecommerce
The Agentic Commerce Shift Report 2026 outlines six execution shifts ecommerce leaders are using to restore conversion and profitability in an increasingly AI-driven landscape. Netcore Report 2026: Rise of Agentic Commerce in Ecommerce After a year of rapid AI adoption and rising digital complexity, ecommerce growth in 2025 exposed a critical reality: increased budgets and more tools did not automatically translate into better outcomes. According to Netcoreâs Agentic Commerce Shift Report 2026, the brands that pulled ahead were those that fixed execution, not those that spent more. The newly released report examines how leading ecommerce teams are re-architecting growth by shifting away from campaign-led, channel-first models toward agentic, always-on execution systems designed around profit outcomes. Drawing on real-world performance patterns from large retailers and digital-first brands, the report identifies six execution shifts that are reshaping ecommerce growth heading into 2026. These shifts focus on how brands capture high-intent signals, orchestrate journeys in real time, and deploy AI agents with shared context and clear ownership. â2025 didnât slow ecommerce; it exposed the limits of old growth models. Funnels multiplied, journeys expanded, and AI scaled, but conversion often didnât follow. The gap wasnât intelligence. It was execution,â the report highlighted. One of the reportâs central findings is the redefinition of discovery itself. Rather than treating discovery as a top-of-funnel activity, high-performing teams are increasingly managing it as a sales function, ensuring that intent signals translate into action through intelligent follow-up, not static campaigns. The report also highlights a shift toward always-on journeys as the default operating model. Instead of episodic campaigns, ecommerce leaders are designing continuous, agent-driven journeys that adapt dynamically to customer behaviour, timing, and context. Another key insight is the emergence of mission-led planning. Rather than starting with channels or formats, leading teams plan around missions such as clearing inventory, improving conversion quality, or increasing lifetime value, then select channels as execution layers. Six E-commerce Trends That Will Define 2026 The Agentic Commerce Shift Report 2026 identifies six structural shifts that explain why ecommerce performance is diverging sharply between leaders and laggards, including Walmart, Restaurant Equippers and Fabindia. Together, they point to a fundamental reset in how digital commerce systems are designed, governed, and measured. 1. Loss-making ecommerce is a systems problem, not a tools problemThe report finds that profitability does not improve by adding more AI features or copilots as seen in early experiments at Walmart. It improves when fragmented tools are collapsed into a small number of governed AI agents operating on shared data, with clear ownership tied to profit outcomes. Leaders who made this shift moved AI from experimentation to accountability. 2. Discovery, not checkout, is where ecommerce leaks the mostContrary to conventional optimisation efforts, the report shows that most revenue loss happens before products are even found. Brands like Restaurant Equippers that turned search and discovery into a guided, conversational experience capable of understanding intent in under a minute saw measurable gains in add-to-cart and conversion without increasing media spend. 3. Fresh markdowns shifted from margin drain to profit leverIn categories with short shelf life, margin erosion was driven less by demand volatility and more by manual guesswork. Retailers such as Morrisons that replaced human-led markdown rounds with governed, store-level AI decision loops transformed pricing from a reactive process into a predictable, controllable profit engine. 4. Language moved from localisation to infrastructureIn growth markets, language emerged as a core operating layer rather than a surface-level translation. The report highlights how Meeshoâs vernacular and voice-first journeys across browsing, payments, and support unlocked higher conversion while reducing cost-to-serve especially among first-time and Tier II+ shoppers. 5. Shopping missions explained behaviour better than channelsChannel-based reporting masked the real drivers of loyalty and basket size. The report shows how organising strategy around shopping missions such as big shop, top-up, and need-it-now enabled retailers to tune assortment, pricing, and journeys more effectively, using channels as execution layers rather than planning anchors. 6. Always-on journeys quietly out-earned campaign calendarsWhile campaigns remained visible and measurable, the report finds that the highest incremental profit came from responding to live intent between campaigns. Brands like Fabindia, Crocs, Andamen and more that treated every browse, cart, and drop-off as recoverable value using AI-driven, triggered journeys outperformed calendar-led approaches without increasing messaging volume. While AI adoption accelerated sharply in 2025, the report stresses that outcomes improve only when AI agents operate on shared context with clear ownership tied to profit metrics. Brands that treated agents as isolated tools saw limited gains; those that embedded them into execution workflows unlocked measurable results. Across multiple use cases, teams applying these execution shifts reported outcomes such as faster revenue acceleration, stronger conversion lift, and improved ROI often without increasing media spend. Unlike trend-heavy or speculative reports, The Agentic Commerce Shift Report 2026 is grounded in execution patterns already in play. It reflects what ecommerce teams learned the hard way in 2025 and how those lessons are shaping operating models for the year ahead. The report is intended for ecommerce CXOs, growth leaders, and digital teams seeking practical guidance on how to adapt to an environment where AI agents, not campaigns, increasingly drive outcomes. Availability The Agentic Commerce Shift Report 2026 is now available to read online. Access the report here: [LINK FOR MORE BLOGS - beyondthepunchlines.com Read the full article
âWhen AI Shopsâ is the new book on agentic commerce by Geoff Gibbins. Photo: Amazon Book Spotlight: The Future of Commerce is Agentic In the time it took you to perfect your marketing fâŚ
Is your marketing funnel becoming obsolete? đ
Geoff Gibbins' new book, When AI Shops is a wake-up call for business leaders on how to market to the "two-sided web," where AI agents are making the purchasing decisions.
Key takeaway: Traditional urgency tactics (like scarcity messaging) can actually hurt your AI recommendations.
Read the full breakdown in my latest blog post.Â
https://saexaminer.org/2026/03/09/when-ai-shops-a-guide-to-marketing-in-the-age-of-ai-agents/
AI Will Buy Your Groceries
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Reinforcement Learning and ReComAI
đ The RL Market: A $194 Billion Powerhouse
Reinforcement Learning isn't just a niche technical strategy; it is a global economic driver.
Market Velocity: The global industry size for Reinforcement Learning has exploded to an estimated $194.9 billion in 2026.
Retail Growth: Retail and e-commerce have become one of the fastest-growing segments for RL, as brands shift from "broad-strokes" marketing to Hyper-Personalization.
The Long Game: Unlike traditional AI, RL is designed to maximize Cumulative Reward. In e-commerce, this means the AI isn't just trying to get one click; it's training itself to increase Customer Lifetime Value (CLV).
đ§ Why Reinforcement Learning is the "Secret Sauce"
Think of traditional recommendation engines as a librarian who suggests books based on what you checked out last year. RL is more like a live conversation with a personal stylist.Traditional AIReinforcement Learning (2026)Reactive: Looks at historical purchase data.Proactive: Learns from real-time "Micro-Signals" (hover time, scroll speed).Static: Updates recommendations periodically.Dynamic: Adjusts the entire storefront layout every few seconds.Short-Sighted: Focuses on the immediate click.Strategic: Optimizes for long-term loyalty and reduced return rates.
đ ď¸ Desti by ReComAI: Agentic RL in Action
Our flagship Shopify AI App, Desti, utilizes Reinforcement Learning from Human Feedback (RLHF) to ensure that every interaction is not just smart, but human-aligned.
Autonomous Carts: Desti learns from user behavior to build recurring orders and suggest bundles that actually make sense, moving beyond the "Customers also bought" clichĂŠ.
Conversational "Oops" Correction: If a customer rejects a suggestion, the RL engine doesn't just stopâit instantly recalibrates. It treats a "No" as a valuable data point to find a better "Yes."
Revenue Operations: By integrating RL with your digital marketing, Desti ensures your ad spend isn't wasted on generic traffic. It helps you identify high-intent shoppers and provides them with a frictionless path to checkout.
đ Join the 2026 Personalization Era
The future of e-commerce belongs to the brands that can "listen" to their customers through data.
Install Desti on Shopify â Experience the industry's most advanced RL-driven chatbot.
Learn more about Destinova AI Labs â Discover our latest breakthroughs in Agentic Commerce.
View Scaling Plans â Ready for a $194 billion market? We have the tools to help you scale.
Reinforcement Learning and ReComAI
In January 2026, the concept of a "static" website is officially a relic of the past. As we move deeper into this year, the e-commerce industry has shifted from simple predictive models to Adaptive Intelligence, powered by Reinforcement Learning (RL).
At ReComAI, weâve moved beyond looking at what customers didâwe focus on what they are doing right now to predict what they will do next. Here is a look at the "RL Revolution" currently reshaping the digital storefront.
đ The RL Market: A $194 Billion Powerhouse
Reinforcement Learning isn't just a niche technical strategy; it is a global economic driver.
Market Velocity: The global industry size for Reinforcement Learning has exploded to an estimated $194.9 billion in 2026.
Retail Growth: Retail and e-commerce have become one of the fastest-growing segments for RL, as brands shift from "broad-strokes" marketing to Hyper-Personalization.
The Long Game: Unlike traditional AI, RL is designed to maximize Cumulative Reward. In e-commerce, this means the AI isn't just trying to get one click; it's training itself to increase Customer Lifetime Value (CLV).
đ§ Why Reinforcement Learning is the "Secret Sauce"
Think of traditional recommendation engines as a librarian who suggests books based on what you checked out last year. RL is more like a live conversation with a personal stylist.Traditional AIReinforcement Learning (2026)Reactive: Looks at historical purchase data.Proactive: Learns from real-time "Micro-Signals" (hover time, scroll speed).Static: Updates recommendations periodically.Dynamic: Adjusts the entire storefront layout every few seconds.Short-Sighted: Focuses on the immediate click.Strategic: Optimizes for long-term loyalty and reduced return rates.
đ ď¸ Desti by ReComAI: Agentic RL in Action
Our flagship Shopify AI App, Desti, utilizes Reinforcement Learning from Human Feedback (RLHF) to ensure that every interaction is not just smart, but human-aligned.
Autonomous Carts: Desti learns from user behavior to build recurring orders and suggest bundles that actually make sense, moving beyond the "Customers also bought" clichĂŠ.
Conversational "Oops" Correction: If a customer rejects a suggestion, the RL engine doesn't just stopâit instantly recalibrates. It treats a "No" as a valuable data point to find a better "Yes."
Revenue Operations: By integrating RL with your digital marketing, Desti ensures your ad spend isn't wasted on generic traffic. It helps you identify high-intent shoppers and provides them with a frictionless path to checkout.
đ Join the 2026 Personalization Era
The future of e-commerce belongs to the brands that can "listen" to their customers through data.
Install Desti on Shopify â Experience the industry's most advanced RL-driven chatbot.
Learn more about Destinova AI Labs â Discover our latest breakthroughs in Agentic Commerce.
View Scaling Plans â Ready for a $194 billion market? We have the tools to help you scale.
Reinforcement Learning and ReComAI
đ The RL Market: A $194 Billion Powerhouse
Reinforcement Learning isn't just a niche technical strategy; it is a global economic driver.
Market Velocity: The global industry size for Reinforcement Learning has exploded to an estimated $194.9 billion in 2026.
Retail Growth: Retail and e-commerce have become one of the fastest-growing segments for RL, as brands shift from "broad-strokes" marketing to Hyper-Personalization.
The Long Game: Unlike traditional AI, RL is designed to maximize Cumulative Reward. In e-commerce, this means the AI isn't just trying to get one click; it's training itself to increase Customer Lifetime Value (CLV).
đ§ Why Reinforcement Learning is the "Secret Sauce"
Think of traditional recommendation engines as a librarian who suggests books based on what you checked out last year. RL is more like a live conversation with a personal stylist.Traditional AIReinforcement Learning (2026)Reactive: Looks at historical purchase data.Proactive: Learns from real-time "Micro-Signals" (hover time, scroll speed).Static: Updates recommendations periodically.Dynamic: Adjusts the entire storefront layout every few seconds.Short-Sighted: Focuses on the immediate click.Strategic: Optimizes for long-term loyalty and reduced return rates.
đ ď¸ Desti by ReComAI: Agentic RL in Action
Our flagship Shopify AI App, Desti, utilizes Reinforcement Learning from Human Feedback (RLHF) to ensure that every interaction is not just smart, but human-aligned.
Autonomous Carts: Desti learns from user behavior to build recurring orders and suggest bundles that actually make sense, moving beyond the "Customers also bought" clichĂŠ.
Conversational "Oops" Correction: If a customer rejects a suggestion, the RL engine doesn't just stopâit instantly recalibrates. It treats a "No" as a valuable data point to find a better "Yes."
Revenue Operations: By integrating RL with your digital marketing, Desti ensures your ad spend isn't wasted on generic traffic. It helps you identify high-intent shoppers and provides them with a frictionless path to checkout.
đ Join the 2026 Personalization Era
The future of e-commerce belongs to the brands that can "listen" to their customers through data.
Install Desti on Shopify â Experience the industry's most advanced RL-driven chatbot.
Learn more about Destinova AI Labs â Discover our latest breakthroughs in Agentic Commerce.
View Scaling Plans â Ready for a $194 billion market? We have the tools to help you scale.
