Automated Suggestions in Shopping Apps

Walmart's "Sparky" Joins the Chat... I have been test-driving Walmart's new AI chat assistant "Sparky" and it marks a fascinating evolution in how we shop online. For years, AI has been confined to the back-end of retail – optimizing inventory, predicting demand, and processing returns. However, today we're witnessing the first genuine consumer-facing AI revolution in e-commerce. 𝐖𝐡𝐚𝐭 𝐈 𝐧𝐨𝐭𝐢𝐜𝐞𝐝 𝐢𝐦𝐦𝐞𝐝𝐢𝐚𝐭𝐞𝐥𝐲: 💬 Sparky operates much like Amazon's Rufus – allowing natural language conversation within your shopping experience 🔍 It helps compare products, synthesize reviews, and make personalized recommendations  💻 You can ask things like "what's the best laptop for an art student?" and get tailored suggestions 🧠 Unlike traditional search, it remembers context and can have a multi-turn conversation 📱 Found in the Walmart app for US customers – look for it in Search Results pages for common items 𝐈𝐬 𝐢𝐭 𝐩𝐞𝐫𝐟𝐞𝐜𝐭? Not yet. The traditional shopping experience is still faster and far superior . But this is clearly where e-commerce is headed – conversation-first discovery that meets you (or your agents) exactly where your shopping journey begins. 𝐓𝐡𝐞 𝐛𝐢𝐠𝐠𝐞𝐫 𝐢𝐦𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐛𝐫𝐚𝐧𝐝𝐬: The large language models powering Sparky fundamentally change how your products are discovered and recommended. Brands now need to ensure these AI systems truly understand their product benefits beyond simple keywords. When consumers ask "which yogurt has the most protein?" or "what moisturizer works best for sensitive skin?", the AI needs to comprehend your product's true value proposition—not just match keywords. The era of SEO-optimized product listings is evolving into one where AI must grasp the complexities, features, and genuine benefits of your brand. Paid Ads? Not 𝐲𝐞𝐭. Right now, these recommendations are purely organic, but make no mistake—Sparky is creating an entirely new platform for future paid recommendations and brand positioning. The brands that understand this shift earliest will have the advantage. Want to try it? Just open the Walmart app, search for a common grocery item, and scroll down to find Sparky.

AI isn't just changing how we work—for years, it has been transforming how customers discover what they want before they even know they want it. And that's through the power of recommendation systems. Let me break it down with a simple example we've all experienced: Open any Amazon product page and you'll see: • "Frequently bought together" • "Customers who viewed this also viewed" • "Recommended based on your browsing history" These aren't just random suggestions. They're calculated revenue multipliers. When a customer lands on a product page, three things typically happen: 1. They buy the original item 2. They buy the original item PLUS recommended items 3. They skip the original item but purchase a recommended alternative Each scenario drives revenue that wouldn't exist without AI-powered recommendations. But here's what most businesses miss: This isn't just for e-commerce. Social platforms use the same concept to increase engagement. When Twitter recommends content that keeps you scrolling longer, they're not just being helpful—they're growing ad impressions and potential click-throughs. The beauty of recommendation systems? There's room for experimentation. Unlike many AI applications where precision is critical, recommendation systems can be effective even when partially accurate. If one of three suggestions resonates, that's still a win. This flexibility creates the perfect playground for companies to: 📌 Test different algorithms 📌 Experiment with recommendation placement 📌 Refine suggestion strategies without disrupting user experience Recommendation engines are a good starting point for AI experimentation—they provide a good combination of impact with minimal disruption risk. Is your business leveraging the power of "you might also like" yet?

Something clicked for me this week… I was exploring how AI is changing how we shop! And I realised we’re entering a completely NEW phase of product discovery 😅 Not through Google. ❌ Not through influencers.❌ But through conversational AI.✅ People aren’t just searching anymore. They’re asking. - “What’s the best shampoo for curly hair?” - “Recommend a vegan face wash under £20.” - “What are some eco-friendly travel kits?” And here’s the part that stopped me: And if your product isn’t showing up in ChatGPT or Gemini? You’re not just missing sales. You’re invisible. I have worked in marketing for decades! I’ve seen trends come and go. But this one feels different. It’s not a “maybe.” It’s happening. Quietly. Rapidly. So I’ve started looking into: - How D2C brands can register their product data into AI models - What tools like ChatGPT actually “see” when people ask for recommendations -And how we, as marketers, can show up where the next-gen consumer is asking This shift reminds me of when brands hesitated to build for mobile. Or ignored TikTok at first. We all know how that played out. 😉 This new wave of AI-first discovery needs a different playbook. 👉🏻👉🏻 So here’s a step by step guide for D2C brands to show up in AI recommendations: 1. Structure your product data using Schema.org / JSON-LD 2. List on Google Shopping, Amazon, and Shopify (these feed AI models) 3. Integrate with ChatGPT plugins like Klarna, Shop.app or use your own GPT 4. Write product content that answers real questions (not just keywords) 5. Test visibility by asking ChatGPT or Gemini to recommend your product category 6. Keep optimizing based on what AI can (and can’t) find If you’re building a brand today especially in D2C, it’s time to think beyond search. The new product shelf is a ‘chat box’ :) If you are a D2C founder or a consumer brand and need more insights on to leverage AI first shopping, comment ‘Product discovery’ and I will share the playbook with you. #AI #D2C #Productdiscovery #Search #Shoppingtrends #consumerbehaviour

ChatGPT just became a storefront On September 29, OpenAI launched Instant Checkout, powered by the Agentic Commerce Protocol. The move turns ChatGPT from a search-and-suggest tool into a place where 700 million weekly users can also buy solutions to their problems, starting with Etsy and expanding to Shopify and Walmart sellers soon. It looks like just another checkout button. But here’s what makes this shift different: ➡️ Purchases now happen entirely inside ChatGPT, so no PDPs, no branded websites. ➡️ Users see only about 8 recommended products in response to a query. ➡️ From fulfillment options to taxes, payment tokens, and order integrity, ChatGPT handles the entire process. The user only selects the product, gives shipping details, and confirms. The AI does the rest. This means that marketplaces or platforms no longer control product discovery. This matters because it reframes how competition works. For two decades, ecommerce has been about building funnels, optimizing PDPs, and fighting for traffic. Now, the funnel may shrink to a single conversation, where visibility depends on whether an AI agent determines that your product is relevant. The risk: fewer options mean fewer chances to be seen. For brands that rely on comparison shopping, PDP storytelling, or retargeting, that surface area will get smaller. The opportunity: if you can align your product content with the way people actually ask questions (and how agents interpret them), you can become one of the 8. For the customer, agentic shopping will create dependency on AI rather than the marketplace or platform where the products are located. If the LLM is learning from the customer's shopping behaviors, the one that aggregates more data will win. I have talked about this in some of my presentations. The AI era is here to SERVE consumers and meet them where they are, the way we discover, compare, and shop will be automated. So what should different operators be thinking? If you’re a brand: double-check product data accuracy, completeness, and context. Agentic commerce will punish sloppy catalog content. If you run ads: prepare for generative engine optimization (GEO), not just search optimization. The prompt is the new keyword. The broader lesson: in this model, discovery and purchase are no longer separate steps. Brands aren’t just competing for clicks, they’re competing to be chosen by an agent that filters the world down to 8 products. That’s not the end of ecommerce funnels, but it may be the start of a new one. #AgenticCommerce #EcommerceStrategy #ChatGPT #RetailInnovation

🚀 An exciting step toward agentic AI in retail. 🛍️ Google’s latest update to its Shopping experience is more than just a cool trick — it’s a glimpse into how AI is evolving from being a passive tool into an active shopping assistant. At I/O 2025, Google announced a suite of new capabilities: • Virtual try-on, using generative AI to realistically render clothes on you using a single photo — no need for 3D scans or complex onboarding. Google’s advanced image generation model accurately simulates how different fabrics drape, fold, and fit on various body types, providing a personalized and realistic preview of how garments would look on you. • AI Mode, powered by Gemini and Google’s Shopping Graph, enabling conversational product discovery — a shift from search to dialogue. • And most notably, agentic checkout — the ability for Google to monitor price drops and complete the purchase for you via Google Pay, all within your set parameters. This marks a shift toward delegated decision-making: where AI not only recommends, but acts on your behalf within defined constraints — one of the core principles of agentic AI. It’s still early days, but this is exactly the kind of applied use case that shows how AI is beginning to operate with more autonomy, context-awareness, and user-aligned intent. Definitely one to watch. 🔗 https://lnkd.in/dTuP2aGh #AI #Ecommerce #VirtualTryOn #GoogleShopping #RetailInnovation #GenerativeAI #UserExperience #TechNews #IOTech2025

I’ve been watching Walmart’s AI moves closely, and this week’s announcement with OpenAI feels like a milestone moment. The way we shop online is fundamentally changing. For 20 years, eCommerce meant typing into a search bar. That is ending. We are now entering an age of AI-first shopping. Today Walmart announced a partnership with OpenAI that lets customers shop directly inside ChatGPT. From meal planning to reordering household essentials, shoppers will be able to chat, discover, and buy without leaving the app. Three things stood out to me, and how business leaders should start to reframe the future: 1. Shift from static browsing to dynamic planning. Instead of waiting for customer intent, build systems that anticipate it. That’s the real promise of AI. AI that learns preferences and patterns can turn repeat purchases into predictive ones. 2. Build for interaction, not transaction. Conversational commerce personalizes the journey. The customer journey is no longer linear; it’s dialogue-driven. Walmart will convert intents like “plan a weeknight taco dinner” into a curated list of items we can buy in one step with Instant Checkout, moving from reactive search to proactive suggestions. Design for trust. 3. As AI handles more of the journey, transparency and data ethics become differentiators. Customers will reward brands that make automation feel human. It’s time to once again redefine what a “storefront” means. AI-first shopping isn’t about selling faster; it’s about serving smarter. How will your organization make that shift? Read the full announcement from Walmart in the comments.