Conversational Commerce Insights

🛍️ What an exciting start to 2025! With OpenAI making SearchGPT available in their free ChatGPT interface, we're set to see a fascinating evolution in how people shop online. We can expect queries will get more conversational as chat becomes an entry point for search. Our BrightEdge Generative Parser™ has uncovered some compelling patterns in how AI platforms are processing shopping queries. 📊 As these AI engines' capability to help shoppers evolves, we're seeing them increasingly rely on expert review sources and specialized retailers. For example, in Google's AI Overview results, sites like ConsumerReports.org saw a 145% increase in citations for e-commerce queries since November, while specialized retailers saw a 178% boost in expert citations. Let's look at an example of a conversational query: "What are some good gas-powered RC cars and where can I buy one?" Just a few weeks ago, Google was not generating an AIO for a query like this! The response sophistication is remarkable: 🔹 Google AI Overview: Rich product cards with filtering + pricing, pulling from specialized hobby retailers 🔹 ChatGPT Search: Detailed product info and local buying options (including phone and addresses of hobby shops close by!) + expert technical guidance 🔹 Perplexity: Streamlined purchase flow with direct "Visit Site" options + comparative features What's fascinating is how each platform balances: ✨ Expert reviews from trusted domains ✨ Specialized retailer data ✨ Local availability information Our Parser is detecting two key trends that are also happening since November: 1.      Product comparison and review site citations (TechGearLab etc) up 147% 2.      Technical advice site citations (Tom’s Guide etc) saw a 311% increase as platforms emphasize expert content. ⚠️ Looking ahead: The competition is driving innovation - and with search functionality now embedded in chat interfaces, shopping queries are becoming more conversational and complex. With review citations on the rise and technical advice citations up since November, AI platforms are evolving from simple product listings into sophisticated shopping assistants that can handle multi-part questions like "What's a good RC car for a beginner and where can I buy it locally?" 🎯 The big question: Is your e-commerce content ready for this new era of AI-driven shopping? Want to see how AI is tackling conversational queries in your market? Let's connect! #AI #Ecommerce #DigitalTransformation #RetailTech

As an analyst, I was intrigued to read an article about Instacart's innovative "Ask Instacart" feature integrating chatbots and chatgpt, allowing customers to create and refine shopping lists by asking questions like, 'What is a healthy lunch option for my kids?' Ask Instacart then provides potential options based on user's past buying habits and provides recipes and a shopping list once users have selected the option they want to try! This tool not only provides a personalized shopping experience but also offers a gold mine of customer insights that can inform various aspects of a business strategy. Here's what I inferred as an analyst : 1️⃣ Customer Preferences Uncovered: By analyzing the questions and options selected, we can understand what products, recipes, and meal ideas resonate with different customer segments, enabling better product assortment and personalized marketing. 2️⃣ Personalization Opportunities: The tool leverages past buying habits to make recommendations, presenting opportunities to tailor the shopping experience based on individual preferences. 3️⃣ Trend Identification: Tracking the types of questions and preferences expressed through the tool can help identify emerging trends in areas like healthy eating, dietary restrictions, or cuisine preferences, allowing businesses to stay ahead of the curve. 4️⃣ Shopping List Insights: Analyzing the generated shopping lists can reveal common item combinations, complementary products, and opportunities for bundle deals or cross-selling recommendations. 5️⃣ Recipe and Meal Planning: The tool's integration with recipes and meal planning provides valuable insights into customers' cooking habits, preferred ingredients, and meal types, informing content creation and potential partnerships. The "Ask Instacart" tool is a prime example of how innovative technologies can not only enhance the customer experience but also generate valuable data-driven insights that can drive strategic business decisions. A great way to extract meaningful insights from such data sources and translate them into actionable strategies that create value for customers and businesses alike. Article to refer : https://lnkd.in/gAW4A2db #DataAnalytics #CustomerInsights #Innovation #ECommerce #GroceryRetail

Every delightful customer interaction begins with the marketer, and it can only be as powerful as the #CRM and #metadata underpinning it. With agents supporting them at every step of the customer journey creation process, marketers and #customerengagement teams can now create superior experiences shaped by intelligent and emotionally resonant conversations. At a cognitive level, the human brain no longer perceives AI as a “chatbot.” It perceives a relationship. This emotional shift fundamentally changes how consumers relate to brands, fostering deeper loyalty and trust. When customers interact with agents in a way that feels natural, their engagement deepens. The implications go far beyond engagement. Every AI-driven interaction generates a wealth of contextual data, far richer than what brands could ever collect from a single web form or survey. In one conversation, an agent can gather insights about a customer’s preferences, behaviors, and intent, building a more complete, dynamic customer profile. This continuous intelligence loop allows brands to maximize the value of every interaction. Let’s bring this to life with an example... Imagine Melanie, one of your many potential customers. She’s been thinking about joining Posh Fitness, a popular gym chain in her city. Instead of filling out a form, she decides to engage with the agent on their website. As they chat, it quickly feels more like a friendly exchange than a transaction. Melanie shares her fitness goals, whether she wants to lose weight, gain muscle, or improve flexibility, and the agent listens closely, asking the right questions to understand her needs and intent. The agent gathers valuable insights through this conversation that a simple web form could never capture. Melanie mentions her dietary restrictions, her preference for a supportive personal trainer style, and that she loves outdoor workouts but needs a flexible schedule due to her busy life. In just a few minutes, the agent collects a wealth of data about Melanie: her goals, preferences, and availability—all essential to crafting a personalized experience. And because the conversation feels human-like and emotionally resonant, it creates an immediate connection to Posh Fitness. By collecting this richer data early in the relationship, Posh Fitness can offer tailored recommendations and build Melanie’s loyalty well before she signs up. This isn’t just about closing a sale. It’s about building trust and delivering personalized experiences that evoke emotions and feel deeply human. Brands that will thrive in the era of #Agentic #AI are those that recognize the shift from transactional interactions to relationship-driven engagement. This isn’t just about personalization; it’s about creating experiences and dialogues that feel alive—where AI and marketers co-create journeys that adapt in real time, amplifying the impact of every customer moment.

A decade ago, e-commerce disrupted traditional retail by capturing the customer relationship. Local shops sold goods, but platforms like Amazon and Meesho understood consumer preferences and dominated the buying journey. As the user experience shifts upstream, moving away from storefronts toward intelligent agents that act on our behalf, e-commerce companies will soon serve as suppliers to these AI agents, just as retailers became suppliers to e-commerce platforms. I explore: 1. How the search and discovery of information has already shifted to conversational interfaces. 2. Why shopping, travel, and home service apps face imminent disruption and risk becoming irrelevant. 3. Key things these platforms must prioritize to remain relevant. If you work at an e-commerce company, what are you doing to adapt to this shift?

WHAT'S GOT MY ATTENTION TODAY 🤔 Something BIG just happened in commerce OpenAI has launched Instant Checkout in ChatGPT in the US, which means consumers can now find and buy products without ever leaving the conversation. - Shopify merchants are among the first to plug into this feature (US) - This isn’t just a shiny new button - it’s a paradigm shift in discovery and conversion. The search box, the website, even the app are no longer the only front doors to commerce. Conversation itself becomes the store. Why this matters 🧐 - Friction is falling away: Going from “tell me about this product” to “I’ve just bought it” is now seconds, not minutes. That’s convenience redefined. - AI agents as storefronts: ChatGPT isn’t just answering questions, it’s selling, recommending, and transacting. This puts brands into the dialogue, not just the marketplace. - A level playing field with new rules: OpenAI says rankings won’t be pay-to-play. Factors like price, quality, availability, and customer experience will matter most. The Agentic Commerce Protocol they’re co-developing with Stripe is open-source, meaning innovation won’t be walled off. - First movers will learn fastest: Whether you’re a global brand or an indie maker, this shift favours those who experiment early. It’s less about the platform you’re on and more about whether you’re ready to meet your customers in this new space. My hot take 🔥 We’ve been talking about “conversational commerce” for a decade. Today, it actually went live. This isn’t the death of websites or apps, but it’s the birth of something additive and potentially transformative. Brands that treat AI-driven discovery as core infrastructure (not just a side hustle) will be better placed as consumer habits change. The exciting part? The field is wide open. 🔍 Question for you (apparently I need to "interact more": What’s the first product or brand you’d expect to see (or would want to buy) directly inside ChatGPT?

Your Next Sales Channel? A Chat Interface. Shopify + OpenAI are building commerce into conversation. OpenAI and Shopify are quietly building something big. ChatGPT is testing native in-chat shopping powered by Shopify—and it’s a glimpse at where e-commerce is headed. You ask ChatGPT: > “Find me eco-friendly running shoes under $100”  … It serves up options, reviews, and a buy button—all in the chat. No tabs, no search, no clicking around. Just straight to checkout. - 𝗙𝗼𝗿 𝗱𝗲𝘃𝘀 & 𝗺𝗲𝗿𝗰𝗵𝗮𝗻𝘁𝘀: One integration (ChatGPT API + Shopify) unlocks a massive new touchpoint—no need to rework your front end or build custom widgets.  - 𝗙𝗼𝗿 𝘀𝗵𝗼𝗽𝗽𝗲𝗿𝘀: Instant, conversational UX replaces clunky menus and filters. Personalization will be ingrained in the experience. - 𝗙𝗼𝗿 𝘁𝗵𝗲 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺: Storefronts become optional; commerce lives wherever your users already hang out.  I’m especially curious how this will reshape themes and headless setups. ❓ Will we see new Liquid tags like {% chat_buy %}? ❓ How do we handle inventory sync & coupon codes in-chat?  ❓ What's the future look like for developers and designers of Shopify themes? If you’re building on Shopify or playing with the OpenAI API, now’s the time to experiment. Imagine your customers checking out without ever leaving Slack, WhatsApp, or your own React app. Source: https://lnkd.in/ge5FGMba

I’ve said this before: The next era of commerce won’t start with a cart. It’ll start with a question. And that’s becoming more true with every step the industry takes! The latest example: Perplexity’s integration with PayPal and Venmo is a clear marker of what’s next. Agentic commerce, where AI doesn’t just assist; it acts. You search. The agent finds. It books. Buys. Executes. No plugins. No handoffs. No checkouts. Just: intent to outcome! This goes far beyond conversational UX. It’s transactional AI, baked directly into the discovery experience. What stood out to me isn’t just the elegance of the interaction. It’s the broader implications for commerce infrastructure at scale: 🌍 A global payment layer (PayPal) fused with a universal information interface (Perplexity) 🧠 Decision-making collapsing into a single, intelligent step 🛒 Conversion happening at the moment of curiosity, not at the end of a funnel This isn’t AI helping people shop. Its agents executing commerce with precision and trust. We’re witnessing the early shape of a model that: • Starts with intent • Ends with fulfillment • And removes nearly everything in between Imagine a shopper asking: “What’s the best hiking gear for next weekend?” …and their order is already on the way. That’s not the future. That’s the next quarter. One to watch. And one to build for. How are you preparing for this shift? #AI #AgenticCommerce #ConversationalCommerce #EcommerceInnovation #Leadership #PayPal #PerplexityAI #FutureOfCommerce #Fintech #DigitalTransformation https://lnkd.in/gHa6DQCW

Most of you know me as the “rug guy” on LinkedIn. Guys, I want to start talking about something bigger—because I think this is going to be the next real shift in commerce. Commerce is getting a new addition. For years, e-commerce has felt flat: if you look at Amazon today versus Amazon 10 years ago, it’s not drastically different. The game started with eBay as the main marketplace and now every retailer plays that game somehow. Over time, things got more advanced, but the core model stayed the same. Now the biggest change is coming. AI-powered agents—what people are calling “agentic commerce”—are about to rewrite how buyers and sellers connect online. 1. What Is Agentic Commerce? Instead of typing keywords, you’ll have a conversational AI “shopper” that: Hears your needs in plain language (“Find me an sofa for under $1000 that looks English Antique”), Compares prices across multiple retailers in real time, and even negotiates or applies coupons for you, Learns your style preferences—so next time, it already knows you love neutral palettes for coastal homes. 2. Why It Matters Now Choice Overload: We’re drowning in SKUs. AI agents will cut through the noise and hand you exactly what you want—often before you realize it. Retailers Risk Losing Shelf Space: If your product doesn’t land in the AI’s “recommend list,” it’s as if you didn’t exist. Traditional SEO and PPC may no longer be enough. Personalization = Table Stakes: Brands have to move from generic “recommended” widgets to genuinely conversational, data-driven experiences. Quick Takeaway: Agentic commerce isn’t a buzzword—it’s a fundamental shift in the retail value chain, from discovery to fulfillment. How would you feel about “handing off” your next home furnishing—or any purchase—to an AI agent? Does your team already experiment with chat-based selling? I’d love to know—drop a comment below.

Most businesses treat conversations like a cost center. In most US and Western companies, the assumption has been simple: - Support and sales conversations are expensive. - They require headcount. - They don’t scale. 📉 In home services, 27% of inbound calls go unanswered. Each one could be worth ~$1,200. 🏢 In property management, 61% of leasing calls are missed, costing $43/unit/day in vacancy. 💬 60% of consumers would switch salons just to book by text. But that’s starting to change. In APAC, it’s clear how different this can look. A huge share of commerce flows through messaging apps. Conversations are a revenue engine and messaging apps are the storefront. Businesses employ [human] agents to convert, retain, and upsell through chat—because the economics work. APAC alone accounts for 84% of the world’s chat-based commerce volume. In the West, where labor is more expensive, we tried to escape this cost by deflecting: chatbots, FAQs, portals. But when you treat conversations as a cost, you miss their potential. Every message is an opportunity to: - Convert a prospect - Retain a customer - Increase LTV That kind of personalized attention used to be impossible. It was too costly and too complex. But with AI, every business can now offer personalized, instant, high-quality service at scale. Every customer can interact with a personal [AI] agent that knows their history, preferences, and needs. An agent who responds instantly, understands complex needs, and steers every interaction toward business outcomes. The same 1:1 messaging that’s always been too costly… is now the best growth channel.

Across retail, travel, gaming, B2B, food and beverage, and more, we’ve seen the same pattern emerge: Search is often treated like a one-and-done interaction. But shoppers aren’t passive. They’re dynamic, curious, and full of intent, and their behavior reflects that. Our conversational research report found 34.7% of shoppers now use questions when they search an ecommerce site, and 61.3% are interested in a conversational search bar. At Bloomreach, we’ve seen what happens when you design for two-way interaction, not just one-sided answers. For example, one of our retail customers using Bloomreach Clarity, our conversational AI shopping agent, saw a 28% drop in exit rate by showing up exactly when shoppers needed to rethink their path to purchase. Optimizing for the first query is table stakes. The real opportunity lies in the conversation that comes next. Check out the research report below.