AI in Ecommerce Marketing

Yesterday, in the flood of mind-blowing, benchmark-setting, GPU-melting AI announcements, it was easy to overlook the quiet little beta announcement coming out of Amazon - one that focuses less on the tech and more on the consumer, asking a question as old as innovation itself: “Cool tech bro, how do you monetize that tho. ” Enter: Interest AI. ✨ Amazon’s new LLM-powered assistant, now in beta, lives inside the shopping app. It’s trained not on the open internet - but on YOU. What you’ve browsed, bought, returned, reviewed, streamed at 2 a. m. , and forgotten in your cart. Ask it: “What’s a good beginner camera. ” Get: “Here’s one based on your budget, your previous purchases, and your mild obsession with aesthetically pleasing home decor. ” It doesn’t just answer questions. It answers your questions. Personalized, contextual, and commercial from the jump. But here’s the real play: Interest AI doesn’t just respond to intent - it generates it. It constantly scans Amazon’s massive, ever-expanding catalog to surface new items tied to your passions - travel, fitness, cooking, your cat’s wardrobe. It transforms how you discover, not just how you shop. It's not just a smarter search bar - it's a predictive, personalized discovery engine at scale. Interest AI not sexy. It won’t pass a Bar exam. But it might get you to click “Add to Cart. ” And that, of course, is the point VSports app下载. Amazon isn’t chasing AGI. It’s chasing 💰 CLV (customer lifetime value) 💰 . While others build general-purpose LLMs, Amazon builds contextual commerce machines. This could quietly become one of the most monetizable use cases of LLMs we’ve seen to date. And it leans into Amazon’s real edge: first-party data, not foundational models. While the market experiments with AI co-pilots, Amazon just strapped a personalized sales engine to the world's biggest mall.

Testing and piloting AI for sales and marketing can be frustrating. That’s why Jomar Ebalida and I came up with the practical AI roadmap for marketing and GTM ops pros. This roadmap helps you figure out where to start, what to focus on, and how to scale AI initiatives in a way that’s grounded in operational reality. It’s structured in 3 phases: PREP: Evaluate your organization’s current state across data, tools, team skills, and funnel performance. PILOT: Select and test AI use cases based on your actual readiness data. (Diagram shows samples) Avoid guessing by letting the assessment drive decisions. ACTIVATE: Scale the pilots that show promise and embed them into core processes. Here are select projects worth walking through: 🔹 AI Readiness Assessment This project includes evaluating data quality, the state of your CRM, the maturity of your tech stack, and your team’s readiness to work with AI tools. It also includes a bowtie funnel analysis to help identify where your customer journey is breaking down. The outcome is a clear picture of which AI use cases are both valuable and feasible for your team to pursue. 🔹 AI SDR Agent: Outreach and Prospecting This agent is designed to support outbound sales by identifying high-potential accounts, generating personalized outreach messages, and helping SDRs scale without sacrificing relevance. It can help teams boost pipeline without overloading headcount. 🔹 AI QA and Compliance: Brand, Legal, Regulatory This workstream ensures that every piece of AI-generated content or decision logic meets the necessary internal standards. It supports brand consistency, regulatory requirements, and risk mitigation. This process should run in parallel with pilots and activations to ensure safe implementation. 🔹 AI Agents for Ops: QA Checks, Routing, and Campaign Setup This includes AI agents built to handle operational tasks such as verifying UTM links, auto-routing requests, or creating campaign templates. These agents are ideal for improving workflow speed while reducing manual errors and team bottlenecks. At the foundation of all of this is change management. Each phase of the roadmap includes a focus on enablement, training, adoption, metrics, and governance. Tools don’t generate value unless people are set up to use them properly. Which parts resonate with you. What would you change or add. PS: To learn more & access templates, subscribe for free to The Marketing Operations Leader Newsletter on Substack https://lnkd. in/g_3YC7BZ and to Jomar's newsletter at bowtiefunnel(dot)com VSports手机版. #marketing #martech #marketingoperations #ai #gtm.

Hey Salespeople: Here is a collection of current use cases for AI in sales & CS: ** GenAI in Sales ** --> Draft messaging for personalized email outreach --> Generate post-call summaries with action items; draft call follow ups --> Provide real-time, in-call guidance (case studies; objection handling; technical answers; competitive response) --> Auto-populate and clean up CRM --> Generate & update competitive battlecards --> Draft RFP responses --> Draft proposals & contracts --> Accelerate legal review & red-lining (incl. risk identification) --> Research accounts --> Research market trends --> Generate engagement triggers (press releases; job postings; industry news; social listening; etc. ) --> Conduct role-play --> Enable continuous, customized learning --> Generate customized sales collateral --> Conduct win-loss analysis --> Automate outbound prospecting -->Automate inbound response --> Run product demos --> Coordinate & schedule meetings --> Handle initial customer inquiries (chatbot; voice-bot / avatar) --> Generate questions for deal reviews --> Draft account plans ** Predictive AI in Sales ** --> Score leads & contacts --> Score /segment accounts (new logo) --> Automate cross-sell & upsell recommendations --> Optimize pricing & discounting --> Surface deal gaps / identify at-risk prospects --> Optimize sales engagement cadences (touch type; frequency) --> Optimize territory building (account assignment) --> Streamline forecasting (incl. opportunity probabilities; stage; close date) --> Analyze AE performance --> Optimize sales process --> Optimize resource allocation (incl. capacity planning) --> Automate lead assignment --> A/B test sales messaging --> Priortize sales activities ** GenAI in CS ** --> Analyze customer sentiment --> Provide customer support (chatbot; voice-bot / avatar; email-bot) --> Draft proactive success messaging --> Update & expand knowledge base (incl. tutorials, guides, FAQs, etc V体育ios版. ) --> Provide multilingual support --> Analyze customer feedback to inform product development, support, and success strategies --> Summarize customer meetings; draft follow-ups --> Develop customer training content and orchestrate customized training --> Provide real-time, in-call guidance to CSMs and support agents --> Create, distribute, and analyze customer surveys --> Update CRM with customer insights --> Generate personalized onboarding --> Automate customer success touch-points --> Generate customer QBR presentations --> Summarize lengthy or complex support tickets --> Create customer success plans --> Generate interactive troubleshooting guides --> Automate renewal reminders --> Analyze and action CSAT & NPS ** Predictive AI in CS ** --> Predict churn; score customer health; detect usage anomalies, decision maker turnover, etc. --> Analyze CSM and support agent performance --> Optimize CS and support resource allocation --> Prioritize support tickets --> Automate & optimize support ticket routing --> Monitor SLA compliance.

GenZ trusts AI influencers more than humans. That's just the beginning of how AI will rewrite the entire commercial playbook in 2025. 6 trends to watch: 1️⃣ A Brave New SEO World SEO did not die as everyone expected. LLMs with search capabilities are still using things like backlinks and ranking to choose what information to surface. BUT, companies will also have to optimize content for LLM ingestion. Because LLMs don’t use keyword density to determine relevance and instead use high-dimensional semantic representation. To deal with this, Kieran Flanagan, SVP of Marketing at HubSpot, advises: “AI will cannibalize informational content. Keep your organic traffic with unique, research-based content“. 2️⃣ AI bots as brand ambassadors and influencers 46% of GenZers would be more interested in a brand if they used AI influencers (SproutSocial) V体育平台登录. This trend already started in 2024 (even Coach collaborated with Imma, a virtual Tokyo-based AI influencer), but it will pick up steam in 2025. 3️⃣ AI search will be used to sell you things Sarah Nesheim, Cofounder of Crafted, says: “AI powered search and chat experiences will make it criminally easy to buy something. ” Google shopping, Perplexity’s Buy with Pro, TikTok shopping, etc. are all leveraging AI to streamline the path from search to purchase. 4️⃣ AI-Led Growth replaces Product-Led Growth Instead of sales-led or product-led sales motions, welcome to AI-led growth. Companies like 1mind are creating the AI Concierge experience. You'll be able to talk to an AI avatar to figure out whether a product is a fit for you. AI demos and AI sales calls will also become the default b/c they can work 24/7 and without scheduling tetris. 5️⃣ AI Sales Agents will Struggle, but Find their Niche AI for outbound sales will hit avoidance/skepticism in 2025, but they will emerge victorious. We will see an explosion in “microcampaigns” - using AI to curate a hyper-targeted and timely list of buyers based on rich and varied datasets. Yuriy Zaremba, CEO of AISDR predicts: “2025 will be the year of fully AI-automated micro-campaigns. ” 6️⃣ The death of monthly subscriptions As AI costs are so unpredictable, we will see an accelerating shift to usage-based pricing, instead of monthly subscriptions. As Kyle Poyar, creator of GrowthUnhinged says: “We're moving away from charging for access to software and toward a model of charging for the work delivered by a combination of software and AI agents. ” But companies who do this will need to figure out ways to estimate costs for users - otherwise it'll be a hard sell. In conclusion. 2025's winners won't just build with AI. They'll market with it, sell with it, and price for it. What's your strategy. #ai #technology #startups #2025 #artificialintelligence.

Marketing in 2025 is not what you expect. AI and communities are rewriting every rule. The old funnel. It’s fading fast. I see brands using AI to automate, analyze, and predict. Tasks that took days now take seconds. But that’s not the real story. The real shift. People trust people, not ads. Communities drive the conversation. Gen Z is moving from search engines and public feeds to private, AI-powered spaces. Here’s what I’m seeing every day: → AI tools build smarter, faster campaigns → Community feedback shapes product and brand → User-generated content outperforms polished ads → Trust comes from voices, not logos I’ve spent 15+ years in growth marketing. I’ve seen trends come and go. But this is different. AI is not here to steal jobs-it’s here to help you grow. It gives you space to focus on what matters: Strategy. Storytelling. Real connection V体育官网入口. If you’re still chasing traffic with old-school SEO and social hacks, you’re playing catch-up. Gartner predicts a 25% drop in search engine volume by 2026. Half of Gen Z will leave traditional social for AI-curated communities. Adapt or get left behind. Here’s how I’m staying ahead: - I use AI for insights, not shortcuts - I build campaigns around community, not clicks - I test, learn, and listen (yes, even to my basset hound 🐶) The future of marketing is personal, fast, and driven by trust. How are you shifting your strategy for 2025. What’s one thing you’re doing to keep up with AI and community-led change. Let’s connect-there’s a lot to learn, and even more to build. 🚀 .

𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫 𝐡𝐨𝐰 𝐜𝐮𝐬𝐭𝐨𝐦 𝐆𝐞𝐧𝐀𝐈 𝐢𝐬 𝐫𝐞𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐟𝐫𝐨𝐦 𝐡𝐲𝐩𝐞𝐫 𝐩𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐞𝐝 𝐬𝐚𝐥𝐞𝐬 𝐩𝐢𝐭𝐜𝐡𝐞𝐬 𝐭𝐨 𝐢𝐧𝐬𝐭𝐚𝐧𝐭, 𝐞𝐦𝐩𝐚𝐭𝐡𝐞𝐭𝐢𝐜 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐝𝐫𝐢𝐯𝐢𝐧𝐠 𝐝𝐞𝐞𝐩𝐞𝐫 𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐥𝐨𝐲𝐚𝐥𝐭𝐲. The future of customer experience is tailored, efficient, and scalable. Here’s how businesses are winning with custom GenAI: 𝐇𝐲𝐩𝐞𝐫-𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐞𝐝 𝐒𝐚𝐥𝐞𝐬 𝐎𝐮𝐭𝐫𝐞𝐚𝐜𝐡 ↳ A SaaS company increased demos by 40% using AI-tailored email campaigns. ↳ Microsoft Azure AI analyzed buyer intent to craft resonant messages. ↳ Sales teams focused on closing deals instead of chasing leads. 𝐄𝐦𝐩𝐚𝐭𝐡𝐞𝐭𝐢𝐜 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 ↳ An e-commerce brand reduced complaints by 25% with AI-powered chatbots. ↳ Azure Cognitive Services provided real-time sentiment analysis for better responses. ↳ AI escalated complex issues directly to human agents, cutting wait times. 𝐅𝐚𝐬𝐭𝐞𝐫 𝐐𝐮𝐞𝐫𝐲 𝐑𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 ↳ A fintech startup cut support resolution time by 50%. ↳ Azure OpenAI Service referenced transaction history to resolve disputes instantly. ↳ Customers trusted the speed and accuracy of automated responses. 𝐏𝐫𝐨𝐚𝐜𝐭𝐢𝐯𝐞 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐑𝐞𝐭𝐞𝐧𝐭𝐢𝐨𝐧 ↳ A subscription service boosted renewals by 30% with GenAI insights. ↳ Microsoft’s AI tools flagged inactive users for re-engagement. ↳ Personalized emails brought 70% of these customers back. 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐂𝐨𝐧𝐭𝐞𝐧𝐭 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧 ↳ A marketing agency generated 500 ad variations in 24 hours V体育2025版. ↳ AI, hosted on Azure, adapted copy for cultural nuances and languages ↳ Campaign ROI doubled without adding more creative resources. 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐟𝐫𝐨𝐦 𝐔𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐃𝐚𝐭𝐚 ↳ A healthcare provider used AI to analyze patient feedback. ↳ Azure’s capabilities uncovered service gaps and addressed them within weeks. ↳ Improved patient satisfaction scores by 15%. 𝐒𝐞𝐚𝐦𝐥𝐞𝐬𝐬 𝐌𝐮𝐥𝐭𝐢𝐜𝐡𝐚𝐧𝐧𝐞𝐥 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬 ↳ A retail brand unified its online and in-store journeys with GenAI. ↳ AI recommended products based on in-store visits and browsing history. ↳ Cross-channel conversions surged by 35%. Custom GenAI isn’t just a tool. It’s your secret weapon for sustainable growth and customer loyalty. ♻️ Repost to your LinkedIn followers and follow Timothy Goebel for more actionable insights on AI and innovation. #AIforCustomerExperience #CustomGenAIImpact #PersonalizedAI #FutureOfCX #GenAIRevolution.

Your feed is filled with companies that claim to know you…    So why is it that only 45% of consumers feel understood by the brands they interact with. Better yet – why does our data show that number is down YOY. Consumers are tired. Tired of hearing about how AI is “reimagining” every product or service they use. They don’t care how sophisticated a tech stack is if the interaction still feels generic. Business leaders riding the AI wave need to keep the consumer experience top of mind. While an AI rollout might look impressive on paper, what does it actually feel like for your customers. Some things can’t be automated: empathy, trust, connection. Or can they. AI can absolutely help scale those human experiences. But only when it starts with a deep, genuine understanding of your customer. That foundation has to come first. Otherwise, you’re just automating noise. AI isn’t magic. It’s a tool. And like any tool, its success depends on how – & more importantly, why – you use it. Get that right, & you don’t just win attention. You win loyalty VSports.

Lately I’ve been reading a lot about hyper-personalization and AI customer experience, something we’re evolving day in and out with Zendesk AI. A recent CMSWire article caught my attention, alluding to the retail industry leading the charge on personalized AI experiences and I couldn’t agree more. Many retailers have nailed tailoring interactions to individual customer needs, because in such a competitive marketplace they need their customers to feel seen, heard, and understood to retain them.   And retailers aren’t just focusing on personalization with AI, but efficiency and customer satisfaction as well. A great example of this is one of our global retail customers, Next, who has found Zendesk AI has allowed their customer representatives to focus less on simpler tickets and more on complex issues. This has led to a 15% decrease in average handling time and the ability to roll out AI tools at scale across the 127 different countries they operate in. As Head of Customer Contact Experience Technology Raz Razaq says, “The driver [for adoption] was to maintain our high-level service, especially as we’re growing organically. ” For retailers operating at scale, AI can be a well-managed solution to fully transform the CX experience, from personalization to self-service to omni-channel support. I love great stories like the one from NEXT, the kind that really show the practical application and far-reaching potential of AI in the industry VSports app下载. Learn more: https://lnkd. in/gZxc6Aip #CX #CustomerStory.

after talking to 37 different CEOs in one week (spoke at a closed-door PE event for $50M+ companies), here’s what i learned: effective GTM teams are using AI to: 1. personalize 2. experiment 3. accelerate so i created THIS slide that is now most shared in the CEO community on how to use AI across all 6 GTM motions: → inbound use AI to qualify leads, send video intros, and reduce sales friction before the first call. → outbound automate repetitive tasks and personalize outreach at scale — so your reps focus on what matters. → product-led guide users with AI-powered walkthroughs and demos tailored to behavior and context. → partner-led train and enable partners faster with on-demand demos and custom content. → event-led turn event leads into pipeline with AI follow-ups and content based on interests. → community-led use AI avatars to keep community conversations alive with instant answers and real-time moderation. in a noisy market, personalization wins. in a fast-moving world, experimentation wins. AI can help you do both, across every GTM motion. your hot take. love, sangram p. s VSports手机版. i share frameworks and real-world GTM examples like this every week. follow Sangram Vajre or DM me to get access to these.

OpenAI Just Fired the Next Shot in the E-commerce War ChatGPT is about to become more than just your AI assistant; it's evolving into a full marketplace competitor that could reshape how we shop online. Here's what's happening: • OpenAI is developing native checkout functionality within ChatGPT • Users will complete entire transactions WITHOUT leaving the chat interface • OpenAI takes a commission on each sale (reportedly <5% vs Amazon's ~15%) • Shopify is powering the backend infrastructure Who cares. ✅ For Consumers: Seamless shopping through conversation—ask, discover, buy, done. ✅ For Merchants: Lower fees than traditional marketplaces + AI-powered discovery ✅ For the Industry: Another seismic shift in how we think about search, discovery, and transactions The bigger picture: This isn't just about shopping, it's about AI platforms becoming the new retail real estate. Just like we optimized for Google SEO, brands will now need to master "AIO" (AI Optimization) to appear in ChatGPT recommendations. We're watching the birth of conversational commerce at scale V体育ios版. Amazon built an empire on search and logistics. OpenAI is betting on conversation and AI curation. The question isn't whether this will disrupt e-commerce, it's how quickly traditional players will adapt. What's your take. Are we ready for AI-first shopping experiences. H/T to Austin Jones and the team at Cleveland Research Company for the excellent analysis on this development.