this is how I would design a marketing team from scratch. vertical specialists + AI agents (claude code) they're letting AI handle the "boring" stuff and working on uncovering new offers/angles/insights to collab on 1) Search/llm specialist - focused on organic traffic - technical website optimization - digital PR, programmatic pages - ai-assisted long form content 2) Paid traffic/ads specialist - unlock paid traffic channels - iterate on ai generated creative - pull data via platform APIs - automated reporting, landing page testing 3) Lifecycle marketer - working with behavior tracking and funnel data - automating + optimizing sequences w/ AI - personalizing account based marketing - iterating on lead magnets Bonus: Social/community - Creator partnerships, relationship builder, affiliates - No manual outreach, knows the niche - Can test formats/angles w/ social content - Launches organic social like someone testing ads (AI powered) you need a strategist / lead that is familiar with the whole stack and can build end to end -- front end/back end, and has done it all manually. hard to find, but 10xer ... almost a marketing AI engineer that can own strategy 3-4 people can get an insane amount done...AND deliver huge roi for in-house teams and agencies this is the future of marketing
How People Are Using AI For Marketing Analytics
Marketing analytics is pivoting from dashboards to agentic, closed-loop systems: brands spending ~$2M+/mo are adopting AI ad analyzers and AI-native automation that trigger, personalize, and iterate in real time (e.g., RL-tuned copy lifted Facebook CTR by 6.7%). The practical playbook favors structured context over hype—build a per-customer JSON profile, connect it to channels, and let a small team of specialists + agents run continuous tests—while experts warn the edge comes from data plumbing, governance, and actionability (not just “AI marketers”) amid workforce-efficiency pressures.
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Improving Facebook ad click rates by 6.7% via RL with genAI text: AdLlama link: https://t.co/fFfk6OolTq https://t.co/CG95pYwzri
85% of data scientists do customer segmentation the WRONG WAY. AI Agents fix this—here's how I made an AI that clusters customers & recommends marketing actions (and you can too). 🧵 https://t.co/hQeWI1zkZK
this one JSON file makes your ad copy feel psychic it’s called a context profile and it’s the missing piece in 99% of AI-powered marketing here’s how to build one (and why it matters) most brands dump raw Shopify exports into GPT and expect personalized marketing. what they get is generic garbage. because without structure or context, your AI is guessing. the output sounds generic because the input is generic a context profile fixes that. it’s a structured snapshot of a customer’s behavior: - order history - site activity - promo engagement - avg order value - product preferences - churn signals and it’s stupid simple to build: 1. pull the data that matters use n8n, Triple Whale, or Shopify’s API to grab: – last 180 days of orders – email/promo activity – on-site behavior (viewed collections, abandoned carts, quiz data) – customer tags or notes 2. structure it as JSON (example below): { "name": "Emily", "email": "[email protected]", "customerType": "Returning", "lifetimeSpend": 742, "averageOrderValue": 62, "lastOrder": "2024-06-01", "orders": [ { "date": "2024-06-01", "products": ["Night Gummies", "Hydration Tabs"], "orderValue": 69 }, { "date": "2024-03-14", "products": ["Calm Focus Tabs"], "orderValue": 55 } ], "productsPurchased": ["Night Gummies", "Hydration Tabs", "Calm Focus Tabs"], "topCategory": "Sleep & Recovery", "quizResult": "Struggles to fall asleep, wants non-groggy solution", "preferredFlavors": ["Lavender", "Citrus"], "pagesViewed": [ "Sleep Collection", "Calm + Focus Bundle", "Subscription Page", "FAQ: Shipping" ], "clickedPromos": [ "Mother’s Day BOGO", "Calm + Focus Bundle Launch" ], "abandonedCart": { "date": "2024-05-27", "items": ["Lavender Sleep Spray"], "cartValue": 38 }, "emailEngagement": { "openRate": 74, "clickedEmails": [ "Productivity Tips for Night Owls", "Calm Bundle Launch", "Hydration How-To" ] }, "subscriptionStatus": "Not Subscribed", "churnRiskScore": 5.8, "lastEngaged": "2024-06-02", "device": "Mobile", "utmSource": "Instagram Ad" } 3. plug it into Claude or GPT: this is where the real leverage kicks in because now you’re feeding the AI a full psychological profile it can think with try prompting it like this: “you’re a performance creative strategist. based on the context profile below, write a UGC script and a 30-second VSL intro that speaks directly to this customer’s needs, preferences, and purchase behavior.” you can use this for: – segmentation-aware email flows – better upsells and winbacks – product recommendations that convert – banger ad copy, hooks, angles and anything else you want your AI is only as smart as the context you give it. this profile turns a generalist model into a laser-targeted strategist. and it works for every part of the funnel.
#MachineLearning and #GenerativeAI for Marketing using #Python — https://t.co/mNksKv5My4 via @PacktDataML Key Features: 🟠Enhance customer engagement and personalization through predictive analytics and advanced segmentation techniques 🟠Combine Python programming with the latest advancements in generative AI to create marketing content and address real-world marketing challenges 🟠Understand cutting-edge AI concepts and their responsible use in marketing ————— #AI #DataScience #ML #GenAI #Martech #CMO #Adtech
Amazon CEO Andy Jassy in a memo to employees earlier today: 'in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company' https://t.co/YaXRgKjW73
$140 billion. That’s what companies spend every year on market research trying to understand their customers. Most of it goes to outdated methods: slow surveys, lagging panels, and static reports. AI is flipping the model. Instead of expensive human surveys, research startups are now simulating entire societies of generative agents — synthetic customers that evolve, interact, and offer feedback in real time. The result? Continuous insight. Smarter bets. A new kind of competitive edge. The shift from static surveys to always-on, AI-driven insights is already underway. This piece from @zachcohen25 and @seema_amble breaks down exactly where it's headed next. https://t.co/uYUAdi4xg8
How to replace your marketing team with AI agents using n8n, MCP, Claude aka "vibe marketing" https://t.co/8P3oWvHCCy
A rethink of the link: Scott Cate, @scottcate, founder of https://t.co/VMzua6dpBQ, has worked at Amazon and other big companies managing thousands of links. He sees a ton of problems with them, so built a new link that marketers who run Websites with thousands of links will want to watch this. ++ Rules-Engine Magic: One short URL, infinite destinations (geo, time of day, device, weather, even AI lookups) ++ Marketer Empowerment: A/B tests, UTM cleanup, domain changes & campaign overrides—click-and-go, no code ++ Affiliate & Team Scaling: On-the-fly tracking codes and one-click bulk updates for hundreds of promos ++ AI Personalization: Dynamically surface the products or CTAs your audience is most likely to love Hit ▶️ to see how modernizing your links can boost conversions, clean up your data, and save you hours every week!
Discord is hiring for AI ads roles The roles involve "building sophisticated ML models to infer user interests and enhance ad targeting" https://t.co/jTVB6KknLs https://t.co/ZrjXpxyYmh