How to Optimize Marketing Using AI Tools

An Oxford study just confirmed what most of us have been saying all along: AI-generated ads can outperform human-made ones, but only when they don't obviously look AI-generated. The secret? Human refinement. The best marketing campaigns aren't purely AI-driven or entirely human-made. They're like pizza. Dough alone is just bread, toppings alone is chaos. The magic happens when everything works together. Want to collaborate with AI effectively? 1) Use AI for rapid ideation, humans for emotional depth Take your worst-performing ad copy and feed it into ChatGPT or Claude with this prompt: "Rewrite this to evoke [specific emotion: frustration, curiosity, nostalgia]. Use conversational language. Surprise me." It'll give you variations you'd never think of. Then your human brain picks the best concept and refines it until you think: "We'd never have written this ourselves." 2) Let AI spot patterns, humans craft the story AI's really good at combing through customer feedback, support tickets, and social mentions for trends. But humans make those insights into stories that actually matter. Say AI finds that most support tickets mention setup frustration. Humans craft that into: "Setup shouldn't feel like assembling IKEA furniture blindfolded." 3) AI scales the testing, you choose the winners Generate multiple variations with AI, but you decide which ones are worth spending money on. AI can create 50 headlines in minutes, your judgment tells you which 3 are worth testing. 4) You set the rules, AI fills the gaps Define your brand voice, values, and no-go zones. Then let AI work within those boundaries to fill content calendars, generate product descriptions, or create email variations. Platforms are making this easier: - Microsoft’s Ads Studio has AI-powered creative tools built into campaign workflows - Google Cloud rolled out AI marketing tools for personalized experiences - Or start simple with ChatGPT/Claude and the prompt above Stop thinking AI vs. humans. Start thinking AI + humans. Your move: This week, pick your worst-performing content. Run it through AI with a specific emotional prompt. Refine the best result with your gut instinct. That's how you make sure your marketing isn't just dough or just toppings, but complete, irresistible pizza. P.S. I'm team pineapple on pizza 🍕 + 🍍 = 🤤 (Sorry to my Italian friends! At least there's no ketchup involved... 😂) #hicm #AI #AIinAdvertising

🛒 AI is no longer just the cherry on top of eCommerce anymore - it’s the cake mix. After speaking with 200+ CX, digital-commerce & IT leaders this quarter, here are 5 high-impact, hot plays you can deploy right now 👇 1️⃣ Conversational recommendations = instant revenue Virtual shopping assistants drive 3-5× higher conversion and lift AOV by 50 %+. If you’re not guiding shoppers in real time, you’re leaving money on the table. 2️⃣ Meet buyers where they scroll More than half of consumers shop on social. 24/7 social-commerce chat nurtures intent and lets shoppers check out without ever leaving the feed. 3️⃣ Automate review replies Serious shoppers read reviews — and your silence after 48 hrs costs trust. AI can triage and respond in minutes, protecting brand perception at scale. 4️⃣ Personalize or perish 70 % of retailers using AI-driven journey personalization report 4×+ ROI, fueled by repeat purchases and email engagement. 5️⃣ Let AI pull the night shift Always-on merchandising & pricing decisions will drive $9 B in spend next year. Safeguard margin while you sleep. By 2025, 4 out of 5 brands will have chatbots in production. Wait another budget cycle and you’re playing catch-up. Want to see these plays live this week? My team is already helping retail brands roll them out with zero lift. Drop a ⚡️ below or DM me - let’s turn AI from buzzword to bottom-line. #ecommerce #AI #CX #RetailTech #shoptalk

This Shopify AI memo changes everything for marketers. If you're still treating AI as a "nice-to-have" in your marketing stack, Shopify's CEO just sent a wake-up call. A leaked internal memo from Tobias Lütke lays out a clear mandate: AI proficiency is now a core expectation for everyone at Shopify. Not optional. Not a "productivity hack." Required. Looking at this memo, it clearly transforms AI from a futuristic concept into immediate, practical action. Tobi establishes five principles: 1. AI literacy is a fundamental, non-negotiable skill for all employees 2. AI exploration must lead the product prototyping phase 3, AI skill evaluation is being added to performance reviews 4. Employees need to share their AI learning with colleagues 5. Teams must attempt AI solutions before requesting additional headcount I believe this represents the first wave of what will soon become standard across the industry. The companies that adapt fastest will create insurmountable competitive advantages. For brands, this shift means fundamentally rethinking how marketing teams operate. The productivity gap between AI-powered marketers and traditional teams is already widening daily. When competitors can produce and iterate creative assets, analyze data, and optimize campaigns at 10x your speed, catching up becomes nearly impossible. For agencies, the implications are even more profound. Clients will increasingly expect AI capabilities to be baked into your service offerings, not charged as premiums. Agencies that can't demonstrate AI-enhanced efficiency risk pricing themselves out of the market entirely. So how can you take action? Consider these 3 strategies: 1. Create your version of this memo today. Define clear, measurable expectations for AI adoption across your marketing organization. Be specific about tools, training resources, and how performance will be evaluated. Most importantly, lead by example. 2. Restructure your creative workflows around AI prototyping. Start building a library of effective prompts and templates that your team can adapt. Set a goal that 80% of first drafts (whether copy, design concepts, or campaign strategies) should be AI-assisted within 90 days. 3. Build AI skill-sharing into your regular team rhythms. Create dedicated Slack channels for sharing effective prompts. Add 10-minute segments to weekly meetings where team members demonstrate a new AI technique. Document these learnings where everyone can access them. The most revealing line in Lütke's memo might be his final point: teams must demonstrate why they can't use AI before requesting more resources. That's the mindset shift happening right now. And one we're paying close intention to across our entire portfolio of companies as well.

AI in marketing has come a LONG way. Here are 8 ways we use AI in marketing at Avenue Z: ✅ #1 - Market Research & Persona Development ChatGPT is phenomenal at competitor research, review-scraping to uncover reasons why people by specific products, and can develop specific personas/funnel ideas to fuel customer acquisition. ✅ #2 - Creative Our AI-powered research fuels our creative briefs & angles. Best use case for AI-driven creative is background swapping of product images, AI voiceovers & video cutdowns. Still aren’t there yet on HQ/usable GenAI creative from a simple prompt. ✅ #3 - Search Engine STILL the #1 way content is found online. AI Overviews appear above organic search results. We craft on-site content designed to rank not just on org search, but in AI search results too. Showcased an example of this a few months ago, where we consistently appear in AIO for a service of ours. ✅ #4 - UGC Playing around w/ Icon, a platform enabling AI-driven influencer content. If an influencer shoots a 2-min video of your product, you can use their likeness to create endless iterations of the content. Swap the hook, talking points, language or B-roll at scale. Have a winning ad? AI deconstructs the vid & enables its recreation using other influencers. Easy way to test diff demographics or languages w/o having to source specific influencers. Game-changing. ✅ #5 - Ad Copy AI is much better at written content than visual content. Platforms like Meta provide copy iterations that you can test seamlessly. ChatGPT is solid for rewriting content to give a diff tone, look, or feel. Build custom GPTs to train the LLM on brand voice or other examples of copy you like/have performed well. ✅ #6 - Landing Pages We built a custom GPT that generates specific landing page frameworks for any brand/offer/product based on our LP best practices. Eventually we'll see AI create personalized landing pages based on a user’s attributes. Ex: returning customer sees diff website experience than new website visitor. Highlights the importance of collecting ample 1P data in today’s world. ✅ #7 - Measurement For larger brands w/ many different traffic sources & sales channels, attribution can be a futile effort. Multi-touch attribution (MTA) can fall short. This is where marketing mix modeling (MMM) comes in. Prescient AI modernized MMM by powering it with AI/ML to give objective recommendations on budget/allocations based on audience saturation & halo effects your marketing has on other ad platforms & sales channels. ✅ #8 - Targeting/Algorithm Training Ad platform algorithms already use AI in targeting which is why they advocate so heavily for broad targeting. BUT- what’s really cool is the concept of using predictive analytics to make the algorithm/AI smarter. Angler AI doing cool things in this area. Especially effective in niche product categories or brands w/ high AOV. Reminder: you're only as effective as your utilization of the tools around you!

80% of people prefer to buy from brands that personalize. Yet most businesses still send generic campaigns. Here’s how I use AI to change that 👇 Step 1: Build Your Data Foundation → Consolidate customer data from all sources → Clean and structure your data → Create unified customer profiles → Map customer journeys Step 2: Choose the Right AI Tools → Start with predictive analytics → Add dynamic content generation → Implement real-time personalization engines → Focus on tools that integrate with your stack Step 3: Create Personalization Frameworks → Segment audiences by behavior → Design content templates → Set up trigger-based workflows → Define success metrics Real examples that work: 1/ E-commerce: → AI analyzes browsing patterns → Predicts next likely purchase → Personalizes email timing ↳ Result: 40% higher conversion rates 2/ B2B Marketing: → AI scores leads in real-time → Customizes content by industry → Automates follow-up timing ↳ Result: 3x faster sales cycles 3/ Content Marketing: → AI suggests trending topics → Personalizes content recommendations → Optimizes posting schedules ↳ Result: 2x engagement rates Warning: Avoid these common mistakes: → Implementing AI without clean data → Focusing on tools over strategy → Forgetting the human element → Ignoring privacy concerns Remember: AI amplifies your marketing. It doesn't replace your strategy. Start small, measure results, scale what works. What's your biggest challenge with marketing personalization? Comment below. Sign up for my newsletter for more marketing and AI content: https://lnkd.in/gSi-nA2F Repost or follow Carolyn Healey for more like this.