Sophie Catonné

The myth of aggressive CTAs is killing your conversion rates. Most CTAs scream “BUY NOW” or “GET STARTED” without addressing the     real friction behind user hesitation.  → People don’t want to feel trapped → They hate immediate commitment → They fear making the wrong choice And yet... most CTAs feel like pressure, not permission.   Here’s what actually works: ➡️ LOW-PRESSURE LANGUAGE ❌ “Buy Now” → ✅ “See Options” ❌ “Get Started” → ✅ “Explore Features” These subtle shifts ease anxiety and can lift clicks by 47%. ➡️ CLEAR NEXT STEPS ✅ “View Pricing (2-minute overview)” ✅ “Schedule Demo (15 minutes)” Clarity removes hesitation. ➡️ VALUE-FOCUSED MESSAGING ❌ “Sign Up Now” → ✅ “Access Free Templates” ❌ “Join Today” → ✅ “View Success Stories” Focus on what they get, not what they must do. When these principles are applied, conversion rates often jump by 60% or   more. The best part? Better leads More trust No pressure Stop pushing. Start connecting. Because the best CTAs don’t yell. They invite. #ConversionOptimization #MarketingStrategy #CopywritingTips  #UXWriting #GrowthMarketing

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Here is my personal CRO Checklist with 140 ideas to optimize your product page (PDP)⚡️ I went through our database with 2,500 A/B-Tests, and broke down the most universal and important CRO checkpoints. Whats included: → 17 Shipping & returns ideas → 6 Customer support ideas → 19 Pricing & options ideas → 7 Product overview ideas → 12 Image & media ideas → 15 Product detail ideas → 9 Cross & upsell ideas → 12 Call to action ideas → 19 Social proof ideas → 6 Trust Signal ideas → 8 Promotions ideas → 4 Navigation ideas 𝗛𝗲𝗿𝗲 𝗶𝘀 𝗵𝗼𝘄 𝘆𝗼𝘂 𝘂𝘀𝗲 𝘁𝗵𝗶𝘀 𝗹𝗶𝘀𝘁: 1. Go through and see what KEY elements you are missing 2. Determine priority of ideas (List is sorted by cost & impact) 3. Validate data with our idea description & psychological whys included. 4. Test and implement 𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝗶𝘁: 1. Like this post 2. Comment "PDP" and I'll send it to you. P.S. Repost for priority access

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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.

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How to publish 30 LinkedIn posts / month without burning out (insane new MCP workflow) BACKGROUND: → Consistent LinkedIn posting is the best way to build a business in 2025 → Most successful creators post 20-30 times per month → I've posted since 2023, and I've written every single post ISSUES: → It's mentally exhausting → You stare at a blank page for hours, dealing with writer's block → You can batch content but it takes forever to research what works SOLUTION: → There's a system using Airtable MCP + Claude Desktop + Wispr AI → It's designed to eliminate the hardest parts of content creation → But most people don't know how these tools can work together Here's the setup: Part 1: Airtable Database → Load it with high-performing content from creators you admire → Categorize by content type with hook templates → Include all your past posts with performance data Part 2: Claude Desktop with Airtable MCP Server → Claude can now tap directly into your database → Ask: "Show me hooks for the 5 best 'Steal My Process' posts" → Or: "Give me links to top 7 cheat sheet style posts" → You instantly have 50-60% of your work done Part 3: Wispr AI → Talk to Claude instead of typing → Give it the example post and hook template → Talk through your original thoughts and adaptations → Get a solid first draft without writer's block → Then use your human brain to edit it to your standard Now you have a robust system: Organized database + AI that accesses it + voice-to-text workflow. (PS. I figured this out ~2 weeks ago and thought about keeping it quiet. But I honestly believe most people won't spend the time building it. So, here you go.)

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I’ve scaled 2 dozen eCommerce brands in 2025 — by 5–15x. How? By mastering demand capture with Google Ads. Here’s the campaign set I use: 1. Standard Shopping (performance-based grouping) → Superstars | High priority → A Players | Medium priority → Reserves | Low priority → Benched | Low priority Bid strategy: tROAS 2. Branded Search → Brand name as exact & phrase → Manual CPC 3. Branded Shopping → Low priority → Exclude non-branded keywords as they appear → tROAS 4. Non-Branded Search → For Superstars & A Players only → Manual CPC / Max Conv. Value → Upgrade to tROAS within 30–60 days 5. Dynamic Product Remarketing → Audience: Abandoned cart (7–14 days) → Frequency: ~7 impressions per day per user → Manual CPC / Max Conv. Value → tROAS within 30–60 days 6. YouTube Remarketing → Audiences: Abandoned cart & product view (7–14 days, no purchase) → UGC or product demo with CTA works best → Manual CPC / Max Conv. Value → tROAS within 30–60 days Timeline: ↳ Weeks 1–2: Learning & testing ↳ Weeks 2–4: Optimising ↳ 4+ Weeks: Scaling Is it easy? No. Is it worth it? Absolutely. Done right, this playbook can skyrocket your eCommerce brand. And the best time to get started? Right now — Q4 is around the corner. Not sure where to begin (and tired of not making the revenue you deserve)? Reach out.

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I worked in CRO at a £5 billion+ brand. What I learned changed how I optimise websites completely ↴ Most people think CRO = conversion rate. But at enterprise level? That’s just one piece of the puzzle. Here’s what I learned ↓ 1. Data is everything ↴ I learned quickly that numbers had to drive every decision. No guesswork. No “I think this looks better.” If something couldn’t be measured, it wasn’t worth testing. If the data didn’t back it up, it wasn’t worth rolling out. That discipline completely changed how I approach optimisation today. ⸻ 2. Business strategy beats following trends ↴ Another big lesson: not every trend is worth chasing. It’s easy to see competitors launch something new and feel pressure to copy. But I realised the real question is always: → Does it align with the bigger strategy? → Does it solve a real customer problem? → Does the data suggest it’ll move the needle? Chasing trends without strategy is how budgets get wasted. ⸻ 3. Conversion rate isn’t the only metric that matters ↴ A 5% conversion rate doesn’t count if: → Returns are 40% → AOV is dropping → Customers never come back What really matters is the full picture: → Basket size → Repeat purchase rate → Customer lifetime value Sustainable growth isn’t just about more sales. It’s about the right sales. ⸻ 4. Best practices differ by category ↴ Some categories see more desktop research before purchase, others are pure mobile impulse buys For certain products, strong imagery outperforms copy There’s no one-size-fits-all. The key is understanding how your customers make decisions and optimising for that. — Because here’s the thing: You don’t need £5B in revenue to benefit from proper CRO. You just need someone who knows how it actually works. I’ve run 50+ tests. 5+ years in e-commerce Trained software engineer. Business degree. I understand strategy, not just tactics. And now I help health, wellness & beauty brands apply enterprise-level thinking Without the enterprise budget or in-house team. Smart optimisation isn’t about traffic volume. It’s about knowing what to test, when to test it, and why it matters.

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Attribution is slowly dying. And most marketers are still trying to bring it back to life. Here's the reality check nobody wants to hear: → Traffic from social platforms is dying → Privacy laws killed cookie tracking → 40%+ of people use ad blockers → Multi-device journeys broke attribution models → AI tools keep traffic for themselves (zero-click everything) The solution? Stop trying to track every click and start measuring what actually matters. Welcome to lift-based measurement (Full credit to Rand Fishkin for both the term and this graphic from one of his posts.) Instead of asking "which channel drove this sale?" ask "did our overall metrics lift when we ran this campaign?" This isn't new - it's how Coca-Cola tested billboards in the 1960s. Run the same ad in two similar cities, measure which one drove more sales. Here's what you measure instead: - Top of funnel: Brand awareness, impressions, initial exposure - Middle of funnel: Engagement, website visits, brand searches - Bottom of funnel: Subscriptions, signups, actual sales The metrics will be different for every business. But the approach stays the same. Test. Measure lift. Scale what works. Attribution tried to give you perfect data. Lift-based measurement gives you actionable insights. Again, credit to Rand Fishkin for breaking this down so clearly. Check out his post. Sometimes the old ways work better than the new ones. … I'll be honest - marketing feels pretty hard right now. Algorithm changes, attribution dying, AI.... everything we thought we knew pretty much is changing and it's a lot. Which is why I'm all for us actually supporting each other instead of pretending we have it all figured out. Share what's actually working, admit what isn't, and help fellow marketers navigate this mess together. … I’ll for sure do my best to do so We're all figuring this out as we go. 🤝🏼

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