Dynamic Content Testing for Email Campaigns

I boosted click-through rates by 45% with dynamic product recommendations. A DTC brand struggled with low engagement and click-through rates in their email campaigns. Their emails lacked relevance and personalization, which led to subscribers tuning out. The Problem: Generic product recommendations that didn’t resonate with individual customers. Low engagement and poor click-through rates. What I Did: 1. Implemented Dynamic Content: Introduced product recommendations based on customers’ browsing and purchase history. 2. Segmented Emails: Sent tailored campaigns to specific customer segments based on their interests and past behavior. 3. Tested Personalization Approaches: A/B tested various personalized elements such as product recommendations, email timing, and subject lines. The Result: 45% increase in click-through rates. Higher engagement and stronger customer relationships. Improved conversion rates from emails. Personalized product recommendations are key to driving engagement and conversions. Are you personalizing your emails effectively? #EmailMarketing #DTC #Personalization #CaseStudy #ClickThroughRates #DynamicContent

POST-4/7👉 Email used to be a megaphone. In 2025, it’s a whisper in a very specific ear. Gone are the days when “blast to all” could pass as a strategy. In fact, that approach in 2025 is actively hurting your deliverability. Email Service Providers (ESPs) like Gmail, Yahoo, and Outlook are no longer just evaluating your IP health—they’re scoring your sender behavior at the recipient level. That means if 40% of your list is cold or disengaged, Gmail sees you as the problem—not just the user. ⚠️ Real Consequence: 1. We audited an ecommerce fashion brand with 220K contacts. Over 92K of them hadn’t clicked a single email in 90+ days. Gmail flagged them for bulk spam behavior, and inboxing fell from 78% to 46% overnight. 2. They were running promos weekly. Nothing was technically broken—but nothing was relevant. That’s what got them crushed. What Micro-Segmentation Solves in 2025: ✅ Reduces spam complaints ✅ Increases engagement velocity ✅ Signals positive intent to inbox providers ✅ Unlocks higher revenue per send with smaller cohorts Micro-Segmentation Tactics That Work Now: 1. Behavior-Based Journeys: Forget static tags. If someone viewed winter boots but didn’t buy, your next 3 emails better talk about warmth, snow, or style—not your general spring lookbook. ✅ Klaviyo + Shopify data lets you trigger flow branches based on: Last viewed product category Cart abandonment by SKU group Pages viewed in session (via UTMs or on-site behavior) Pro Tip: Use dynamic content blocks inside campaigns to adjust hero sections based on browse activity without cloning entire flows. 2. Lifecycle Automation by Spend Velocity This isn’t “new vs returning” logic anymore. In 2025, flows shift based on: Time since last order AOV trends SKU replenishment cycles Example: First-time customer who hasn’t returned in 30 days → “2nd purchase incentive” High-value buyer within 7 days → “VIP early access” Customer inactive 60+ days → Winback + dynamic offer block + channel sync suppression 3. AI-Supported Clustering Tools like RetentionX, Lexer, and even Klaviyo’s predictive analytics are now building multi-dimensional customer clusters using: Purchase frequency Channel source Time to second order Category loyalty It’s loyal mid-value buyers who shop monthly but only when free shipping is offered. ✅ What to do: Export these clusters to your ESP Build messaging that maps exactly to their past actions Suppress low responders from paid channels and warm email instead. Ready to Execute? Create 5 foundational micro-segments: 1. High spenders 2. First-time buyers 3. VIPs (CLV > 2.5x avg) 4. Dormant >90 days 5. Active clickers, no conversion Test 2 cadences per segment: VIPs: 4x/month + early access Dormant: 1x/month reactivation with content—not promos Use Recency, Frequency, and Monetary score buckets to tag customers and let your automations react to movement between them. #EmailMarketing #email

99% of DTC brands are missing this. (And it’s quietly draining their revenue…) See, most brands think the answer is sending more emails. Or writing clever subject lines. Or A/B testing themselves into oblivion. (Those help… but they’re not the fix.) The REAL reason most brands are bleeding email revenue? They’re running email with the WRONG strategy. 🚨 Batch-and-blast campaigns 🚨 Spray-and-pray segmentation 🚨 “Personalization” that’s just {FIRSTNAME} and vibes Meanwhile… the brands actually crushing it? They made one MASSIVE shift: They stopped guessing… and started running email like a machine. A strategy that… • Adapts to customer behavior in real-time. • Learns from every click, browse, and purchase. • Delivers the right message to the right person - automatically. And at the core of it? 🔥 HYPER-PERSONALIZATION. 🔥 (Not just a fancy way to say "send better emails." We're talking real, behavior-driven, AI-powered personalization that makes every email feel custom-made.) Let’s break it down - 9 ways we’re using hyper-personalization at E/X to print money for brands: 1️⃣ Collect Data Like a Pro Most brands are flying blind. We track demographics, past purchases, browsing history, ad click data, and more. (Yes, it’s legal. No, we’re not the NSA.) 2️⃣ Build Smart Segments "Engaged" and "Unengaged" aren’t segments. We group customers by actual buying behavior, interests, and intent. 3️⃣ Use AI to Predict What’s Next Because guessing is for amateurs. We analyze real-time data to anticipate customer needs before they even realize it. 4️⃣ Personalize Every Single Email Dynamic content, unique offers, behavior-triggered messaging - EVERYTHING adapts to the recipient. 5️⃣ Automate Like a Boss Abandoned cart? Handled. Post-purchase flows? Dialed in. Re-engagement campaigns? Running on autopilot. 6️⃣ Recommend Products Based on REAL Data No random "you might like this" nonsense. We serve products based on actual browsing and buying behavior. 7️⃣ Create Offers That Actually Convert Personalized discounts based on purchase history, browsing habits, and engagement. (Instead of handing out 10% off codes like candy.) 8️⃣ Predict Future Purchases We don’t wait for customers to act. We anticipate their next move - and show up at the perfect time. 9️⃣ Use Real-Time Data to Stay Relevant Loyalty points, recent interactions, browsing habits - we use what’s happening NOW to make emails hit harder. Here’s the deal… ❌ STOP blasting the same emails to everyone. ❌ STOP guessing what customers want. ❌ STOP treating email like an afterthought. Because the brands that get this right? They don’t just make “more” from email. They turn it into their highest-ROI revenue channel. One that drives new customers, keeps existing ones loyal, and scales without burning more ad spend. The ones who ignore this? They’re stuck wondering why their list keeps growing... but their revenue doesn’t. Which side are you on?