Using viewer behavior to drive email revenue

What if personalized videos could detect the best time to be watched by analyzing the viewer's email habits, ensuring they're sent when the viewer is most likely to open and watch them? Step 1: Gather Viewer Email Habits Data - Action to Take: Use Vidyard data monitoring insights to collect data on when your viewers typically open their emails. - Reason: Understanding the patterns in your viewers' email habits allows you to identify the optimal times for sending your videos. Step 2: Analyze Data for Optimal Send Times - Action to Take: Review the collected data to identify trends and patterns in email activity. - Reason: Pinpointing the most active times ensures your video reaches the viewer when they're most likely to engage. - Tip: Look for outliers and exceptions in the data to avoid basing decisions on anomalies. - Framework/Template: Use a spreadsheet to categorize email open rates by time and day. - Examples: 1. Most viewers open emails at 9 AM on weekdays. 2. Saturdays show a peak in email activity at noon. 3. Late evenings have the lowest open rates. Step 3: Segment Your Audience Based on Habits - Action to Take: Divide your audience into segments based on their email opening habits. - Reason: Tailoring send times to specific segments increases the personalization of your outreach. - Tip: Avoid creating too many segments, which can complicate your strategy. - Framework/Template: Segment your audience into morning, afternoon, and evening groups. - Examples: 1. Early birds who open emails before 8 AM. 2. Midday checkers, active between 12 PM and 2 PM. 3. Night owls, engaging with emails after 7 PM. Step 4: Create and Customize Your Videos - Action to Take: Produce personalized video content for each audience segment. - Reason: Customized content feels more relevant and engaging to the viewer. - Tip: Keep videos concise and focused to maintain viewer interest. - Framework/Template: Develop a video content plan that addresses the specific interests of each segment. - Examples: 1. For early birds, create motivational videos to start their day. 2. Midday viewers might enjoy educational, informative content. 3. Evening content can be more relaxed and entertaining. Step 5: Schedule Videos Based on Optimal Times - Action to Take: Use email automation tools to schedule the sending of your personalized videos at the determined optimal times for each segment. - Reason: Ensuring that your videos land in the inbox at the most opportune moment maximizes viewership and engagement. - Tip: Regularly update your sending schedule based on ongoing analysis of viewer habits. - Framework/Template: Develop a scheduling calendar that aligns video releases with audience segments' peak activity times. - Examples: 1. Early birds receive their video email at 7:30 AM. 2. Midday checkers get theirs just before 12 PM. 3. Night owls find a new video waiting at 8 PM. Will you act on this?

How I turned a client's struggling email list Into a revenue machine When this client came to me, they were frustrated.  They had a big email list.  But almost no sales.  They were doing what most businesses do Sending random newsletters.  Their open rates were low.  Their click rates were even worse.  So, I changed everything.  1. We stopped blasting emails to everyone.  I segmented their list based on behavior.   New subscribers got welcome sequences.   Engaged users got personalized offers.   Inactive users got re-engagement emails.  2. We made every email valuable. No more generic updates.   We told stories.   We educated.   We gave people a reason to open every email.  3. We optimized for conversions. Clear subject lines.   Strong calls to action.   Simple, high-converting designs.  2 months later, the results were amazing Open rates doubled.  Clicks tripled.  Revenue from emails? A 400% increase.  This wasn’t magic.  It was strategy.  Your email list is not just a list.  It’s a goldmine if you know how to use it.  Are you getting the most out of yours?

How I increased 270% more email revenue without a single extra campaign One of our clients had very strong organic traffic But the traffic from e-mail campaigns wasn’t pulling its weight. • Low open rates • High cart abandonment • Generic blasts that didn’t convert Here’s how we used Klaviyo’s AI stack to change that. → Phase 1: Data foundation • Synced Shopify + Klaviyo. Unified browsing, purchase, and engagement data into clean profiles. → Phase 2: Flow buildout with Flows AI • Used Flows AI to generate behavior-triggered journeys, cart recovery, post-purchase, churn re-engagement. → Phase 3: Personalization at scale • Predictive insights to flag high-LTV and at risk customers • Dynamic product recommendations tailored to individual behavior • AI-written subject lines + optimized send times →Phase 4: Optimization • Auto monitors flagged dips in CTR → live campaign tweaks • Segment builder created microlists based on behavior, not guesswork • Review sentiment AI tracked feedback loops across products Six months later: • Email-driven sales ↑ 270% • Open rates ↑ 58% • Cart abandonment ↓ 35% • Repeat orders, retention, and AOV all up We didn’t just send smarter emails We built a machine that knows who to reach, when, and with what message Which of these is blocking your email growth:tech, data, or execution? If you're not sure, let's audit it

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?

Why your email revenue is capped (and how to fix it) 💡 Alright, let’s be real for a second - most Ecom brands are stuck in the same email cycle: Send discount → Hope for sales → Repeat And sure, it works… kinda. But if you want to unlock serious email revenue, you’ve got to level up. Here’s the difference between email amateurs and email masters: 👎 Amateurs: ❌ Blast the same 10% off code to everyone ❌Send generic emails with zero personalization ❌Have no real strategy beyond “more emails = more sales” 👌 Masters: ✅ Emails feel 1:1, not 1-to-many – Dynamic content changes based on each customer’s behavior (browsed a product? Show it. Bought last month? Offer an upsell.) ✅ They don’t rely on discounts – Instead of slashing margins, they stack value (bundles, exclusives, VIP perks). ✅ Email & SMS work together – Not just “Hey, you forgot your cart,” but a real multi-step, cross-channel journey. 💡 Pro Move: Instead of blasting discounts, try progressive profiling -meaning you collect small bits of customer data over time and serve hyper-relevant offers (not just random sales). At the end of the day, email isn’t just about sending more messages - it’s about engineering buying behavior. #emailmarketing #ecom #ecommerce