Frans Ekman’s Post

Data doesn't lie, but vanity metrics do. And they silently kill the product strategy. Over time, I learned this: The best PMs pick a handful of key metrics and revisit them often. Here are 10 metrics I use (and recommend to every PM): 1. Retention rate: Are users coming back? 2. Churn rate: Who’s leaving and why? 3. Daily/Monthly Active Users (DAU/MAU): Are people using what we built? 4. Customer Lifetime Value (LTV): What’s each user worth over time? 5. Feature adoption rate: Are new features being used?  6. Funnel drop-off: Where do users abandon the journey? 7. Net Promoter Score (NPS): Would they recommend us? 8. Load time / Performance: Is the experience smooth?  9. Sign-up conversion rate: Are we converting visitors into users? 10. Support ticket trends: What issues keep surfacing? The key is tracking what matters most to your product stage, customer needs, and business goals. Takeaway: You don’t need 100 dashboards. You need the right 5 metrics tied to your product’s stage and goals, and the discipline to act on them. Which 3 metrics do you rely on the most?

Case Study: How We Generated $127,000 in Additional Revenue in 45 Days 📊 CLIENT PROFILE: E-commerce Fashion Brand - $50K monthly revenue, struggling with conversions 🚨 THE PROBLEM: → 1.8% conversion rate (industry average: 2.35%) → 67% bounce rate on product pages → 8.3 second load time → Mobile experience was broken → Zero personalisation or automation 🎯 OUR STRATEGIC APPROACH: WEEK 1-2: RESEARCH & PLANNING → Heat map analysis revealed user behavior patterns → Competitor analysis identified key opportunities → Customer interview insights guided strategy WEEK 3-4: IMPLEMENTATION → Complete product page redesign with social proof → AI-powered recommendation engine implementation → 3-step checkout process optimisation → Mobile-first responsive design overhaul WEEK 5-6: OPTIMISATION → A/B tested 14 different elements → Speed optimisation to 1.2 second load time → Advanced analytics and tracking setup 💰 THE RESULTS: → Conversion rate: 1.8% → 4.3% (+139%) → Average order value: +42% increase → Page load speed: 8.3s → 1.2s (-85%) → Mobile conversions: +187% increase → Monthly revenue: $50K → $77K (+$27K/month) 🔬 THE SECRET SAUCE: We treated their website like a revenue laboratory, not an art project. Every decision was data-driven, every change was measured. What's your current conversion rate? What would a 139% improvement mean for your business? #CaseStudy #EcommerceOptimization #ConversionResults #RevenueGrowth #DataDriven

Today we're launching our most requested feature: 📈 Usage Insights You might ask, why do I need another analytics platform and/or why should a monetization platform like Schematic do usage analytics? Well, we listened to our customers and they constantly ask us questions like: ⋅ Which customers are at their limit or approaching their limit? (Upgrade opportunities) ⋅ Which customers are paying but not really using the product? (Churn risk) ⋅ Which of my features are used the most by paying customers? (Value insight for pricing) ⋅ Which features are my customers paying for but not using? (Value insight for pricing) Because Schematic has both customer billing and usage context in one place, we're uniquely positioned to answer these questions. Even better, once you learn something about usage, you can grant an override or tweak your pricing/packaging right in Schematic. See the video for how it works. p.s. You can also set up alerts for when customers reach or approach their limits to trigger a slack message or email via a webhook.

Most 𝗔/𝗕 𝘁𝗲𝘀𝘁𝘀 fail not because of poor execution, but because of poor strategy. After helping small and mid-size businesses optimize their digital experiences with Optimizely, we've noticed patterns that separate successful tests from wasted efforts: 1. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘂𝘀𝗲𝗿 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝘂𝗿 𝗱𝗮𝘁𝗮, 𝗻𝗼𝘁 𝗴𝘂𝘁 𝗳𝗲𝗲𝗹𝗶𝗻𝗴𝘀. • Heat maps and user recordings reveal what visitors do, not what we think they do. 2. 𝗧𝗲𝘀𝘁 𝗺𝗲𝗮𝗻𝗶𝗻𝗴𝗳𝘂𝗹 𝗰𝗵𝗮𝗻𝗴𝗲𝘀, 𝗻𝗼𝘁 𝗯𝘂𝘁𝘁𝗼𝗻 𝗰𝗼𝗹𝗼𝗿𝘀. • We helped an e-commerce client increase conversions by 34% by testing value propositions instead of CTAs. 3. 𝗦𝗲𝘁 𝗽𝗿𝗼𝗽𝗲𝗿 𝘀𝗮𝗺𝗽𝗹𝗲 𝘀𝗶𝘇𝗲𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝗹𝗮𝘂𝗻𝗰𝗵𝗶𝗻𝗴. • Too many tests end prematurely with inconclusive results. 4. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝘆𝗼𝘂𝗿 𝗿𝗲𝘀𝘂𝗹𝘁𝘀. • What works for mobile users might not work for desktop. The goal isn't just to run tests—it's to build a culture of data-driven decision-making. What's the most surprising insight you've discovered from A/B testing? Let us know in the comments. #ABTesting #CRO #DataDrivenMarketing #TestingStrategy #Optimizely 

⭐ Turn Customer Reviews into Actionable Insights with Review Scraper API! 📊🚀 In today’s digital-first economy, #customerreviews are a goldmine for business growth, #productdevelopment, and #brandstrategy. The #ReviewScraperAPI from #DataZivot empowers you to seamlessly #extractreviews from multiple online platforms—giving you instant access to #valuablecustomerfeedback. 🔍 Key Benefits You’ll Unlock: ▪️ Automate review extraction from e-commerce sites, apps, and marketplaces ▪️ Access structured data including ratings, comments, timestamps & reviewer profiles ▪️ Perform sentiment analysis & trend tracking with ease ▪️ Monitor competitor reviews for benchmarking ▪️ Integrate with analytics platforms for continuous monitoring 🚀 Why It Matters: Whether you're in #productmanagement, #marketing, or #customer experience, this API helps you gain deep #customerinsights, refine offerings, and make data-backed decisions. 🔗 Explore More>>>>https://lnkd.in/dXv57YmX 📩 Contact us: sales@datazivot.com #ReviewScraperAPI #ReviewExtractionService #SentimentAnalysisAPI #MultiPlatformReviewData #CustomerFeedbackAPI #ReviewAggregationTools #ProductReviewAPI #ServiceReviewExtraction #ReviewScoreAnalytics #ConsumerOpinionAPI #ReviewAlertSystem #ReviewMiningTool #UserReviewExtraction #ContextualReviewAnalysis #GlobalReviewInsights #BusinessReputationAPI #ReviewPipelineSolution

Your COA isn’t the problem. Your perspective is. Most businesses (and agencies) obsess over Cost of Acquisition (COA). "Can we get leads for less?" "Is £30 too much for a £60 product?" COA is important. But it’s not the full picture. One of the most overlooked metrics is Customer Lifetime Value (LTV). Let’s say you sell a £60 product. It costs £30 to acquire a customer. A lot of people would panic and start slashing ad spend. But here’s the reality: 📦 That first purchase is just the intro 🔁 If your product’s great, they’ll come back 📈 If your average LTV is £2,000 over 12 months… …that £30 COA is an absolute steal. The problem is that too many strategies are based on single transactions, not customer journeys. And if you’re not factoring in LTV, retention, upsells, or brand loyalty, you’re probably leaving money on the table. 💡 You can’t run a data-driven strategy if you’re only looking at part of the data. Zoom out. Look long-term. And build your campaigns around lifetime value, not just first clicks.

How we boosted an ecom client’s conversion rate by 11.21% 🚀 3 strategic image tweaks. 100+ user behavior insights. One powerful CRO framework. Here’s what we tackled: ✅ Misaligned PDP images ✅ Unclear customer benefits ✅ Trust-killing visuals The result? 📈 +11.21% conversion rate 📈 +$12K monthly revenue PDP images shape the customer journey. By prioritizing clarity and intent, we turned hesitation into action. All backed by deep research and smart optimization. 👉 Swipe through to see how we did it.

I recently reviewed growth metrics for a client who was celebrating 1 million app downloads. Impressive on the surface, but digging deeper revealed only 12% completed onboarding and a 70% churn rate within 30 days. The real story? They were tracking vanity metrics, not value metrics. This disconnect between surface success and actual performance is why I always start with the LTV:CAC ratio - it's the single most reliable indicator of sustainable growth. Here's your 3:1 framework: • Below 3:1: Unsustainable acquisition costs - you're overspending for the value you're getting • Sweet spot 3:1: Profitable and scalable - every £1 spent returns £3 in customer value • Above 5:1: Underinvesting in growth - you could be scaling faster with higher acquisition spend The key insight? That 'too high' ratio often means you're leaving money on the table by being too conservative with your marketing investment. At Veritern, I help businesses make this shift from vanity to value. One e-commerce client's transformation shows exactly why this matters: ✅ Installs dropped 15% (yes, downloads went down) ✅ Average order value increased 43% ✅ ROI improved 28% Less traffic, more value. That's sustainable growth. Ready to audit your metrics? Start by calculating your LTV:CAC ratio, then ask: are you optimising for what looks good or what drives profit? Drop a 📊 if you'd like my free LTV:CAC calculator template. #GrowthMetrics #CustomerAcquisition #BusinessGrowth #MarketingROI #LTV #CAC

Unlocking user insights can transform your conversion strategy. Google Analytics 4's 'Explore' section empowers businesses to create customized reports revealing vital information on user behavior throughout the conversion funnel. By defining specific steps in the checkout process, like 'begin checkout,' 'billing and shipping,' and 'purchase', you can track user journeys with precision. The data obtained offers a segmented view by city, illustrating completion and abandonment rates. Furthermore, analysis by device category provides deeper insights, identifying critical drop-off points in the funnel. Tailor these explorations to actions that matter most to your business, whether it’s form completions or appointment bookings. Leverage these insights to enhance user experience and optimize conversion strategies. For a comprehensive understanding of your data, consider scheduling a data audit through our website.

🧟♂️ Your Users Are Stalking You. (And That’s Exactly What You Want.) They watch your every move — 👀 Scroll your website 🖱️ Click, hover, hesitate 🚪 Leave without saying goodbye …then come back at 2:47 AM like nothing happened. Creepy? Kinda. Helpful? Absolutely. Because behind every "weird" user behavior lies a pattern — a breadcrumb trail of what excites, annoys, or confuses them. Here’s what that “digital ghosting” might be telling you: 🧩 Users abandon after step 3 in your checkout? → Your pricing or trust factor might be spooking them. 🌀 They keep toggling between two pages? → They’re looking for clarity. Give them answers before they ask. 🔁 Repeat visitors who never convert? → They're curious. Nurture, don’t sell. 🎯 User behavior isn’t noise — it’s a map. Decode it, and you’ll stop chasing users. They’ll come to you. So the next time your dashboard creeps you out with strange bounce rates or zombie sessions… remember: 👻 "Every ghost in your funnel was once a curious customer." #UserBehavior #ProductAnalytics #CustomerInsights #GrowthStrategy #ProductManagement