Using Ecommerce Analytics to Improve User Experience

A client came to us frustrated. They had thousands of website visitors per day, yet their sales were flat. No matter how much they spent on ads or SEO, the revenue just wasn’t growing. The problem? Traffic isn’t the goal - conversions are. After diving into their analytics, we found several hidden conversion killers: A complicated checkout process – Too many steps and unnecessary fields were causing visitors to abandon their carts. Lack of trust signals – Customer reviews missing on cart page, unclear shipping and return policies, and missing security badges made potential buyers hesitate. Slow site speeds – A few-second delay was enough to make mobile users bounce before even seeing a product page. Weak calls to action – Generic "Buy Now" buttons weren’t compelling enough to drive action. Instead of just driving more traffic, we optimized their Conversion Rate Optimization (CRO) strategy: ✔ Simplified the checkout process - fewer clicks, faster transactions. ✔ Improved customer testimonials and trust badges for credibility. ✔ Improved page load speeds, cutting bounce rates by 30%. ✔ Revamped CTAs with urgency and clear value propositions. The result? A 28% increase in sales - without spending a dollar more on traffic. More visitors don’t mean more revenue. Better user experience and conversion-focused strategies do. Does your ecommerce site have a traffic problem - or a conversion problem? #EcommerceGrowth #CRO #DigitalMarketing #ConversionOptimization #WebsiteOptimization #AbsoluteWeb

Ever launched a product or feature, only to see users drop off without knowing why? You check the analytics - traffic looks fine, but engagement is slipping. Where are users struggling? Why do some breeze through while others get stuck? Traditional metrics like bounce rates and session counts barely scratch the surface. This is where session analysis becomes a game-changer. It moves beyond surface-level metrics to uncover hidden behavioral patterns - why users hesitate, get frustrated, or abandon tasks entirely. One of the biggest challenges in UX research is understanding friction points in real time. Hesitation detection reveals where users pause too long, signaling uncertainty or cognitive overload. Rage click detection catches moments of frustration - those rapid, repeated clicks that scream, "Why is this not working?" But frustration does not always look the same. Some users walk away silently. Task abandonment analysis helps us detect disengagement before it is too late, using behavioral trends rather than arbitrary cutoffs. Dwell time analysis adds another layer, showing how long users actively engage before losing interest. Of course, not all users behave the same way. Clustering techniques help group them based on interaction styles, making personalization and targeted interventions possible. And we can take it further - predictive modeling, like logistic regression, helps forecast dropout risk, allowing us to act proactively rather than reactively.

Stop chasing vanity metrics like views. They don’t matter. Focus on the real metrics that do matter. Clicks and conversions. Then build a user experience that maximizes them. First impressions are everything. Your site has to hit the UX out of the park to get engagement, clicks, and conversions. Here are a few things to consider when optimizing UX : 1) Know User Behavior How do users interact with your site? Do they spend a lot of time on product pages but bail at checkout? Do they ditch their shopping carts? Can they find your content on best-selling strains but get lost when they try to buy them? Tracking their journey gives a clear picture of user behavior and how your site needs to adapt to that behavior to maximize time on-site, clicks, and conversions. 2) Identify and Address Where You Lose Customers Pinpointing where and why potential customers leave your site is crucial. Maybe it's a complicated checkout process, poor site speed with product images that load slowly, or a hard-to-find "Shop" button. Make these weaknesses strengths to improve conversions. Simplify checkout. Improve site speed. Make the "Shop" button a can’t-miss. Some of our partners have seen a 10% increase in click-through to the menu by simply moving the "Shop Now" button above the fold. 3) Create an engaging User Experience Every step from the moment a user lands on your site to completing a purchase must feel intuitive and flow smoothly if you want your users to engage. This could mean streamlined navigation, clear, concise product descriptions, or improving the mobile browsing experience (which is crucial for customers who shop on their phones, and most customers shop on phones.) The bottom line is that more engagement = More Clicks and More Clicks = More Conversions.

Subscription services need strong analytics to build smarter & strategically strong plans. 🚀 Subscription models aren’t just a trend anymore—they’re shaping the future of eCommerce. 🛍 But are you leveraging data & analytics sufficiently, to iteratively build your strategy, & have your customers coming back? Here’s why you should make data analytics an integral part of your business approach: 🎯 Customer Retention Isn’t a Guessing Game Many eCommerce businesses still rely on gut feeling & high level market trends when deciding what keeps their subscribers happy. What if you could make smarter, data-driven decisions instead? Here’s how: 1️⃣ Understand User Behavior at a Granular Level Accurate analytics helps you spot patterns in how your subscribers behave. 👉 For example, a fitness app found that users who completed daily workouts stayed subscribed longer. With this insight, the app focused on features that encourage consistent engagement, boosting retention. 2️⃣ Personalize the Experience Analytics isn’t just about numbers—it’s about the people behind them. By segmenting your customers based on their behavior & psychographics, you can create personalized experiences that drive loyalty. 👉 Example: Netflix tailors its show and movie recommendations at a segment of one level, making subscribers feel seen and valued, while also making their life easier! 3️⃣ Track Key Metrics Keep an eye on crucial metrics such as Churn Rate, Average Order Value (AOV), & Customer Lifetime Value (CLTV). These metrics tell you what’s working, & where you need to pivot. 👉 For instance, a music app discovered that users who created personalized playlists were less likely to churn. Now they focus on promoting playlist creation to keep users engaged. 4️⃣ Leverage Predictive Analytics Want to predict churn before it happens? Predictive analytics can highlight warning signs of disengagement so you can take action before your subscribers leave. 👉 Takeaway: With predictive analytics you can send personalized reminders, special incentives, or tips to at-risk users, keeping them engaged. 5️⃣ Test, Learn, Optimize Don’t settle for your first plan. A/B testing helps you experiment with different subscription models, pricing, & features to arrive at the best. 👉 Example: A video streaming service can test different pricing structures & tiers, & find the best pricing plans that maximize sign-ups, market share, & retention. Bottom line: Subscription analytics give you the insights you need to understand, retain, & grow your subscriber base. Embracing smart data, & analyzing it while keeping the people behind it in your mind can create more personalized, engaging, & profitable subscription model. At Appstle Inc. there are 30,000+ eCommerce businesses that hands-on use our granular analytics to make impactful data driven customer retention strategies. The analytics are an integral part of Appstle Subscriptions. Because there is no better way to profitably scale!

How I find conversion rate opportunities by breaking down the shopping funnel: Instead of looking at your entire funnel conversion rate (2-3% on average)... Step 1. Break it into parts. 1. All traffic 2. Non-bounce (% Sessions viewing 2+ pages) 3. Product Viewers (% Sessions viewing 1+ product) 4. Add to Cart (% Sessions adding 1+ product to cart) 5. Checkout Start (% Sessions starting checkout) 6. Checkout Complete* (% Sessions completing 1+ orders) *You can also break down the checkout flow further: Billing/Shipping > Review > Thank You As a percent of the total, a typical e-commerce site might be: 1. All traffic: 10,000 sessions - 100% 2. Non-bounce: 7,000 sessions - 70% 3. Product Viewers: 3,000 sessions - 30% 4. Add to Cart: 800 sessions - 8% 5. Checkout Start: 400 sessions - 4% 6. Checkout Complete: 300 sessions - 3% Step 2. Calculate the % moving to the next step The KEY is to look at the conversion rate between steps. Calculate by dividing the sessions on each step over the sessions from the previous step. 1. All traffic: NA 2. Non-bounce: 7,000 / 10,000 = 70% 3. Product Viewers: 3,000 / 7,000 = 43% 4. Add to Cart: 800 / 3,000 = 27% 5. Checkout Start: 400 / 800 = 50% 6. Checkout Complete: 300 / 400 = 75% Step 3. Look for trends You don't need to worry about ecommerce benchmarks. Your marketing channel mix, product type, and audience will all influence your numbers. Focus on YOUR numbers. This is your baseline. Trend these rates over time, and watch for anomalies. Step 4. Improve each step methodically Does your checkout completion rate look low (75%)? Maybe consider: - Checkout Form optimization - Adding new payment types - Simpler discount codes - Accurate delivery estimates Is your Add-to-Cart rate low (27%)? Maybe consider: - Pricing optimization - Additional social proof on PDP - Improved product images and videos - Digging into inventory and availability Step 5. Track your results As you make improvements (or run experiments) measure your intra-funnel rates. It's much easier to track improvements compared to looking at your aggregate conversion rate. Are you breaking down your e-commerce funnel? #cro #conversionrate #ecommerceanalytics