Understanding Ecommerce User Behavior Data

Every product team strives to understand their users, but traditional methods like surveys, interviews, and usability tests only tell part of the story. They capture what users say - but not always what they do. The real insights lie in their actions, and that’s where clickstream analysis changes the game. Clickstream data is the digital trace of user behavior - where people click, how long they stay on a page, the paths they take, and where they drop off. At first glance, it seems like just a collection of numbers, but hidden in that data is a story - a real, unbiased view of how users interact with a product. For UX researchers, this kind of data is invaluable. It helps uncover behavior patterns that might not surface in traditional research. It highlights friction points, moments of hesitation, and places where users disengage. It shows what features are actually being used versus what people say they use. It helps measure the impact of design changes and track engagement over time. But analyzing clickstream data requires more than just counting clicks. The key is going beyond the surface and asking the right questions: What patterns separate engaged users from those who leave? When do people tend to drop off, and what factors contribute to it? How do different types of users interact with the same experience? Can we predict future engagement based on past behavior? To answer these kinds of questions, we used multiple methods: - Tracking engagement trends helped us understand how user behavior evolved over time. - Forecasting future engagement used time-series analysis to predict upcoming trends, revealing whether engagement would remain stable or decline. - Predicting user behavior leveraged machine learning to anticipate which users were likely to continue engaging and which might churn. - Estimating dropout risk with survival analysis pinpointed the moments when users were most likely to disengage, helping identify critical intervention points. Clickstream analysis isn’t a replacement for usability research, but it adds another layer to how we understand user behavior. Usability testing tells us why people struggle with a design, but clickstream data shows where and when those struggles happen in real-world use. Together, they create a more complete picture of digital experiences. UX research has always been about understanding people, and in a world where user interactions generate more data than ever, clickstream analysis helps see beyond what users say and into what they actually do.

Most teams are just wasting their time watching session replays. Why? Because not all session replays are equally valuable, and many don’t uncover the real insights you need. After 15 years of experience, here’s how to find insights that can transform your product: — 𝗛𝗼𝘄 𝘁𝗼 𝗘𝘅𝘁𝗿𝗮𝗰𝘁 𝗥𝗲𝗮𝗹 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗥𝗲𝗽𝗹𝗮𝘆𝘀 𝗧𝗵𝗲 𝗗𝗶𝗹𝗲𝗺𝗺𝗮: Too many teams pick random sessions, watch them from start to finish, and hope for meaningful insights. It’s like searching for a needle in a haystack. The fix? Start with trigger moments — specific user behaviors that reveal critical insights. ➔ The last session before a user churns. ➔ The journey that ended in a support ticket. ➔ The user who refreshed the page multiple times in frustration. Select five sessions with these triggers using powerful tools like @LogRocket. Focusing on a few key sessions will reveal patterns without overwhelming you with data. — 𝗧𝗵𝗲 𝗧𝗵𝗿𝗲𝗲-𝗣𝗮𝘀𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲 Think of it like peeling back layers: each pass reveals more details. 𝗣𝗮𝘀𝘀 𝟭: Watch at double speed to capture the overall flow of the session. ➔ Identify key moments based on time spent and notable actions. ➔ Bookmark moments to explore in the next passes. 𝗣𝗮𝘀𝘀 𝟮: Slow down to normal speed, focusing on cursor movement and pauses. ➔ Observe cursor behavior for signs of hesitation or confusion. ➔ Watch for pauses or retracing steps as indicators of friction. 𝗣𝗮𝘀𝘀 𝟯: Zoom in on the bookmarked moments at half speed. ➔ Catch subtle signals of frustration, like extended hovering or near-miss clicks. ➔ These small moments often hold the key to understanding user pain points. — 𝗧𝗵𝗲 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 + 𝗤𝘂𝗮𝗹𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 Metrics show the “what,” session replays help explain the “why.” 𝗦𝘁𝗲𝗽 𝟭: 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮 Gather essential metrics before diving into sessions. ➔ Focus on conversion rates, time on page, bounce rates, and support ticket volume. ➔ Look for spikes, unusual trends, or issues tied to specific devices. 𝗦𝘁𝗲𝗽 𝟮: 𝗖𝗿𝗲𝗮𝘁𝗲 𝗪𝗮𝘁𝗰𝗵 𝗟𝗶𝘀𝘁𝘀 𝗳𝗿𝗼𝗺 𝗗𝗮𝘁𝗮 Organize sessions based on success and failure metrics: ➔ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗖𝗮𝘀𝗲𝘀: Top 10% of conversions, fastest completions, smoothest navigation. ➔ 𝗙𝗮𝗶𝗹𝘂𝗿𝗲 𝗖𝗮𝘀𝗲𝘀: Bottom 10% of conversions, abandonment points, error encounters. — 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗥𝗲𝗽𝗹𝗮𝘆 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 Make session replays a regular part of your team’s workflow and follow these principles: ➔ Focus on one critical flow at first, then expand. ➔ Keep it routine. Fifteen minutes of focused sessions beats hours of unfocused watching. ➔ Keep rotating the responsibiliy and document everything. — Want to go deeper and get more out of your session replays without wasting time? Check the link in the comments!

Let's talk about e-commerce KPIs that are important, but you may not be tracking. These are great leading indicators to spot if something is amiss and can help you run a more profitable and effective business. 1) Days Between Purchases What is the average number of days between the first and second purchase? In most cases, we are aiming to reduce this over time as customers become much more sticky if they can purchase 2+ times in their lifetimes. A tactical way to close the gap is your post purchase email flows - are you taking advantage of cross-sell/upsell opportunities in high open rate emails such as order and shipment confirmation emails? 2) % of Product Page Views What percentage of your traffic makes it way over to the product pages? We keep an eye on this as a trend in order to see if the quality of our traffic is up to snuff and if the site is developing any unwanted friction between upper level pages vs. pages deeper in the funnel. 3) Add to Cart % & Checkout Passthrough % The cart/checkout experience is one of the most valuable and high impact places on your site. We have often reversed sudden dips in this due to malfunctioning coupon codes, technical issues, pricing presentation issues, etc. and this has saved us and our clients a lot of money! 4) Revenue by New & Returning Customers We analyze trends in this over time to ensure our media mix is achieving its goals and also to see if we have any issues with retaining our customers. We were surprised in the past to see things like slow shipping times heavily affect returning customer revenue over long periods of time. 5) E-Commerce Search % For certain sites/brands, we see great conversion rates (up to 5x higher than average) whenever someone uses the search function on their sites. We aim to slowly increase search usage or experience over time in order to get customers closer to where they need to go. Amazon thinks that this is so critical that the search bar dominates every page on their site. 6) Site load times Site load times are critical to the customer experience and to conversion rates, but are often ignored and not tracked over long periods of time. A key piece of managing this is ensuring third party pixels are behaving well and are not unnecessarily kept on the site as your needs fluctuate and change. 7) Customer NPS / Customer Service Metrics (avg. time to fulfill order, etc) These metrics positively correlate to repeat revenue and order %. It's also a great way to "talk" to your customers since these surveys can be incredibly revealing and surface issues that are holding your business back, such as issues with products being damaged during the shipping process. KnoCommerce is a great tool to execute this! Lastly, we use an extremely customized dashboard from Databox to track and monitor all of these KPIs while being able to see weekly, monthly or quarterly trends. Any other lesser known metrics that are worthy of tracking?

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