Understanding User Behavior On E-commerce Platforms

User behavior is more than what they say - it’s what they do. While surveys and usability tests provide valuable insights, log analysis reveals real interaction patterns, helping UX researchers make informed decisions based on data, not just assumptions. By analyzing interactions - clicks, page views, and session times - teams move beyond assumptions to data-driven decisions. Here are five key log analysis methods every UX researcher should know: 1. Clickstream Analysis - Mapping User Journeys Tracks how users navigate a product, highlighting where they drop off or backtrack. Helps refine navigation and improve user flows. 2. Session Analysis - Seeing UX Through the User’s Eyes Session replays reveal hesitation, rage clicks, and abandoned tasks. Helps pinpoint where and why users struggle. 3. Funnel Analysis - Identifying Drop-Off Points Tracks user progression through key workflows like onboarding or checkout, pinpointing exact steps causing drop-offs. 4. Anomaly Detection - Catching UX Issues Early Flags unexpected changes in user behavior, like sudden drops in engagement or error spikes, signaling potential UX problems. 5. Time-on-Task Analysis - Measuring Efficiency Tracks how long users take to complete actions. Longer times may indicate confusion, while shorter times can suggest disengagement.

Your customers are lying to you. Not intentionally. They just don't know what they actually want. Last week, a SaaS founder showed me their on-site survey data. 87% of respondents wanted "more features." Their session recordings told a different story: visitors couldn't find the features that already existed. This happens everywhere... what people *say* and what they *do* are different universes. For example, during a recent project with Adobe, we discovered something shocking: survey respondents begged for advanced filters. But heatmaps showed they never clicked the basic filters already there 🤦🏻♂️ We ignored the surveys. We followed the behavior. Revenue jumped. In my latest book "Behind The Click," I detail the psychological forces where users aren't conscious of their real motivations: ↳ They tell you they want lower prices. Their behavior shows they'll pay more for convenience. ↳ They say they want more options. Their behavior shows paralysis with current choices. That's why The Good | Digital Experience Optimization's methodology ignores opinions. We observe actions. We measure what users *do*. Not what they *claim*. Otherwise, despite endless survey data, conversion rates will stay flat. Your survey says users want faster checkout. Your data shows they abandon at shipping options. Different problems. Different solutions. Don't optimize for fictional preferences. Watch what users do for one hour. Learn more than 1,000 survey responses can teach you. Behavior beats intention every single time. Trust their clicks, not their words.

Look at what they do, not just what they say. User behavior is how users interact with and use software. It includes things like: → how people navigate the interface → which features people use most often → the order in which people perform tasks → how much time people spend on activities → how people react to prompts or feedback Product managers and designers must understand these behaviors. Analyzing user behavior can enhance the user experience, simplify processes, spot issues, and make the software more effective. Discovering the "why" behind user actions is the key to creating great software. In many of my sales discussions with teams, I notice that most rely too heavily on interviews to understand user problems. While interviews are a good starting point, they only cover half of the picture. What’s the benefit of going beyond interviews? → See actual user behavior, not just reported actions → Gain insights into unspoken needs in natural settings → Minimize behavior changes by observing discreetly → Capture genuine interactions for better data → Document detailed behaviors and interactions → Understand the full user journey and hidden pain points → Discover issues and opportunities users miss → Identify outside impacts on user behavior Most people don't think in a hyper-rational way—they're just trying to fit in. That's why when we built Helio, we included task-based activities to learn from users' actions and then provided follow-up questions about their thoughts and feelings. User behaviors aren't always rational. Several factors contribute to this: Cognitive Biases ↳ Users rely on mental shortcuts, often sticking to familiar but inefficient methods. Emotional Influence ↳ Emotions like stress or frustration can lead to hasty or illogical decisions. Habits and Routine ↳ Established habits may cause users to overlook better options or new features. Lack of Understanding ↳ Users may make choices based on limited knowledge, leading to seemingly irrational actions. Contextual Factors ↳ External factors like time pressure or distractions can impact user behavior. Social Influence ↳ Peer pressure or the desire to conform can also drive irrational choices. Observing user behavior, especially in large sample sizes, helps designers see how people naturally use products. This method gives a clearer and more accurate view of user behavior, uncovering hidden needs and issues that might not surface in interviews. #productdesign #productdiscovery #userresearch #uxresearch

In talking to ecommerce marketers in and around my network, community, and customers, here are 6 of the most important things I discovered about their shoppers. 1. Redirecting shoppers in the shopping journey is hurting conversions. - They have very little patience. They’re dropping off if they find too many steps in the buying journey. - The fewer & more direct paths to purchase, the better. Amazon has nailed it in providing a smooth buying journey. 2. If they can complete purchases directly in a channel, they’ll do it. - Apps like TikTok and Instagram have already begun experimenting with this, and it’s working. - Very soon we will enter into an era where all messaging channels will become avenues to shop end-to-end. 3. The search bar on the website is extremely valuable. It's where 50%+ of shoppers start their journey. It’s a huge deal-breaker if shoppers can't find what they're looking for. - Shoppers often use the search bar to search for something specific. If they don’t find the product, they drop-off your website/app. - The recommendations that come while searching need to be as relevant in-session as possible to keep the shoppers engaged. This improves the odds of conversions. 4. They are willing to share their personal details to get better offers - Only if they will get special discounts or offers. Anything that has a strong incentive that benefits them. - If they receive good benefits from loyalty programs and the programs meet their expectations, they’ll become lifelong customers. - These sound obvious, but if this is still a concern even today, it only shows that many marketers still don’t take this path seriously. 5. Many shoppers still receive irrelevant recommendations. This is pushing them away cause of bad experiences. - This means that shopper data that is being collected is broken and inaccurate. - It also indicates that marketers using automation tools to send messages and gather data are not good enough. They need to upgrade to better ones that really understand shopper intent, more importantly, with the products that are being shopped. 6. Over-personalizing the experience is counterintuitive. - Shoppers feel the brands are being intrusive and creepy. - This indicates that the shopper data is being abused without respecting privacy. Here are my biggest takeaways 🛒 Shoppers want convenience at every step in their shopping journey. 💡 Marketers are aware of this. They know what they have to do. They’re just not aware of the right marketing tools to solve this problem. 🔎 These tools can channelize the data customers willingly share about both their intent and the type of product they'd like to purchase, to create relevant, contextual, and even predict recommendations that make it easy for their shoppers. 💰 Kill the redirect and the subsequent loss of intent. Convert in channel! It’s 2024! The shopping experience has evolved. Adapt or die.

Success in e-commerce boils down to one fundamental principle: Understanding and aligning with your customers' intent. The introduction of an Amazon Science Papers Engagement-based Query Ranking (EQR) model provides a transformative approach, particularly for high-consideration (HC) queries, which reflect a shopper’s deeper decision-making journey. Here’s how EQR is revolutionizing the way businesses approach search optimization and customer engagement: 1️⃣ High-Consideration Queries Are Goldmines: HC queries, like “best DSLR cameras,” indicate a customer’s readiness to make informed decisions. Unlike generic searches, these queries offer invaluable insights into customer intent, helping businesses deliver meaningful, context-rich content that fosters trust and drives conversions. 2️⃣ Traditional Keyword Strategies Fall Short: Most strategies focus on frequency or popularity, often prioritizing low-consideration terms (e.g., “rubber mats for gym”). This approach overlooks HC queries’ potential to engage intent-driven shoppers, leading to wasted resources and missed opportunities. 3️⃣ EQR’s Precision in Ranking Keywords: Amazon’s EQR model shifts the focus from volume to value by ranking keywords based on engagement potential. It considers behavioral metrics (e.g., click-through rates), financial signals (e.g., sales volume), and catalog insights (e.g., product availability), achieving 96% accuracy in identifying impactful queries. 4️⃣ Proven Results from EQR: In live deployments, EQR-selected queries increased engagement by 6% compared to human-selected keywords. This scalability and precision save time, reduce costs, and maximize the ROI of e-commerce strategies. 5️⃣ Actionable Steps for Businesses: Identify HC keywords using behavioral and financial metrics. Develop tailored content such as buying guides and FAQs for these queries. Continuously refine strategies based on customer interactions, ensuring relevance and scalability. ✅ From Sellers to Trusted Advisors: EQR-inspired strategies enable businesses to move beyond reactive keyword optimization, fostering deeper engagement with high-intent shoppers. By focusing on what truly matters to customers, brands can achieve sustainable growth, build trust, and establish themselves as indispensable resources in the customer journey. 🔍 How is your business addressing high-intent customer queries today? Let’s discuss innovative approaches to transform search optimization into meaningful customer connections. #amazonseo #amazonscience #amazonsearch #ecommerce #keywordoptimization #seostrategies #optimization #searchterms #amazon #sellerstrategies