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The Smashing Magazine article examines the four levels of customer understanding, highlighting the importance of deeply understanding customer needs, barriers and emotions to improve the customer experience. The levels include demographic context, stated feedback, purchase intent and deeper motivations. The essence of customer experience lies in connecting data to human behavior, directly impacting revenue and customer satisfaction.
Smashing Magazine's article on the four levels of customer understanding touches on an issue that most e-commerce businesses know in theory, but often underestimate in practice: it's not enough to know who your customer is; you need to understand what they are doing, what they are trying to achieve, what is preventing them and what emotion is behind their decision. For an online store, this difference is critical. It's one thing to see that a user abandoned the cart at checkout and another to understand that they didn't feel trusted, that they were afraid of extra costs or that they didn't find a clear return policy. This is exactly where the real improvement of the customer experience starts.
The four levels can be translated practically as follows. First level is the demographic and behavioural context: who the customers are, where they come from, what devices they use, what products they see and where they leave. Second level is what they self-report: reviews, ratings, support questions, survey responses and voice of customer data. Third level is the intent and the actual task they are trying to accomplish, i.e. purchase intent and job-to-be-done: are they buying a gift, comparing prices, looking for reliability or wanting a quick solution to an urgent problem? Fourth level is the deeper motivation: fears, self-image, social proof, the need for security, the desire for convenience, or the expectation that the brand will understand them without tiring them out.
This model helps e-commerce owners to move beyond a superficial reading of analytics. Dashboards show what happened, but rarely explain why it happened. The essence of customer experience is to connect the data to human behavior. If, for example, a product has a lot of views but low cart additions, the problem may be the price, photos, description, lack of reviews or size doubt. If you only see the conversion rate optimization as a technical exercise, you'll be changing buttons and colors. If you see it as customer understanding, you'll improve the message, proof of value, trust and overall experience.
The commercial value of customer experience is not just in the aesthetics of a site or the speed of loading, but in reducing friction and increasing trust at every step of the customer journey. According to Salesforce, 88% of customers say the experience a company provides is as important as its products or services, while 73% expect companies to understand their unique needs and expectations. For an e-shop, these percentages show that competition is no longer just on price. It becomes about convenience, clarity, personalization, consistency and the feeling that the customer doesn't have to struggle with the site to buy.
As shown in the graph below, customer expectations have shifted from a simple transaction to an integrated experience. This means that every product page, every email, every return policy and every checkout message functions as part of the brand promise.
The practical implication for an online store is clear: the better you understand the customer, the more targeted you can invest. If customers find it difficult to choose a size, you don't necessarily need more advertising; you need a better size guide, more compelling content and perhaps user-generated photos. If customers aren't completing a purchase because they're afraid of shipping, the solution isn't just a discount pop-up; it's cost transparency early on. If mobile visitors have a high bounce rate, the problem may be speed, information prioritization or an overloaded interface. In all of these cases, understanding comes before optimization.
At the first level, data from user behavior analytics, first-party data and tools such as GA4, heatmaps, session recordings and in-site search reports show behavioral patterns. Here you map the key flows: from landing page to category page, from product page to cart, from cart to checkout and from checkout to purchase. You're not just looking for percentages; you're looking for discontinuities. For example, if a category has high traffic but low engagement, maybe the merchandising doesn't match the user's intent. If users repeatedly filter by price, the page needs better display of offers or value comparison.
At the second level, customer insights come from what customers say. This is where product reviews, service tickets, live chat conversations, social media comments and responses to short post-purchase surveys come in. The most common pitfall is treating this data as «noise» rather than a strategic asset. A recurring complaint about late delivery, a question about product materials or an objection about returns is a sign that the content is not answering basic doubts. Voice of customer can be translated directly into copywriting, FAQs, email flows and improvements to product pages.
At the third level, you use UX research to understand the purpose behind the behavior. Here, customer personas should not be fictional profiles like «Maria, 34, loves fashion», but functional segments with needs, barriers and decision criteria. For example, one customer may belong to the segment «buys last minute and needs guaranteed delivery», while another may belong to the segment «carefully compares quality and reviews before buying». This form of customer segmentation is much more useful than general demographics because it leads to specific decisions about content, offers, filters, email automation and shipping policy.
At the fourth level, you look at the emotional and social context. The purchase decision is not always rational. A customer may pay more to avoid risk, choose a brand with better after-sales or buy because the product reinforces the image they want to have of themselves. This is where e-commerce personalization takes on substance: it doesn't just mean «suggest similar products», but «show the right message, the right proof and the right path based on the customer's context». To do this respectfully and accurately, zero-party data is needed, i.e. data that the user consciously provides, such as preferences, needs, budget or purchase goal.
McKinsey has documented how strongly personalisation is linked to experience and buyback. The graph below shows that customers not only expect personalized interactions, but are disappointed when they are not present and are more likely to repurchase or recommend the company when personalization works well.
Step 1: Map the customer journey based on actual flows rather than internal assumptions. Start with the key touchpoints: paid ads, organic search, homepage, category pages, product pages, cart, checkout, confirmation email, delivery updates, returns and post-purchase communication. For each step, note the user's goal, the information they need, their potential doubt and the metric that indicates if there is a problem. A proper journey map is not a decorative file in a presentation; it's a prioritization tool for marketing, design, development and customer support.
Step 2: Create a single data collection system. Combine first-party data from purchases, browsing behavior and email engagement with zero-party data from quizzes, preference centers and short surveys. Be careful not to collect data you won't use. Quality is more important than volume. If you ask a customer what product category they are interested in, you need to leverage that answer in product recommendations, content, email flows or landing pages. Otherwise, trust is diminished.
Step 3: Organise a weekly customer insights review. Once a week, the team should look not only at sales and ROAS, but also at customer questions, reviews, inconclusive searches, reasons for returns, abandoned checkout recordings and feedback from support. This is where businesses that are consistently improving stand out from those that are constantly chasing new traffic campaigns to catch up with leaks. Retention strategy starts with understanding the small signs of frustration.
Step 4: Convert the findings into experiments. If you see that users are abandoning at checkout, don't change everything at once. Try metaphor transparency first, then guest checkout, then trust badges, then field simplification. If you find that users are struggling on the product page, try a new description structure, a better photo series, feature comparison, video or more prominent reviews. Each experiment should have a hypothesis, metric, duration and a clear success criteria.
Step 5: Link understanding to content and brand. Customer understanding is not just about UX or CRO. It affects positioning, campaigns, product bundles, email marketing, and even policy pages. If you know your customers are concerned about quality, your product page should respond with materials, warranties, reviews and real photos. If you know they are buying gifts, they need occasion filters, gift wrapping, fast delivery and the ability to change. If you know they are comparing prices, they need proof of value, not just a discount.
The most dangerous mistake is to consider the customer experience as a project that is completed. It is actually a function of the business, like merchandising or service. Customer needs change with seasonality, economic conditions, competitive trends and brand maturity. That's why metrics need to be monitored systematically. For acquisition, look at bounce rate, engagement rate and landing page conversion. For consideration, look at product page engagement, filter usage, add-to-cart and clicks on reviews or size guides. For purchase, look at checkout completion, payment errors, shipping cost drop-offs and average order value. For post-purchase, look at NPS, repeat purchase rate, returns, request resolution time and customer lifetime value.
The Baymard Institute shows in a very practical way why customer understanding should result in checkout optimization decisions. Cart abandonment reasons are not abstract: extra costs, mandatory account creation, lack of trust and slow delivery are specific barriers that can be improved with design, copy, pricing policy and technical implementation.
For an e-commerce team, the next step is to create a common vocabulary around the customer. Marketing should not only talk about campaigns, design only about interfaces, development only about tickets and support only about complaints. These are all different facets of the same system. When the team takes a unified view of the customer experience, decisions become faster and more accurate. TWO DOTS approaches these types of projects at exactly this intersection: strategy, data, UX, content and technical implementation. The value is not in a single change, but in creating a mechanism that continuously learns from the customer and turns that learning into better experiences, more trust and higher profitability.
If we keep one conclusion from the four levels of customer understanding, it is that the customer is not a line on a report. He is a human being with a goal, doubts, limited time and alternatives. The e-shop that understands him better will write more convincingly, plan more clearly, sell more effectively and build relationships that last beyond the first purchase. This is customer experience as a competitive advantage, not as an aesthetic detail.
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The four levels of customer understanding are: demographic and behavioural context, stated insights from customers, the intention and actual work they are trying to complete, and deeper motivations such as fears and self-image.
Customer experience improves trust and reduces friction in the customer journey, increasing the likelihood of purchase and repurchase. A good customer experience is just as important as the product itself.
Improving conversion rate requires understanding customers and the barriers they face. Focus on issues such as cost transparency, improving product descriptions and building trust through reviews and guarantees.
Personalisation reinforces the feeling that the customer is understood and deserves attention. Customers are more likely to repurchase and recommend the brand when interactions are tailored to their needs.
Data from analytics, reviews, and customer surveys reveal patterns of behaviour and preferences. These insights can lead to optimization strategies that meet real customer needs.
The first step is to map the customer journey based on actual data rather than assumptions. Identify key touchpoints and analyze the needs and barriers customers face at each stage.
Use customer insights to identify common problems and design improvement experiments. Focus on issues such as trust, ease of navigation and providing clear information to improve the user experience.
With UX research, proper checkout flow and conversion optimization, an e-shop can increase sales without increasing advertising.
