Microsoft Clarity vs Hotjar – Optimize Your Website for Free and Improve Conversions

Are you trying to decide between Microsoft Clarity or Hot Jar to analyze user behavior on your website? You're not the only one. Both tools have become benchmarks, but they don't exactly compete in the same space. And if you choose based only on intuition, it's easy to get it wrong. In this video, we're going to look at how they are similar, how they're truly different, and above all, how we use them at CyberClick within a very specific methodology to go from pretty heat maps to decisions that improve conversions. Let's start with the basics. Both Microsoft Clarity and Hot Jar are behavioral analytics tools. They don't replace Google Analytics or your main measurement tool. They complement it. They allow you to see where users click, how far they scroll, what catches their attention, and how they move across your pages. And with the recordings, you're practically sitting next to the user while they browse. And that's where the similarities end. The first big difference is the pricing model. Microsoft Clarity is still completely free. You don't pay for the number of sessions, the number of projects, or the functionalities. If you have a hightraic website or several digital properties you want to measure, this is key. You can record and analyze without having to negotiate the budget every month. Hot Jar, on the other hand, works with scalable paid plans. It has a free version, but with a limited number of sessions. From there, you pay depending on the volume and the type of product you want to use. the observation features, surveys, user interviews. The more traffic you have, and the more you want to research, the higher the bill. This isn't inherently good or bad, but it strongly shapes the kind of projects each tool fits best. The second major difference is their functional focus. Both cover the essentials: heat maps, session recordings, and detection of behaviors like rage clicks or abandonment points. If you only look at that layer, it seems like they do the same thing. But when you go deeper, you notice they've taken different paths. [music] Clarity has leaned heavily into artificial intelligence. Its co-pilot allows you to automatically summarize large volumes of sessions, detect patterns, and answer questions about what's happening on your website in natural language. It also integrates well with the Microsoft ecosystem and tools like PowerBI. And it offers SDKs for mobile apps. If you work with hight traffic websites, projects with apps, and need to move quickly from data to insight, this approach makes a lot of sense. Hot Jar, meanwhile, has increasingly positioned itself as a complete UX research suite. Besides heat maps and recordings, it includes onpage surveys, feedback collection, NPS, conversion funnels, custom dashboards, and even the ability to recruit users for interviews. You don't just see what users do, you can directly ask them what happened. It's especially interesting for product or UX teams working in a continuous research mindset. There's a third layer that often stays in the background but is critical. Data management and privacy. In clarity, standard recordings are kept for 30 days. If you want to keep some longer, you have to mark them as favorites. In that case, they can last up to 13 months. Also, in the European context, the tool depends on consent signals. If the user doesn't accept, the data becomes degraded and part of the analysis stops making sense. And as Microsoft states, the data is used to improve their AI systems in an aggregated and anonymized way. Something to keep in mind for sensitive sectors. Hot Jar has built a large part of its value around privacy and data control. It offers more configuration options, longer retention periods depending on the plan, and specific tools to manage information from individual users. This makes it particularly appealing when your organization is very strict about legal or compliance requirements. Up to this point, we could stay in the field of feature comparisons, but in practice, that's not what makes the difference. What truly matters is what you do with the data. And this is where the way we work at CyberClick comes in. Because our process with Microsoft Clarity isn't based on logging in, checking a few heat maps, and leaving, but on a much more structured system. The first thing we do is prioritize. [music] We don't analyze every page of a website. It would be inefficient and in many cases irrelevant. We start with pages that are strategically important and have enough traffic. The homepage, [music] key services pages, certain campaign landing pages or content we know has a direct impact on the business. The goal is to focus the analysis where changes can make a real difference. Once we have the priority pages defined, the heat maps come into play. They are our first diagnostic layer and tell us what is happening. The click map shows where users interact, whether the main CTA is getting the attention it should, whether secondary elements are capturing too much interaction, or if there are seemingly harmless areas that concentrate many clicks. This is often where the first frustration clicks appear on elements that aren't clickable. Next, we look at the scroll map. This map tells us how far users get and what percentage of traffic sees each content block. It allows us to see, for example, whether the first contact CTA appears in an area that only a small portion of users reach or whether there are sections that cause sharp drop offs in reading. When we see a strong drop between the two segments, there's almost always something in the content design or value proposition that needs reviewing. The third layer is the attention map. Here, we're not talking so much about clicks, but rather where the visual focus is concentrated. On our own website, for example, we use this map to validate whether the attention is focused on the headline and main CTA or if, on the contrary, it drifts toward a decorative image that adds nothing to conversion. When the latter happens, we already have a clear hypothesis about distraction. With these three layers, we get a solid understanding of the what, but it's almost never enough. As soon as we detect something that doesn't add up, many clicks on a non-clickable element, a section that makes users leave, a form that almost no one reaches, we move on to the recordings. That's where the why becomes clear. The recordings allow us to see the user journey in context. How they move through the page, where they pause, how many times they go back, and at what point they decide to leave. It's very different to know that 40% of traffic is lost in a specific block than to see how that block generates doubts forces users to reread several times or makes them return to the menu to look for another path. In Clarity, the ability to record many sessions without worrying about volume gives us room to filter and find behavioral patterns quickly. Once we have heat map and recording data, we activate a set of questions that we always use in our analysis. They're not AI prompts, but prompts for ourselves. questions that force us to turn what we're seeing into concrete hypothesis. We ask ourselves, for example, what the exact objective of that page is and where it breaks down, which elements visually compete with the CTA and what the user expected to happen when clicking a non-clickable element or what specific barriers stopped them from moving to the next step. From this, we get actionable hypotheses, not generic conclusions. Instead of the CTA doesn't work, we formulate something like we believe the main CTA goes unnoticed because it is visually competing with the sidebar block. In the recordings, three out of five users look at that area first and click there. These hypotheses form the basis to propose design changes, adjust the copy, reorganize content, or set up AB test. At this point, the question is no longer just clarity or hotar, but what do you need and what methodology will you apply on top of the tool? Even so, we can outline some quick guidelines. If you work with hightraic projects, have a limited budget for tools, and value using AI to move faster from data to insight, Microsoft Clarity fits especially well. It allows you to record and analyze at scale, integrate the data into the Microsoft ecosystem, and use C-pilot to summarize large volumes of information that would otherwise be hard to review. If however you're part of a product or UX team working in a continuous research mindset, need to launch surveys, measure NPS, build detailed funnels, and conduct user interviews, Hotchart gives you an ecosystem built just for that. You don't just see what's happening, you can ask and collect the user's voice within the same tool with longer data retention and advanced reporting options. And then there's the hybrid option which is more common than it seems. Using clarity as the base for largecale behavioral analysis and complementing it with hot jar on certain pages, projects or phases where you need deeper qualitative research. In many growth and product teams, this combination has become the standard. In our case at CyberClick, we primarily work with Microsoft clarity because it fits very well with the type of projects we manage and the way we like to analyze. We start with priority pages, combine heat maps and recordings, formulate hypotheses, and from there propose businessoriented changes. The tool matters, but what makes a difference is the system you build on top of it. If you want us to review your website with this methodology and analyze together what's happening on your key pages, you'll find more information in the video description. And of course to tell us in the comments which tool you're working with right now, what you like, and what's been hardest for you when interpreting the data. If this content was useful, subscribe to the channel, activate the bell, and we'll see you in the next