User Experience for SaaS Products

Do you sometimes feel frustration, as you are building a product to get the management off your back, rather than address the users? Here are 6 ways to become user-centric again: 1) Prioritize in a transparent way This is a great place to start. If your backlog is prioritized based on data and potential opportunity, risk, and cost, it will be easier to put forth user-centric initiatives ahead of those that came from upstairs. At the very least, you will have a good basis for an educated discussion. 2) Utilize users' perspective using user stories and personas If your team understands the users and their problems, it will be easier to craft something great that will later appeal to the same users. Just keep up the empathy of creating something by people for other people, and not get some metric magically go up! 3) Make user feedback public If everyone in the company can see the themes that come from user feedback, it will be way harder to ignore it in favor of some corporate nonsense. Let those voices be heard by everyone! 4) Have the NPS and user ratings at the forefront The same goes for a single metric representing the general product sentiment. If the number is low or, worse, is going down and everyone can see that, the responsible Product Manager has to react. 5) Focus on your product goals Now, upstairs mandates might not be the only distraction you face when trying to improve your product. To survive them all, focus on one thing: your product goals. This will allow you to demonstrate you are doing what you are asked for and you can use user feedback and points 1-4 to pursue those goals. Thus, it's like killing 2 birds with 1 stone. However, you can also simply: 6) Have the confidence to say "No" Not all company/legal/management requests can be ignored. Sometimes changing the law or a wider company initiative will require you to comply and that is OK! However, there will also be times when someone will try to force your compliance. This is where you need to be confident, and exercise your Product Manager's independence, especially when there is no data to support a specific request. There you go! My 6 ways you can become a user-centric Product Manager. How about you? Do you address your users or your management first and foremost when developing your product? Sound off in the comments! #productmanagement #productmanager #usercentricity

Common launch mistake: Rolling out new features to ALL customers. Pushing out a new feature to a sizable customer base comes with risks: - Higher support volume if things go south, affecting many. - Lost opportunity to refine the product with a focus group. - Difficulty in rolling back changes in certain cases. That's why products, especially those with huge customer counts, adopt a gradual rollout strategy to mitigate risk. There are multiple options here like: ✔️ Targeted roll-out Selective release to specific users or accounts. ✔️ Future-cohort facing Only new sign-ups get the feature, existing users keep legacy version ✔️ Canary release Test with a small group first, then expand after confirming it's safe. ✔️ Opt-in beta Users voluntarily choose to try new features before official release. ✔️A/B rollout Two different versions released to different groups to compare performance. ✔️Switcher Everyone gets new version by default but can temporarily switch back to old version. ✔️Geo-fenced Features released to specific geographic regions one at a time. Some factors to consider: ✅ User base capabilties How savvy is your user base? How adaptive would they be the change you're rolling out? If you need to ease them over time, think about a switcher or an opt-in beta. ✅ Complexity How complex is the product update and is it in the way of a critical path? If it's a minor update, a universal deployment will suffice. However, you might opt for an opt-in or canary release for more complex changes. ✅ Risk Assessment What's the risk profile of the update? Ex: If it's performance-intensive and could affect server load, consider using a phased release to observe patterns as you open the update upto more users. ✅ Objective Is this a revamped version of an existing product use case? Do you want to experiment which works better? Strategies like canary releases or A/B testing are valuable in this scenario. ✅ Target users Do you have different user behaviors or preferences across markets or geographies of operation? Do certain cohorts make more sense than others? Think about geo-fenced roll-outs (we used to use this a lot at Bayt when launching job seeker features). --- What rollout strategies do you use for your product?

𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗽𝗿𝗶𝗰𝗲 𝗼𝗳 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗢𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗶𝗻 𝗣𝗿𝗼𝗰𝘂𝗿𝗲𝗺𝗲𝗻𝘁? Cognitive overload happens when the mental effort required to use a system or process exceeds the user’s capacity. In Procurement, this happens when tools are overly complex or poorly designed. 𝗧𝗵𝗲 𝗰𝗼𝗻𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲𝘀 𝗼𝗳 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗢𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗮𝗿𝗲 𝘀𝗶𝗴𝗻𝗶𝗳𝗶𝗰𝗮𝗻𝘁 and range from a persistent operational inefficiency, more errors, low adoption of complex solutions and ultimately a risk for employee burnout. While some level of complexity is inevitable to support advanced functionality, the way tools and workflows are designed plays a crucial role for their usability, how effectively users can engage with them and the level of mental load they create. The Cognitive Load Theory (CLT), introduced by John Sweller in the 1980s, provides a framework for reducing mental strain by focusing on how users learn, process and retain information. The CLT identifies three types of cognitive load and offers insights into how Procurement Systems can be optimised for usability: 1️⃣ 𝗜𝗻𝘁𝗿𝗶𝗻𝘀𝗶𝗰 𝗟𝗼𝗮𝗱 which arises from the inherent complexity of the task or information. In Procurement, examples include multi-dimensional RFP scoring or the authoring of complex contracts and their SLAs. 𝗛𝗼𝘄 𝘁𝗼 𝗵𝗮𝗻𝗱𝗹𝗲 𝘁𝗵𝗶𝘀? Break down and simplify complex tasks into manageable steps using modular workflows, and provide pre-configured templates for common scenarios. 2️⃣ 𝗘𝘅𝘁𝗿𝗮𝗻𝗲𝗼𝘂𝘀 𝗟𝗼𝗮𝗱 stemming from poor system design, irrelevant information or inefficient processes. For example, clunky interfaces, unnecessary workflow steps or dashboards that hide insights under excessive detail. 𝗛𝗼𝘄 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝘁𝗵𝗶𝘀? Minimise Extraneous Load with a functional user interface design, using smart visualisations and streamlining workflows. 3️⃣ 𝗚𝗲𝗿𝗺𝗮𝗻𝗲 𝗟𝗼𝗮𝗱 resulting from the cognitive effort that directly supports learning and mastery. Examples include tooltips, clear guidance, and onboarding processes that make systems easier to navigate. 𝗛𝗼𝘄 𝘁𝗼 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗵𝗶𝘀? Enhance Germane Load with role-specific training, embedded tool tips & intuitive help features accelerating user learning. All three types can lead to a reduced capacity of employees to be able to operate effectively and potential negative consequences and mental stress. 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗼𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗰𝗼𝗺𝗲𝘀 𝗮𝘁 𝗮 𝗵𝗶𝗴𝗵 𝗽𝗿𝗶𝗰𝗲. 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝘄𝗵𝗶𝗰𝗵 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿 𝗮 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗱𝗲𝘀𝗶𝗴𝗻 and optimise their cognitive load levels by unveiling tasks step by-step, simplifying design and providing helpful learning features, 𝗵𝗮𝘃𝗲 𝗮 𝗵𝗶𝗴𝗵𝗲𝗿 𝗰𝗵𝗮𝗻𝗰𝗲 𝘁𝗼 𝘁𝘂𝗿𝗻 𝗳𝗿𝗼𝗺 𝗮 𝗵𝗲𝗮𝗱𝗮𝗰𝗵𝗲 𝘁𝗼 𝗮 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗯𝗼𝗼𝘀𝘁𝗲𝗿. ❓How do you think can solutions be humanised to reduce cognitive load. ❓What else helps to generate a good usability and user experience.

A Director of UX at a SaaS company recently shared a painful calculation with me: Their team of 3 researchers spent 75% of their time on manual analysis. At an average salary of $150K, that's nearly $300K annually spent on analyzing data. But the bigger cost? Critical product decisions made without insights because "we can't wait for research." Most UX and product teams are trapped in a costly cycle of inefficiency: Conduct user interviews → Spend 30+ hours manually analyzing → Create a report → Make decisions based on gut feeling before the report is ready. After watching UX teams struggle with this for years, I've identified the core problem: research insights are treated as artifacts, not conversations. This is why we built AI Wizard into Looppanel - a conversational research companion that transforms how teams extract value from user research. Instead of static reports and manual analysis, AI Wizard allows anyone to simply ask: "What pain points did users mention about the onboarding process?" "Summarize the key recommendations users suggested for improving the checkout flow." "What were the main differences in how novice users versus power users approached this task?" You start by selecting from templates like Pain Points, Recommendations, or Summary. AI Wizard instantly analyzes your project data and engages in a natural conversation - complete with follow-up questions to dig deeper into specific areas. The way I see it, AI Wizard helps solve 3 critical problems: 1. The speed-to-decision problem Waiting weeks for analysis means missing decision windows. AI Wizard delivers TLDR overviews in seconds, not days. 2. The iteration problem No more spending time on data again because of a follow-up question. Answer unexpected stakeholder questions on the spot instead of scheduling another week of analysis 3. The tailored communication problem Automatically format the same insights for different audiences: executives get metrics, designers get details, all without rebuilding presentations. With AI Wizard, your team can: → Start conversations with templates like Pain Points, Recommendations, or Summary → Ask follow-up questions to dig deeper → Get insights from across your entire research repository in seconds → Democratize access to insights throughout your organization Will your team be leading this transformation or catching up to it? If you want to make the shift, sign up for a personalized demo here: https://bit.ly/42PEOlX

We often say “people don’t buy products, they buy feelings.” But here’s the twist; people don’t just buy feelings. They experience them through design. Every swipe, scroll, haptic pulse, sound cue, and animation is a moment of emotional choreography. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • FEATURES DON’T CONVERT - FEELINGS DO A smooth interface isn’t enough anymore. What converts is the emotion the experience evokes - relief, delight, confidence, or even belonging. You don’t remember the app that loaded fastest. You remember the one that made you smile when it did. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • FEELINGS DRIVE DECISIONS (AND REVENUE) → Cognitive fluency: Interfaces that are simple and predictable “feel right,” which reads as trustworthy and high quality. → Loss aversion: Users work harder to avoid losing what they’ve earned (credits, streaks, carts) than to gain something new. → Peak–End rule: People remember the emotional high point and the ending. Design your peaks and endings like they’re your brand. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • MICRO-INTERACTIONS = MICRO-EMOTIONS → Apple’s haptics reduce uncertainty and signal precision (visceral satisfaction confidence). → Netflix previews create open loops (Zeigarnik effect) that pull you into a session before you choose. → Duolingo blends encouragement + accountability: streaks (goal-gradient), “streak freeze” (loss aversion), leaderboards (social proof), and the owl’s tone (gentle shame → commitment). • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • CLOSE THE “AFFECTIVE GAP” BETWEEN GOOD AND GREAT Good brands ship usable features. Great brands shape feelings across the whole journey: → Visceral layer (first glance): Reduce cognitive load; make the next action obvious. → Behavioral layer (in use): Show progress, provide reversible choices, celebrate milestones. → Reflective layer (memory): End on a high, summarize achievement, invite sharing. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • MAKE EMOTION MEASURABLE Feelings aren’t fluffy if you pick the right lenses: → Confidence Task success without help, drop in abandonment at critical steps. → Progress Time-to-first-value, streak retention, return after day 7/30. → Belonging/Recognition Organic shares, community replies, unsolicited reviews. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • When emotion becomes part of UX, you don’t just create usability. You create affinity. Because features are copied. But feelings? Those are proprietary. ------------------------------------------ 💬 Let me know what you think 🔗 Share if helpful! 👉 Follow Anand Sankara Narayanan for brand stories & strategies ------------------------------------------

How do you figure out what truly matters to users when you’ve got a long list of features, benefits, or design options - but only a limited sample size and even less time? A lot of UX researchers use Best-Worst Scaling (or MaxDiff) to tackle this. It’s a great method: simple for participants, easy to analyze, and far better than traditional rating scales. But when the research question goes beyond basic prioritization - like understanding user segments, handling optional features, factoring in pricing, or capturing uncertainty - MaxDiff starts to show its limits. That’s when more advanced methods come in, and they’re often more accessible than people think. For example, Anchored MaxDiff adds a must-have vs. nice-to-have dimension that turns relative rankings into more actionable insights. Adaptive Choice-Based Conjoint goes further by learning what matters most to each respondent and adapting the questions accordingly - ideal when you're juggling 10+ attributes. Menu-Based Conjoint works especially well for products with flexible options or bundles, like SaaS platforms or modular hardware, helping you see what users are likely to select together. If you suspect different mental models among your users, Latent Class Models can uncover hidden segments by clustering users based on their underlying choice patterns. TURF analysis is a lifesaver when you need to pick a few features that will have the widest reach across your audience, often used in roadmap planning. And if you're trying to account for how confident or honest people are in their responses, Bayesian Truth Serum adds a layer of statistical correction that can help de-bias sensitive data. Want to tie preferences to price? Gabor-Granger techniques and price-anchored conjoint models give you insight into willingness-to-pay without running a full pricing study. These methods all work well with small-to-medium sample sizes, especially when paired with Hierarchical Bayes or latent class estimation, making them a perfect fit for fast-paced UX environments where stakes are high and clarity matters.

25% of their sprint was invisible. Nobody budgeted for it. Nobody tracked it. Nobody even knew it existed. A SaaS team asked me why velocity kept dropping. "We're shipping. We're just... not getting anywhere." Same features taking longer. Same bugs coming back. Same complaints about things that "should just work." They tracked everything that mattered: Revenue. Churn. Conversion. But they weren't tracking what was bleeding them. I spent a week mapping where time actually went. What I found: Cost 1: Regression loops Every new feature broke an old one. Fix it. Break something else. 25% of every sprint was just running in circles. The PM showed me the pattern: "This checkout bug? We fixed it in March. And May. And last week." Three times. Same bug. Nobody connected the dots. Cost 2: Navigation chaos Users couldn't find things. Support calls doubled. One agent told me: "Half my day is answering 'where is...?' questions." The product worked. Users just couldn't navigate it. Cost 3: Onboarding cliff 7 steps before any value. 40% of users quit before step 3. Marketing blamed product. Product blamed marketing. Both missed the real problem: asking too much, too soon. Cost 4: Design debt No shared components. Every feature built from scratch. Hidden rework eating every sprint. Nobody budgeted for it because nobody named it. Four invisible costs. All compounding. All unmeasured. The team wasn't slow. They were fast — in four different directions at once. We didn't add more sprints. We fixed the leaks. Modular components. Shared patterns. Logic that repeats. Velocity came back. Not from working harder. From removing friction nobody could see. Here's what I've learned: You can't optimize what you don't measure. And you can't measure what you haven't named. Which of these four is bleeding YOUR team right now?

At Clueso (YC W23), we get tens of demos booked with every new feature announcement! Here are some learnings on how to announce product updates to generate maximum impact. As a SaaS company, adding new functionalities & continuously improving your product is very essential. But equally important is how you announce these updates to keep your users informed and engaged. Here’s how you can make your updates more impactful: 🎥 Keep it Visual Users prefer quick, digestible content. Videos and GIFs are perfect for demonstrating new features. Whenever you’re announcing a new feature, make sure to have an engaging launch video! We get 25000+ engagements on our launch posts with videos. 📝 Be Concise When sharing a new update, focus on the new functionalities and their benefits. Keep your language simple and avoid jargon. Focus on what, who and how. What problem are you solving with the new update, who are you solving it for, and how does the new update solve for it. 📢 Spread the Word With any new update, your goal is to increase the product adoption from existing customers and get new prospects interested in your product. To achieve this, it's very important to share the announcement on the right channels: - In-App Notifications: Make these concise and action-oriented to guide users directly to try the new feature or update. A clear call-to-action button, such as "Try it Now", can increase engagement. - Knowledge Base: As your customers go to your knowledge base to learn about any feature, it’s important to keep this updated with all the new features. - LinkedIn, X: Along with the feature announcement in the post, share the journey of developing the new feature and user feedback that led to its creation. Posting on social platforms is also a great way of getting inbound leads. - Blogs: Write blogs explaining the new updates and customer feedback that led to developing the new features. These can help with bringing in organic traffic when prospects are searching for similar functionalities. - Support channels: If you use Slack or Teams channels for communicating with your customers, they’re a great place to share the product updates, initiate discussions and get useful feedback from your customers. - Emails and Newsletters: Write compelling subject lines, use bullet points to highlight key updates, embed GIFs showcasing the new updates. 💬 Engage Post-Announcement Engage with your customers and prospects after the announcement by answering questions and gathering feedback. This helps reinforce the value of the update and improves customer experience. Analyze engagement metrics to understand how your announcements are received and where you can improve. Timing is also crucial. Announce updates early in the week when users are planning their tasks, and avoid major holidays to ensure your message doesn’t get lost in the noise. Check out this detailed blog we wrote: https://lnkd.in/dDcERDaJ #saas #startups #productmarketing

Most UX teams have been there: standing in front of a wall of sticky notes, surrounded by user quotes and caffeine, trying to decide if “Goal Oriented Greg” and “Curious Carla” are genuinely different people or just the same imaginary user with better handwriting. Persona discovery sessions like this often feel productive, the colors, the discussions, the post-its forming patterns, but deep down, we know something is off... The process is usually more art than science, more consensus building than discovery. It produces personas that sound nice in presentations but rarely hold up when real users start behaving unpredictably. Good news?! There is a more rigorous way to approach this, one that turns persona creation from a creative exercise into an analytical process grounded in evidence. Instead of guessing who your users are, you can identify them empirically by examining their real behaviors, motivations, and characteristics across your datasets. This is where clustering analysis becomes invaluable, allowing your data to uncover the story of your users on its own. Clustering uses statistical algorithms to uncover patterns and similarities across multiple dimensions of user data, revealing natural groups that exist beneath the surface. These are not personas invented in a meeting; they are personas discovered in the data. Here is how it works in practice. You begin by gathering rich, multidimensional data, including behavioral metrics. After cleaning and preparing your data, you apply a clustering algorithm such as K Means, Hierarchical Clustering, or Gaussian Mixture Models. These methods analyze the combined patterns across all features and group users who are statistically similar into clusters. Each cluster represents a group of people who share distinctive traits, perhaps they are highly efficient but disengaged, or slower but deeply curious. From there, you interpret and label these clusters in human terms. The data gives you the structure, and your UX insight gives it meaning. You might visualize the results, examine which variables most differentiate each group, and build out personas that reflect the real diversity within your audience. These personas are no longer fictional composites; they are data backed archetypes that show how meaningful subgroups actually behave, think, and feel. The benefits are substantial. Clustering eliminates much of the bias that comes from relying on small samples or internal intuition. It exposes hidden user types that might never emerge from interviews alone, such as a quiet but influential group of users whose needs are consistently overlooked. It also creates alignment across teams because the evidence is transparent and reproducible. When you present personas derived from clustering, you can trace every insight back to data, not opinion. #PersonaDiscovery #UXResearch #DataDrivenDesign #CustomerSegmentation #ProductStrategy #UserExperience #QuantitativeUX

Good design is more than problem-solving. It creates an emotional connection with users. But to do so, it has to be useful and usable, have personality, and communicate that through design. 1. Useful and usable ------------------------- Unless your product is useful and usable, the surface-level delight will turn into frustration. A useful product… Solves a problem or fulfils a need. It has a specific purpose and provides value to the user. It’s practical and functional and helps them achieve their goals. Some methods to determine usefulness: - Conduct interviews to understand your customers' needs, goals, and pain points. - Study similar products to identify gaps and opportunities. - Examine usage patterns and trends that indicate whether goals were achieved. - Review support tickets and queries to identify common issues and unmet needs. A usable product… Is intuitive and easy to navigate, with clear and consistent interfaces. Completing tasks requires minimal effort on the part of the user. Some methods to determine usability: - Performing a heuristic evaluation. - User testing your prototypes. - Gathering feedback from actual users via surveys, interviews and feedback forms. - Analysing metrics such as task completion rates, time on task, and error rates. 2. Personality ------------------------- By giving a product a distinct personality, it can create an emotional connection with the user, making it more engaging. Here are some examples: • Playful: users smile & enjoy themselves. • Attractive: visually appealing via imagery and colours. • Natural: comfortable and intuitive, feels familiar. • Personal: an experience adapted to the individual user. • Empowering: enables the user to achieve results beyond their expectations. • Friendly: warm and approachable, the user feels welcome and at ease. • Trustworthy: secure, reliable, sense of confidence. • Innovative: creates excitement and curiosity, the user feels inspired. • Sophisticated: elegant and refined. Consider your product and your target audience. The personality of a banking app will be different from that of a learning app. They are not mutually exclusive; you can aim for friendly and empowering. 3. Communicate via design ------------------------- Some of the ways your designs can communicate your product’s personality and add delight to the experience: • Microcopy • Animations • Illustrations • Gamification • Photography • Microinteractions “Design doesn’t need to be delightful for it to work, but that’s like saying food doesn’t need to be tasty to keep us alive” ― Frank Chimero, The Shape of Design Ps., if you're looking for more frameworks for communicating the value of design, I'm teaching a course next month to help you become a more strategic partner. Learn more and sign up here; enrollment closes in a couple of weeks: https://lnkd.in/dnvcfR5h