Developing Experience-Focused KPIs

🍱 How To Design Effective Dashboard UX (+ Figma Kits). With practical techniques to drive accurate decisions with the right data. 🤔 Business decisions need reliable insights to support them. ✅ Good dashboards deliver relevant and unbiased insights. ✅ They require clean, well-organized, well-formatted data. ✅ Often packed in a tight grid, with little whitespace (if any). 🚫 Scrolling is inefficient in dashboards: makes comparing hard. ✅ Start with the audience and decisions they need to make. ✅ Study where, when and how the dashboard will be used. ✅ Study what metrics/data would support user’s decisions. ✅ Explore how to aggregate, organize and filter this data. ✅ More data → more filters/views, less data → single values. 🚫 Simpler ≠ better: match user expertise when choosing charts. ✅ Prioritize metrics: key insights → top left, rest → bottom right. ✅ Then set layout density: open, table, grouped or schematic. ✅ Add customizable presets, layouts, views + guides, videos. ✅ Next, sketch dashboards on paper, get feedback, iterate. When designing dashboards, the most damaging thing we can do is to oversimplify a complex domain, or mislead the audience. Our data must be complete and unbiased, our insights accurate and up-to-date, and our UI must match users’ varying levels of data literacy. Dashboard value is measured by useful actions it prompts. So invest most of the design time scrutinizing metrics needed to drive relevant insights. Bring data owners and developers early in the process. You will need their support to find sources, but also clean, verify, aggregate, organize and filter data. Good questions to ask: 🧭 What decisions do you want to be more informed on? (Purpose) 😤 What’s the hardest thing about these decisions? (Frustrations) 📊 Describe how you are making these decisions? (Sources) 🗃️ What data helps you make these decisions? (Metrics) 🧠 How much detail is needed for each metric? (Data literacy) 🚀 How often will you be using this dashboard? (Value) 🎲 What constraints should we know about? (Risks) And, most importantly, test dashboards repeatedly with actual users. Choose key tasks and see how successful users are. It won’t be right at first, but once you get beyond 80% success rate, your users might never leave your dashboard again. ✤ Dashboard Patterns + Figma Kits: Data Dashboards UX: https://lnkd.in/eticxU-N 👍 dYdX: https://lnkd.in/eUBScaHp 👍 Ethr: https://lnkd.in/eSTzcN7V Orange: https://lnkd.in/ewBJZcgC 👍 Semrush: https://lnkd.in/dUgWtwnu 👍 UKO: https://lnkd.in/eNFv2p_a 👍 Wireframing Kit: https://lnkd.in/esqRdDyi 👍 [continues in comments ↓]

After designing hundreds of business dashboards, I keep coming back to these four patterns: Tall + Scrolly Stack everything vertically, organized by metric family, and let people scroll to their level of depth. Best for mobile viewing and email delivery with basic chart types that doesn't require instructions. Where I've seen this work: New product/feature introductions where audiences are different levels (executive to operators) and functions. BANs + Decomp Big numbers that focus attention and breakdowns that show differences. For when you've identified the important metrics, but want to show segment granularity. Switch group-by dimension while maintaining familiar layout. Where I've seen this work: Operational monitoring for teams that have ownership of metric outcomes. Sankey + Wide Table Flow diagram establishes a map of the whole system and reference tables show details. For diagnosing conversion and retention patterns across nodes and segments to know where to optimize. Where I've seen this work: Growth teams figuring out behavior across complex funnels and overlapping segments. Potential Show what you could be delivering versus what you're actually delivering. Makes the gap between current performance and available capacity visible. Where I've seen this work: Operational teams that have a clear action to take, but limited time. What each of these have in common: - Establish big picture awareness, but direct small picture action (think global, act local) - Strengthened by KPI ownership - Act as a prioritization mechanism Organizations often start with one dashboard trying to serve everyone, then evolve into multiple dashboards with different patterns for different groups. The more established the business, the more discrete the problems being solved are. That means early on, you go from optic oriented communications to more optimization oriented direction. I've found that organizations lack a portfolio strategy for their analytics interfaces, they take templates from one context and try to apply them to another OR they try to combine use cases together into a singular dashboard because they only have budget for one but multiple stakeholders with different needs, so they get a flying-boat-car of compromises. Some data work and analytics are going to be a cost of doing business, like reporting that just keeps everyone informed. While other data work is a strategic bet. The challenge is that some analytics deliver hard value you can measure in dollars, while others provide soft value like better collaboration and shared understanding that's difficult to quantify. Most organizations don't think about this mix deliberately. #dataAnalytics

Your customer journey map is missing the 8 touchpoints that matter most. You've optimised your ads, polished your landing pages, and A/B tested your emails to death. But whilst you've been obsessing over the obvious touchpoints, your customers have been forming opinions about your brand in places you've completely overlooked. These hidden moments of truth determine whether customers stick around or silently disappear. The good news? Your competitors are probably ignoring them too. 1. Pre-awareness Influences • What it is: Social conversations & word-of-mouth before formal brand discovery • Why it's missed: Difficult to track & attribute • Optimisation tip: Create shareable content specifically designed for peer-to-peer sharing • Impact potential: ⭐⭐⭐⭐ 2. Post-Purchase Onboarding • What it is: The critical first 24-48 hours after purchase when buyers seek validation • Why it's missed: Teams focus on acquisition, not retention • Optimisation tip: Create "success accelerator" emails with usage instructions • Impact potential: ⭐⭐⭐⭐⭐ 3. Product Documentation • What it is: Help guides, FAQs, & support materials • Why it's missed: Often delegated to technical teams without marketing input • Optimisation tip: Inject brand personality into help documentation • Impact potential: ⭐⭐⭐ 4. Customer Support Interactions • What it is: The conversations with service teams that shape perception • Why it's missed: Viewed as cost center, not marketing opportunity • Optimisation tip: Create scripts that highlight complementary products/features • Impact potential: ⭐⭐⭐⭐ 5. Digital "Dead Ends" • What it is: 404 pages, out-of-stock notifications, & other negative pathways • Why it's missed: Seen as technical errors, not opportunities • Optimisation tip: Transform dead ends into discovery points with recommendations • Impact potential: ⭐⭐⭐ 6. Transaction Confirmations • What it is: Receipts, shipping notifications, & order confirmations • Why it's missed: Treated as operational communications only • Optimisation tip: Include personalised next-best action recommendations • Impact potential: ⭐⭐⭐⭐ 7. Post-Usage Check-ins • What it is: The period after customer has used your product for intended purpose • Why it's missed: Customer journey maps often end at purchase or initial use • Optimisation tip: Create timely follow-ups based on typical usage patterns • Impact potential: ⭐⭐⭐⭐⭐ 8. Community Participation • What it is: Customer-to-customer interactions in forums & social spaces • Why it's missed: Difficult to scale & often understaffed • Optimisation tip: Identify & empower customer advocates within communities • Impact potential: ⭐⭐⭐⭐ Your marketing doesn't end where your analytics dashboard stops tracking. The brands that will win tomorrow are already investing in these invisible touchpoints today. Which one will you optimise first? ♻️ Found this helpful? Repost to share with your network.  ⚡ Want more content like this? Hit follow Maya Moufarek.

Data alone can often feel impersonal and hard to relate to but professionals have found an interesting way around it - at least in the consulting world. I found it interesting that Bain & Company tackles this by using "customer journey mapping" - an approach that transforms data into vivid narratives about relatable customer personas. The process starts by creating detailed personas that represent key customer groups. For example, when working on the UK rail network, Bain created the persona of "Sarah" - a suburban working mom whose struggles with delays making her miss her daughter's events felt all too real. With personas established as protagonists, Bain meticulously maps their end-to-end journeys, breaking it down into a narrative arc highlighting every interaction and pain point. Using techniques like visual storyboards and real customer anecdotes elevates this beyond just experience mapping into visceral storytelling. The impact is clear - one study found a 35% boost in stakeholder buy-in when Bain packaged its conclusions as customer journey stories versus dry analysis. By making customers the heroes and positioning themselves as guides resolving their conflicts, Bain taps into the power of storytelling to inspire change. Whether mapping personal experiences or bringing data to life, leading firms realize stories engage people and shape beliefs far more than just reciting facts and figures. Narratives make even complex ideas resonate at a human level in ways numbers alone cannot.

Organizations talk about customer journey mapping. Singapore Changi Airport Group has been implementing it for over 30 years. Most airports manage infrastructure. Changi manages experience at scale. You’ve seen the alternative. You land after a long flight. There’s an online arrival form you didn’t know about. No Wi-Fi. No guidance. Long queues. Friction at every step. At Changi, the passenger journey is engineered end-to-end. If you haven’t completed your SG Arrival Card, you’re notified multiple times before passport control. If you still need to complete it, terminals are provided immediately. Clear. Simple. Fast. No chaos. Security? Not a central bottleneck. Changi uses biometric clearance at immigration, and security screening is conducted at each individual gate. The result: smaller volumes per checkpoint, shorter queues, faster throughput. Its operational design is aligned to customer experience. I fly close to 180 days a year. The difference is not cosmetic. It’s structural. Changi focuses relentlessly on the critical passenger touchpoints: ▶️ Arrival preparation ▶️Immigration flow ▶️Security design ▶️Digital integration It consistently ranks among the world’s best airports. Not because of waterfalls or shopping — but because it understands "experience is strategy implemented." Its awards don’t come from vision statements. They come from designing and implementing the journey that customers actually experience. That’s why Changi isn’t just an airport. It’s a masterclass in implementation.

📌 The 4 Types of Dashboard Users (and How to Design for Them) Not everyone who opens a dashboard is trying to do the same thing. Some people come in to take action. Some are there to explore. And others just want to stay informed without going too deep. One of the biggest reasons dashboards fail is because they try to serve everyone in the exact same way. But in reality, each user type comes in with a different goal, different expectations, and a completely different way of interacting with data. If you want real adoption, you have to design with that in mind. Here are the 4 types of users I see most often and how to design for each of them: 1️⃣ 𝐓𝐡𝐞 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐌𝐚𝐤𝐞𝐫 These are your directors, heads of departments, or team leads. They’re not here to explore or play with filters. They want clarity, fast, and without friction. Their goal is simple: understand if things are on track and quickly spot what needs attention. They’ll absolutely ask questions if something looks off, but they won’t spend time digging through the dashboard to find answers themselves. Some design tips: → Limit to 3-5 high-level KPIs → Use clear indicators: green = good, red = action needed → Provide year-over-year or vs-target comparisons → Avoid unnecessary interactivity. Make it passive and digestible 2️⃣ 𝐓𝐡𝐞 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫 These are your day-to-day executors: sales reps, support leads, logistics managers. They’re not looking for trends or storytelling. They need actionable information they can use right now. Their focus is on what’s broken, what’s delayed, and what needs immediate attention today. For them, a dashboard shouldn’t feel like a report. It should be more like a control room. How to design for them: → Surface anomalies, delays, and exceptions clearly → Make tasks and follow-ups easy to identify → Prioritize clarity and usability over visual polish → Design for action, not analysis 3️⃣ 𝐓𝐡𝐞 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 This is the user who actually lives inside your dashboard. They’ll slice, filter, drill down, and explore every corner of the data to build their own understanding. Unlike decision-makers, they don’t want simplified views. They prefer flexibility and depth. Your job here isn’t to guide every step, but to give them the tools to explore freely. Some design tips: → Provide filters for all major dimensions (time, segment, channel, etc.) → Add tooltips, detailed breakdowns, and trend charts → Avoid locking the layout too much. Let them explore 4️⃣ 𝐓𝐡𝐞 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐯𝐞 These users care about vision, ROI, and the big picture. They’re looking for signals, not noise. They don’t have time to interpret busy visuals. If the dashboard doesn’t answer "Are we on or off track?” within seconds They won’t use it. The bottom line: Dashboards are not one-size-fits-all. Before building, you should always ask: → Who is this for and what do they need from this dashboard? Build for users. Not just data.

I've launched a lot of dashboards. Many of them flopped. It's caused me to become a bit of a snob about making them. Here's the framework I follow: – Accuracy Can users trust the numbers? If not, congratulations, you’ve built a very pretty fiction generator. – Freshness If the data is older than the meeting you're presenting it in, it’s already losing the argument. – Governance and security Basic question: will this accidentally expose payroll? If the answer is “maybe,” the answer is “no.” – Latency If it loads slower than airport WiFi with a Boingo paywall, users will bail and ask someone to “just send the numbers” instead. – Seamless access If the login flow requires more steps than filing taxes, adoption is dead on arrival. – Discoverability Can people actually find what they came for, or is it an escape room with filters? – Flexibility Does it handle breakdowns, filters, and definitions without collapsing like a folding chair at a cookout? – User experience and adoption If it feels clunky, people will go right back to their rogue spreadsheets and pretend they never saw it. – Actionability Insights should drive decisions, not quietly live out their days in a forgotten tab. – Visualization quality Clear, intuitive, useful. If it looks like clip art, users won’t trust it. – Exportability People will export no matter how much you beg them not to, so it might as well work. – Interoperability It should play nicely with other tools, not behave like a jealous app that refuses to integrate. A dashboard shouldn't just be a bunch of charts. If it flops on any of these, it’s not ready for sunlight. But that's ok, keep refining if you are chasing a real business need. If you aren't chasing a business need though, lol. what are you doing. get a spreadsheet or something. What did I miss in my list? -- I'm 🏴☠️ Bill Yost and the most loving thing a data analyst can say is "that doesn't exactly sound like you need a dashboard"

Why Customer Journey Mapping Matters for Product Success Have you ever watched a product you knew was great fail to connect with users? 😢       I worked on a product once that had everything going for it: 🌟 Great features 📈 Solid metrics 👍 Enthusiastic internal buy-in But after launch, the results didn’t add up. Adoption was slow, and users weren’t sticking around. The issue wasn’t the product itself .. it was the experience. Through customer journey mapping, we discovered a poorly timed touchpoint was causing users to drop off before realizing the product’s value. Fixing it made all the difference. 👉 Your product is only as good as the EXPERIENCE it DELIVERS to USERS. That’s why Customer Journey Mapping is invaluable - it reveals the blind spots holding your product back. Journey maps are more than just visuals, they are strategic tools that help you understand and improve the entire experience users have with your product. Here’s my 7-step framework for creating actionable customer journey maps: 1️⃣ Define Your Objective – Start with a clear goal (e.g., "Reduce drop-offs during onboarding") 2️⃣ Identify Personas – Research your audience deeply using interviews, analytics, and surveys. 3️⃣ Map the Stages – Break down the journey: awareness, onboarding, engagement, retention, and advocacy. 4️⃣ List Touchpoints – Identify every interaction users have with your product (e.g., website, support) 5️⃣ Capture Emotions – Track emotional highs and lows to uncover frustration or delight points. 6️⃣ Spot Pain Points – Identify where friction or dissatisfaction occurs. 7️⃣ Identify Opportunities – Highlight actionable improvements to enhance the user experience. 📌 Example: Spotify’s Playlist Sharing Journey 🔸 Problem: Spotify wanted to understand why users weren’t fully utilizing the playlist-sharing feature. 🔸 Solution: Using customer journey mapping, they pinpointed that users were reluctant to share playlists due to fear of judgment or were unaware that the feature existed. 🔸 Result: Spotify improved the sharing experience, making it more intuitive, which led to higher user engagement and more frequent playlist sharing. 🔑 TAKEAWAY: Customer Journey Maps are not just about fixing pain points; they’re about building empathy, aligning your teams, and designing a seamless, cohesive experience that delights users at every stage of their journey. 💬 Your Turn: Have you used customer journey mapping in your role? What’s one surprising customer behavior you uncovered through journey mapping? Drop your thoughts below. #ProductManagement #CustomerJourney #CustomerExperience #EmpathyInDesign #UXInsights

✈️ Most dashboards are designed like airplane cockpits…when what you really need is a Control Tower. Too many BI dashboards try to show everything at once: KPIs, segments, raw data — all mashed together. It overwhelms users and kills decision speed. Instead, think about your dashboards as a Control Tower. The top of the tower offers a clear, panoramic view. You’re scanning for major movements and disruptions. When needed, you can zoom in with instrumentation or speak directly to pilots, but that's not your default. By managing your information hierarchy in layers, you can start simple and progressively reveal complexity. Here’s how it works: 📊 L1: The Tower View – high-level KPIs, trends, and alerts. What’s happening? 🔍 L2: Segment View – explore segments and categories. Where is it happening? 🧾 L3: Transaction View – detailed records and raw data. Why is it happening? Each level is built for a specific cognitive mode. Mixing them forces your brain to multitask and that’s where insight gets lost. 🧠 Rule of thumb: Dashboards should optimize for low cognitive load at entry. Users should never have to reconcile different zoom levels simultaneously. Control Tower dashboards allow users to scan, zoom, and act without overwhelming them. By designing dashboards to reflect human cognitive modes and information hierarchy, you create tools that are not just insightful but usable. #dataviz #dashboards #BI #uxdesign #analytics #productivity

🗺️ Customer Journey Mapping: More than just sticky notes on a wall! When you bring people together to map a customer journey, you’re not just drawing boxes and arrows - you’re uncovering the truth about how your customers actually experience your service. Here’s how to run a simple yet powerful session: 1️⃣ Set the scene Start with a clear journey to map (complaints, repairs, onboarding, arrears - pick one). Agree the start and end points so everyone’s aligned. 2️⃣ Bring the right people Customers, frontline colleagues, back-office teams, leaders. If they touch the journey, they should have a seat at the table. 3️⃣ Walk the steps Document the journey as it really happens today, not how the process map says it should. Capture every stage in the customer’s shoes. 4️⃣ Surface the feelings At each step, ask: how does the customer feel here? Frustrated, confused, reassured, delighted? Emotions are often the missing layer. 5️⃣ Spot the gaps Write down pain points, blockers, and duplication. But don’t forget to highlight the moments that work well as you’ll want to protect these. 6️⃣ Layer in evidence Add data, feedback, and insights to back up the journey. This turns sticky notes into a business case for change. 👉 What to document: ✅️ Steps & touchpoints ✅️ Customer thoughts & feelings ✅️ Pain points & opportunities ✅️ Supporting data & insights ✅️ “Moments of truth” - the make-or-break points in the journey Done well, a journey map becomes more than a workshop artefact. It’s a living tool that guides design, investment, and transformation. Because when you see your service through your customer’s eyes, it becomes impossible to design it any other way.