User Experience Metrics To Communicate Value To Clients

Over the last year, I’ve seen many people fall into the same trap: They launch an AI-powered agent (chatbot, assistant, support tool, etc.)… But only track surface-level KPIs — like response time or number of users. That’s not enough. To create AI systems that actually deliver value, we need 𝗵𝗼𝗹𝗶𝘀𝘁𝗶𝗰, 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 that reflect: • User trust • Task success • Business impact • Experience quality    This infographic highlights 15 𝘦𝘴𝘴𝘦𝘯𝘵𝘪𝘢𝘭 dimensions to consider: ↳ 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 — Are your AI answers actually useful and correct? ↳ 𝗧𝗮𝘀𝗸 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 — Can the agent complete full workflows, not just answer trivia? ↳ 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 — Response speed still matters, especially in production. ↳ 𝗨𝘀𝗲𝗿 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 — How often are users returning or interacting meaningfully? ↳ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗥𝗮𝘁𝗲 — Did the user achieve their goal? This is your north star. ↳ 𝗘𝗿𝗿𝗼𝗿 𝗥𝗮𝘁𝗲 — Irrelevant or wrong responses? That’s friction. ↳ 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗗𝘂𝗿𝗮𝘁𝗶𝗼𝗻 — Longer isn’t always better — it depends on the goal. ↳ 𝗨𝘀𝗲𝗿 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 — Are users coming back 𝘢𝘧𝘵𝘦𝘳 the first experience? ↳ 𝗖𝗼𝘀𝘁 𝗽𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 — Especially critical at scale. Budget-wise agents win. ↳ 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝘁𝗵 — Can the agent handle follow-ups and multi-turn dialogue? ↳ 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 𝗦𝗰𝗼𝗿𝗲 — Feedback from actual users is gold. ↳ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 — Can your AI 𝘳𝘦𝘮𝘦𝘮𝘣𝘦𝘳 𝘢𝘯𝘥 𝘳𝘦𝘧𝘦𝘳 to earlier inputs? ↳ 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 — Can it handle volume 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 degrading performance? ↳ 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 — This is key for RAG-based agents. ↳ 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗰𝗼𝗿𝗲 — Is your AI learning and improving over time? If you're building or managing AI agents — bookmark this. Whether it's a support bot, GenAI assistant, or a multi-agent system — these are the metrics that will shape real-world success. 𝗗𝗶𝗱 𝗜 𝗺𝗶𝘀𝘀 𝗮𝗻𝘆 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗼𝗻𝗲𝘀 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀? Let’s make this list even stronger — drop your thoughts 👇

Most UX folks are missing the one skill that could save their careers. For a long time, many UXers have been laser-focused on the craft. Understanding users. Testing ideas. Perfecting pixels. But here’s the reality. Companies are cutting those folks everywhere, because they don’t connect their work to hard, actual, tangible $$$$$. So it’s viewed as a luxury. A nice-to-have. My 2 cents.. If you can’t tie your decisions to how it helps the business make or save money, you’re at risk. Full stop. But I have good news. You can quantify your $$ impact using basic financial modeling. Here’s a quick example.. Imagine you’re working on a tool that employees use every day. Let’s say the current experience requires 8 hours a week for each employee to complete a task. By improving the usability of the tool, you cut that time by three hours. Let’s break it down. If the average employee makes $100K annually (roughly $50/hr), and 100 employees use the tool, that’s $15K saved each week. Over a year, that’s $780K in savings.. just by shaving 3 hours off a process. Now take it a step further. What if those employees use those extra 3 hours to create more value for customers? What’s the potential revenue upside? This is the kind of thinking that sets a designer apart. It’s time for UXers to stop treating customer sentiment or usability test results as the final metric. Instea learn how your company makes or saves money and model the financial impact of your UX changes. Align your work with tangible metrics like operational efficiency, customer retention, or lifetime value. The best part? This isn’t hard. Basic math and a simple framework can help you communicate your value in ways the business understands. Your prototype or design file doesn’t need to be perfect. But your ability to show how it drives business outcomes? That does. — If you enjoyed this post, join hundreds of others and subscribe to my weekly newsletter — Building Great Experiences https://lnkd.in/edqxnPAY

When reporting on your impact as a UX Researcher, here are the best → worst metrics to tie your work to: 𝟭. 𝗥𝗲𝘃𝗲𝗻𝘂𝗲 Every company is chasing revenue growth. This is especially true in tech. Tying your work to new (or retained) revenue is the strongest way to show the value that you’re bringing to the organization and make the case for leaders to invest more in research. Examples: - Research insights → new pricing tier(s) → $X - Research insights → X changes to CSM playbook → Y% reduction in churn → $Z 𝟮. 𝗞𝗲𝘆 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 This might not be possible for many UXRs, but if you can, showing how your work contributed to key decisions (especially if those decisions affect dozens or hundreds of employees) is another way to stand out. Examples: - Research insights → new ideal customer profile → X changes across Sales / Marketing / Product affecting Y employees' work - Research insights → refined product vision → X changes to the roadmap affecting Y employees' work 𝟯. 𝗡𝗼𝗿𝘁𝗵 𝘀𝘁𝗮𝗿 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 If you can’t directly attribute your work to revenue, that’s ok! The majority of research is too far removed from revenue to measure the value in dollars. The next best thing is to tie your work to core user engagement metrics (e.g. “watch time” for Netflix, “time spent listening” for Spotify). These metrics are north star metrics because they’re strong predictors of future revenue. Examples: - Research insights → X changes to onboarding flow → Y% increase in successfully activated users - Research insights → X new product features → Y% increase in time spent in app 𝟰. 𝗖𝗼𝘀𝘁 𝘀𝗮𝘃𝗶𝗻𝗴𝘀 For tech companies, a dollar saved is usually less exciting than a dollar of new (or retained) revenue. This is because tech companies’ valuations are primarily driven by future revenue growth, not profitability. That being said, cost savings prove that your research is having a real / tangible impact. 𝟱. 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻’𝘁 𝗯𝗲 𝘁𝗿𝗮𝗰𝗲𝗱 𝘁𝗼 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗮𝗯𝗼𝘃𝗲 Hot take: The biggest trap for researchers (and product folks generally) is focusing on user experience improvements that do not clearly lead to more engagement or more revenue. At most companies, it is nearly impossible to justify investments (including research!) solely on the basis of improving the user experience. Reporting on user experience improvements without tying them to any of the metrics above will make your research look like an expendable cost center instead of a critical revenue driver. — TL;DR: Businesses are driven by their top line (revenue) and bottom line (profit). If you want executives to appreciate the impact of (your) research, start aligning your reporting to metrics 1-4 above.

Aligning design with business goals requires business speak. Most business workflows aren’t built to assess the value design brings. Business has its own language. Design needs a measured approach to correlate value. We know design decisions aren’t just about creativity—they directly impact business success when guided by good processes and metrics. That’s the perspective we’ve embraced in our open, data-informed framework Glare. From our experience working with customers, several key factors must be considered to demonstrate the value of design decisions. → Design as a business driver Design decisions can influence workflows, customer interactions, and ultimately business results, proving that good design is aesthetic AND strategic. It requires analytical skills and patience to bring stakeholders along for the journey. This is what people mean by having a “seat at the table.” Example: Redesigning a mobile app checkout flow reduces cart abandonment by 5% and boosts sales by 10%, showing that design drives user satisfaction and business growth. → Metrics bridge the gap UX metrics act as a common language between design and business teams. They ensure that creative efforts are measurable and directly tied to business objectives. The goal is to find a correlation between the product and business metrics, typically lagging indicators. UX metrics are leading. Example: Task completion rates increase by 10%, and user satisfaction scores increase by 20%, showing that the checkout redesign reduces drop-offs and increases conversions, aligning design improvements with business goals. → Continuous Feedback Loop The process establishes a feedback loop that informs better decision-making and ensures continuous improvement by correlating design concepts and UX metrics with business goals. Design KPI trees can make this easier to manage.  Vitaly Friedman has a lot of great content on this topic. Example: Testing the checkout flow refines the design and boosts average order value by 15%, showing how continuous iteration improves user experience and revenue. → Results Matter Design can be validated not just by intuition or creativity but also by its ability to deliver tangible business outcomes, such as increased revenue, customer satisfaction, or improved usability. Example: The redesigned checkout delivers measurable results: 25% fewer support tickets and a 10-point NPS increase, validating the design’s impact on customer satisfaction and business success. (don’t shoot me for using NPS, it’s still business speak). Using an approach like this highlights the strategic value of design in achieving business outcomes. This allows design teams to communicate their impact in business speak that resonates with executives and stakeholders. The goal is to shift the perception of design from a cost center to a growth driver.