{"id":230286,"date":"2024-11-29T10:23:11","date_gmt":"2024-11-29T10:23:11","guid":{"rendered":"https:\/\/userpilot.com\/blog\/optimize-product-metrics-for-growth-dan-olsen\/"},"modified":"2026-04-10T09:49:43","modified_gmt":"2026-04-10T09:49:43","slug":"how-to-optimize-your-product-metrics-for-growth","status":"publish","type":"post","link":"https:\/\/userpilot.com\/blog\/how-to-optimize-your-product-metrics-for-growth\/","title":{"rendered":"How to Optimize Your Product Metrics for Growth by Dan Olsen"},"content":{"rendered":"<p>Many companies invest heavily in acquiring new customers, yet still struggle with growth. Why? According to product expert <a href=\"https:\/\/www.linkedin.com\/in\/danolsen98\/\" target=\"_blank\" rel=\"nofollow noopener\">Dan Olsen<\/a>, it\u2019s because their \u201cbucket\u201d \u2014 the product itself \u2014 is leaky. Customers leave as fast as new ones come in. Dan, a Stanford-trained engineer with experience guiding companies like Intuit, understands how to optimize your <a href=\"https:\/\/userpilot.com\/blog\/product-analytics-metrics\/\">product metrics for<\/a> growth by focusing on retention and building a product users truly value.<\/p>\n<p>In his recent talk at <a href=\"https:\/\/summit.productdrive.io\/\" target=\"_blank\" rel=\"noopener noreferrer\">Product Drive<\/a>, Dan shared actionable strategies from his book, The Lean Product Playbook, for making products people love to use.<\/p>\n<p>We\u2019ll discuss these strategies here, but to get the full scope of Dan\u2019s proven methods, you can watch <a href=\"https:\/\/summit.productdrive.io\/talks\/how-to-optimize-your-product-metrics-for-growth\/\" target=\"_blank\" rel=\"noopener noreferrer\">his talk<\/a>:<\/p>\n<figure class=\"video strchf-type-video regular strchf-size-regular strchf-align-center\">\n<div class=\"embed-container\">\n<div style=\"max-width: 100%; position: relative; height: 400px;\"><iframe loading=\"lazy\" style=\"position: absolute; top: 0px; left: 0px; width: 100%; height: 100%; border: none;\" title=\"How to Optimize Your Product Metrics for Growth by Dan Olsen\" src=\"https:\/\/www.youtube-nocookie.com\/embed\/SdJBKciRGiA?feature=oembed&amp;start=187\" width=\"200\" height=\"113\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/div>\n<\/div>\n<\/figure>\n<p>Let\u2019s dive in!<\/p>\n<h2 id=\"98a44\">The product manager\u2019s roles and responsibilities<\/h2>\n<p>Being a product manager often means balancing multiple priorities. We&#8217;re everywhere at once &#8211; crafting <a href=\"https:\/\/userpilot.com\/blog\/product-vision-examples\/\" target=\"_blank\" rel=\"noopener noreferrer\">product vision<\/a>, digging into customer research, and somehow keeping engineering, marketing, and sales teams all moving in the same direction.<\/p>\n<p>Here&#8217;s the kicker, though &#8211; we have to do all this without actual authority. You might have heard our favorite motto: &#8220;<a href=\"https:\/\/productdive.com\/with-great-responsibility-comes-no-power\/\" target=\"_blank\" rel=\"noopener noreferrer\">With great responsibility comes no power.<\/a>&#8221; Funny because it&#8217;s painfully true. We&#8217;re tasked with achieving product-market fit and driving growth, but we have no direct control over the people who build, market, and support it.<\/p>\n<p>And let&#8217;s be honest &#8211; the odds aren&#8217;t exactly in our favor. Most new products never find their <a href=\"https:\/\/userpilot.com\/blog\/product-market-fit-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">product-market fit<\/a>. And many features we ship with high hopes end up missing their targets completely. Research also shows that <a href=\"https:\/\/startupgenome.com\/article\/the-state-of-the-global-startup-economy\" target=\"_blank\" rel=\"nofollow noopener\">about 90% of startups fail<\/a>, and poor product-market fit is often the culprit.<\/p>\n<p>But don&#8217;t worry &#8211; we&#8217;ll show you how to optimize your product metrics for growth, and more importantly, which to prioritize between acquisition, conversion, and retention.<\/p>\n<h2 id=\"ee7ed\">Understanding the product metrics<\/h2>\n<p>Let\u2019s have two products &#8211; A and B. At first glance, they look identical. Both show the same number of <a href=\"https:\/\/userpilot.com\/blog\/active-user\/\" target=\"_blank\" rel=\"noopener noreferrer\">active users<\/a> over time, and their growth curves could be considered twins.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/active-users-graph_29c12aec42f49ce786d91bda09f66a79_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/active-users-graph_29c12aec42f49ce786d91bda09f66a79_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/active-users-graph_29c12aec42f49ce786d91bda09f66a79_800.png\" alt=\"Active-users-curve-to-learn-how-to-optimize-your-product-metrics-for-growth\" \/><\/picture><figcaption>Looking at active users alone, Products A and B appear to perform similarly.<\/figcaption><\/figure>\n<p>But here&#8217;s where it gets interesting. \u201cActive users\u201d combines two distinct metrics: new users and returning users. It isn\u2019t an atomic metric or a single, standalone measurement.<\/p>\n<p>When we split into these two metrics, we see something fascinating: Product A gets <a href=\"https:\/\/userpilot.com\/blog\/how-to-onboard-new-users\/\" target=\"_blank\" rel=\"noopener noreferrer\">new users<\/a> regularly, but these users slip away faster than ice cream on a hot day. Their marketing team might be crushing it, but users haven\u2019t discovered their <a href=\"https:\/\/userpilot.com\/blog\/aha-moment\/\" target=\"_blank\" rel=\"noopener noreferrer\">Aha! moment<\/a>.<\/p>\n<p>While Product B may not attract as many new users, the ones it does acquire have high retention rates. When asked, most product managers would pick Product B every time.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/a-graph-showing-new-vs-active-users-for-two-products_f75ade02699388cf26af03ba778af473_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/a-graph-showing-new-vs-active-users-for-two-products_f75ade02699388cf26af03ba778af473_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/a-graph-showing-new-vs-active-users-for-two-products_f75ade02699388cf26af03ba778af473_800.png\" alt=\"New-and-returning-users-curve-for-two-products-to-know-how-to-optimize-your-product-metrics-for-growth\" \/><\/picture><figcaption>Breaking down the numbers reveals a very different story between Products A and B.<\/figcaption><\/figure>\n<h2 id=\"6rgg\">What\u2019s the optimal order between acquisition, conversion and retention<\/h2>\n<p>To prioritize your growth metrics effectively, let\u2019s use the &#8220;leaky bucket&#8221; analogy \u2014 Dan\u2019s favorite for explaining why some products struggle even with substantial spending on growth. When your product metrics show high user churn, adding more users through marketing is like pouring water into a bucket full of holes.<\/p>\n<p>Only when you see users consistently staying engaged &#8211; when your &#8220;bucket&#8221; holds water &#8211; should you scale up your user acquisition efforts. This way, your marketing spend actually contributes to sustainable growth rather than just temporarily inflating your user numbers.<\/p>\n<p>Here&#8217;s what this looks like in practice: if you&#8217;re losing 80% of users within the first week, spending money on ads is mostly wasting resources.<\/p>\n<p>Instead, focus on understanding why users leave. Are they dropping off after specific actions? Are they never reaching key features? Your <a href=\"https:\/\/userpilot.com\/blog\/product-analytics\/\" target=\"_blank\" rel=\"noopener noreferrer\">product analytics<\/a> will tell this story.<\/p>\n<p>The optimal order of metrics to focus on after <a href=\"https:\/\/userpilot.com\/blog\/new-product-launch\/\" target=\"_blank\" rel=\"noopener noreferrer\">launching a new product<\/a> is:<\/p>\n<h3 id=\"6itvt\">1. Retention<\/h3>\n<p>The first step is defining what value means for your specific product. This means identifying your core features and understanding how customers actually use them.<\/p>\n<p>For example, if you&#8217;re running a note-taking app, don&#8217;t just track if someone clicked the &#8220;create note&#8221; button. Look deeper &#8211; are they writing substantial notes? Do they come back to review them? Are they sharing notes with others? This is what real feature usage looks like.<\/p>\n<p>You&#8217;ll want to track these core events and set clear benchmarks. Let&#8217;s say you expect users to create at least one note per week &#8211; if you see users falling below this, it&#8217;s a clear signal that they&#8217;re not getting consistent value from your product.<\/p>\n<p>The key is to go beyond surface-level metrics. Anyone can click a button once, but sustained engagement shows true product value. Look at patterns like:<\/p>\n<ul>\n<li>How frequently users return to key features.<\/li>\n<li>Whether usage aligns with your expected use cases.<\/li>\n<li>If users are achieving their goals through your product<\/li>\n<\/ul>\n<p>Once you identify where users are dropping off, you can focus on fixing those specific friction points. Maybe your mobile app is too slow, or perhaps users can&#8217;t find important features. These are the &#8220;holes&#8221; you need to plug in before thinking about getting more users.<\/p>\n<p>Retention should always be your primary focus because it signals <a href=\"https:\/\/userpilot.com\/blog\/product-market-fit-framework\/\" target=\"_blank\" rel=\"noopener noreferrer\">product-market-fit<\/a> (PMF) &#8212; the key to long-term growth.<\/p>\n<h3 id=\"cdlel\">2. Conversion<\/h3>\n<p>Once you have retention under control, move on to conversion. This step is about turning interested visitors into active users or paying customers. High <a href=\"https:\/\/userpilot.com\/blog\/conversion-rate-optimization-for-saas\/\" target=\"_blank\" rel=\"noopener noreferrer\">conversion rates<\/a> show that your messaging, onboarding, and pricing resonate.<\/p>\n<p>But conversion is not just about getting users to sign up &#8211; it&#8217;s about getting them to experience your product&#8217;s value. I&#8217;ve seen many products with great sign-up rates but poor activation because they focused on the wrong metrics.<\/p>\n<p>Think about your user&#8217;s journey. When someone lands on your product, what&#8217;s the shortest path to their &#8220;<a href=\"https:\/\/userpilot.com\/blog\/aha-moment\/\" target=\"_blank\" rel=\"noopener noreferrer\">Aha! moment<\/a>&#8220;? For a video editing app, this might be completing their first edit. For a project management tool, it might be setting up their first project board with their team.<\/p>\n<p>Your onboarding should focus on this core value moment. Cut out everything else. If users don&#8217;t need to fill out their profile immediately, don&#8217;t ask them to. If they don&#8217;t need to invite team members yet, save it for later. Guide them to that first win as quickly as possible. This means really understanding what makes users stick around.<\/p>\n<p><strong>Tip<\/strong> \ud83d\udca1: Look at your most engaged users &#8211; what did they do in their first session? That&#8217;s often your best clue for what your onboarding should prioritize.<\/p>\n<h3 id=\"5rs86\">3. Acquisition<\/h3>\n<p>Acquisition is the final step, but it only makes sense once retention and conversion are solid. With a leak-proof bucket and easy <a href=\"https:\/\/userpilot.com\/blog\/conversion-path-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">conversion path<\/a>, every dollar spent on marketing will yield better returns.<\/p>\n<p>Focus on acquisition when:<\/p>\n<ul>\n<li>You\u2019ve achieved strong retention and conversion.<\/li>\n<li>Your <a href=\"https:\/\/userpilot.com\/blog\/product-market-fit-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">product-market fit<\/a> is validated.<\/li>\n<li>Each new user has a higher chance of sticking around.<\/li>\n<\/ul>\n<p>Using the same bucket metaphor above, here&#8217;s how it relates:<\/p>\n<ul>\n<li><strong>Conversion<\/strong>: How much of that water makes it into the bucket (visitors becoming customers).<\/li>\n<li><strong>Acquisition<\/strong>: The amount of water aimed at the bucket (potential users you attract).<\/li>\n<li><strong>Retention<\/strong>: How well the water stays in the bucket over time (users who keep returning to your product).<\/li>\n<\/ul>\n<p><strong>Remember, don\u2019t drive acquisition until you\u2019re confident in your product-market fit.<\/strong><\/p>\n<h2 id=\"cft7e\">How to track your product-market fit with 1 metric?<\/h2>\n<p>Here&#8217;s a fun thought experiment: if you could only track one metric to measure <a href=\"https:\/\/userpilot.com\/blog\/product-market-fit-framework\/\" target=\"_blank\" rel=\"noopener noreferrer\">product-market fit<\/a>, what would it be?<\/p>\n<p>Drumroll, please&#8230; It&#8217;s retention rate.<\/p>\n<p><a href=\"https:\/\/userpilot.com\/blog\/retention-rate-meaning\/\" target=\"_blank\" rel=\"noopener noreferrer\">Retention rate<\/a> is the percentage of your customers who stay active over time.<\/p>\n<p>Imagine having the world&#8217;s best sales team &#8211; they&#8217;re so good they convert 100% of prospects. Sounds amazing, right? But if your product doesn&#8217;t solve real problems, those perfectly-converted users won&#8217;t stick around.<\/p>\n<p>Now imagine having the world&#8217;s worst <a href=\"https:\/\/userpilot.com\/blog\/saas-sales-process-stages\/\" target=\"_blank\" rel=\"noopener noreferrer\">sales process<\/a>, but a product that genuinely helps people. Even with a clunky acquisition process, users who discover the value will keep coming back. They might even tell their friends, &#8220;Look, the signup was a pain, but trust me &#8211; this thing is worth it.&#8221;<\/p>\n<p>That&#8217;s why retention rate should be your <a href=\"https:\/\/userpilot.com\/blog\/north-star-metric\/\" target=\"_blank\" rel=\"noopener noreferrer\">North Star metric<\/a> for product-market fit.<\/p>\n<h2 id=\"5t0g\">How to track PMF with cohort analysis<\/h2>\n<p>Don&#8217;t let the fancy term &#8220;cohort analysis&#8221; scare you. A <a href=\"https:\/\/userpilot.com\/blog\/cohort-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">cohort analysis<\/a> is a technique that groups users based on shared characteristics and analyzes how they behave over time.<\/p>\n<p>Cohort analysis identifies what factors contribute to <a href=\"https:\/\/userpilot.com\/blog\/user-retention\/\" target=\"_blank\" rel=\"noopener noreferrer\">user retention<\/a>, pinpoints stages where users drop off, and evaluates your <a href=\"https:\/\/userpilot.com\/blog\/best-product-marketing-campaigns\/\" target=\"_blank\" rel=\"noopener noreferrer\">marketing <\/a>campaign&#8217;s effectiveness.<\/p>\n<p>For instance, we can use a cohort analysis to track and study users of a product in two ways: by when they join and by what they do.<\/p>\n<p>Here\u2019s how it works:<\/p>\n<ul>\n<li><strong>Acquisition cohort<\/strong>: This means grouping users by when they first sign up. It lets us see if people who join in different months or weeks behave differently. We often use this to track how many new users stay active over time.<\/li>\n<\/ul>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/acquisitioncohort-1-1600_293744a11d7b8fe1cf4ab4cc0fc7d123_800.jpg 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/acquisitioncohort-1-1600_293744a11d7b8fe1cf4ab4cc0fc7d123_800.jpg 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/acquisitioncohort-1-1600_293744a11d7b8fe1cf4ab4cc0fc7d123_800.jpg\" alt=\"Acquisition-cohort-chat\" \/><\/picture><figcaption>This chart tracks how many new users keep coming back each week. As you can see, the numbers drop sharply after week one.<\/figcaption><\/figure>\n<ul>\n<li><strong>Behavioral cohort<\/strong>: This means grouping users by the actions they take, like when they try a new feature or finish setting up their account. It helps us see how different actions affect whether users keep coming back.<\/li>\n<\/ul>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/behavioral-cohort-2-1600_7e7eaae1224842393bf2064acb3a9098_800.jpg 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/behavioral-cohort-2-1600_7e7eaae1224842393bf2064acb3a9098_800.jpg 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/behavioral-cohort-2-1600_7e7eaae1224842393bf2064acb3a9098_800.jpg\" alt=\"Behavioral-cohort-chat\" \/><\/picture><figcaption>You can learn more by looking at which users try specific features.<\/figcaption><\/figure>\n<p>To conduct a cohort analysis, follow these steps:<\/p>\n<h3 id=\"eku33\"><strong>Step 1: Create cohorts by time periods or other segments<\/strong><\/h3>\n<p>This is where we get organized. Here&#8217;s how:<\/p>\n<ul>\n<li>Group users by their sign-up month (your January cohort, February cohort, etc.).<\/li>\n<li>Start each cohort at 100% and track how that number changes.<\/li>\n<\/ul>\n<p>Alternatively, you can consider other grouping factors like:<\/p>\n<ul>\n<li><a href=\"https:\/\/userpilot.com\/blog\/customer-acquisition-channels\/\" target=\"_blank\" rel=\"noopener noreferrer\">Acquisition channel<\/a> (did users come from ads, organic search, or referrals?).<\/li>\n<li>User type (free vs. paid, small business vs. enterprise).<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/feature-usage\/\" target=\"_blank\" rel=\"noopener noreferrer\">Feature usage<\/a> (users who used specific features in their first week).<\/li>\n<\/ul>\n<p>The key is consistency &#8211; pick meaningful groups and track them the same way every time.<\/p>\n<h3 id=\"6migl\"><strong>Step 2. Track retention over time<\/strong><\/h3>\n<p>Now comes the detective work. For each cohort:<\/p>\n<ul>\n<li>Monitor weekly or <a href=\"https:\/\/userpilot.com\/blog\/how-to-increase-monthly-active-users\/\" target=\"_blank\" rel=\"noopener noreferrer\">monthly active users<\/a>.<\/li>\n<li>Track how many users complete key actions in your product.<\/li>\n<li>Look for patterns in when users typically drop off.<\/li>\n<li>Measure how long it takes to reach the &#8220;terminal value&#8221; (where the retention curve flattens).<\/li>\n<\/ul>\n<h3 id=\"1oqgn\"><strong>Step 3: Compare cohorts<\/strong><\/h3>\n<p>This is where the insights start coming together. Watch out for:<\/p>\n<ul>\n<li>Are newer cohorts retaining better than older ones? (This suggests your product is improving)<\/li>\n<li>Do certain types of users stick around longer? (This helps target your ideal customer)<\/li>\n<li>Is there a specific period where you lose most users? (This highlights critical <a href=\"https:\/\/userpilot.com\/blog\/drop-off-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">drop-off points<\/a>)<\/li>\n<li>Which features are used most by your retained users? (This shows what <a href=\"https:\/\/userpilot.com\/blog\/increase-product-stickiness-saas\/\" target=\"_blank\" rel=\"noopener noreferrer\">drives stickiness<\/a>)<\/li>\n<\/ul>\n<p>For example, we\u2019re looking at three cohorts: Cohort A (blue diamonds), Cohort B (red squares), and Cohort C (green triangles).<\/p>\n<p>According to Dan, \u201cIf you were the <a href=\"https:\/\/userpilot.com\/blog\/what-is-a-project-manager\/\" target=\"_blank\" rel=\"noopener noreferrer\">project manager<\/a>, which cohort would you choose? When I ask this, most people pick Cohort C. I then ask them why, and I get different responses. One common answer is that Cohort C has the smallest drop-off between week one and week five.<\/p>\n<p>Then I follow up with, &#8220;What if I lowered the week one value of the blue curve to 10%?&#8221; This would make the blue curve&#8217;s drop-off even smaller. But people still prefer Cohort C, so we know <a href=\"https:\/\/userpilot.com\/blog\/drop-off-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">drop-off <\/a>size isn\u2019t the main factor.<\/p>\n<p>Others mention the area under the curve as a reason, but eventually, someone says, \u201cI want the highest <a href=\"https:\/\/userpilot.com\/blog\/retention-rate-meaning\/\" target=\"_blank\" rel=\"noopener noreferrer\">retention rate.<\/a>\u201d<\/p>\n<p>I then point to the graph, saying, \u201cThis shows the highest rate here at 50%.\u201d But they clarify that they mean the highest rate on the right side of the graph.\u201d<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/example-of-a-cohort-analysis_92e2b48592b9de5025dbd95e512ea393_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/example-of-a-cohort-analysis_92e2b48592b9de5025dbd95e512ea393_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/example-of-a-cohort-analysis_92e2b48592b9de5025dbd95e512ea393_800.png\" alt=\"A-cohort-analysis-of-3-different-cohorts-on-how-to-optimize-your-produt-metrics-for-growth\" \/><\/picture><figcaption>An example of a cohort analysis for 3 different cohorts.<\/figcaption><\/figure>\n<p>Remember, if your retention curve hits zero, you don&#8217;t have <a href=\"https:\/\/userpilot.com\/blog\/product-market-fit-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">product-market fit<\/a>. But if it flattens out at a healthy level (which varies by industry), you&#8217;re on the right track.<\/p>\n<blockquote><p>The final value where the retention curve flattens out is known as the &#8220;terminal value.&#8221; This is an indicator of how well your product retains users in the long term. A higher terminal value indicates better product-market fit.<\/p><\/blockquote>\n<h2 id=\"4ju0\">Conclusion<\/h2>\n<p>Growing a successful product isn&#8217;t about throwing money at acquisition &#8211; it&#8217;s about building something people want to keep using. Before you spend big on getting new users:<\/p>\n<ul>\n<li>Focus on retention first &#8211; make sure your current users are getting real value.<\/li>\n<li>Then optimize conversion &#8211; remove barriers that keep new users from experiencing that value.<\/li>\n<li>Only then scale acquisition &#8211; when you know you can keep the users you attract.<\/li>\n<\/ul>\n<p>Want to build better product experiences that keep users coming back? <a href=\"https:\/\/userpilot.com\/userpilot-demo\" target=\"_blank\" rel=\"noopener noreferrer\">Book a demo<\/a> call with our team and get started!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&#8216;How to optimize your product metrics for growth&#8217; by Dan Olsen is one of the sessions in this year&#8217;s Product Drive hosted by Userpilot. Intrigued? In this article, you will learn who Dan Olsen is, discover the core ideas from his book The Lean Product Playbook, and find out what you can expect from his talk.<\/p>\n","protected":false},"author":56,"featured_media":230288,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[214],"tags":[346,5474,292,216,215,571],"class_list":["post-230286","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product-management","tag-product-analytics","tag-product-drive","tag-product-growth","tag-product-management","tag-product-manager","tag-product-metrics"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.2 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>How to Optimize Your Product Metrics for Growth by Dan Olsen<\/title>\n<meta name=\"description\" content=\"Learn who Dan Olsen is and discover the core ideas from his book The Lean Product Playbook, which focuses on creating products people love.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/userpilot.com\/blog\/how-to-optimize-your-product-metrics-for-growth\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to Optimize Your Product Metrics for Growth by Dan Olsen\" \/>\n<meta property=\"og:description\" content=\"Learn who Dan Olsen is and discover the core ideas from his book The Lean Product Playbook, which focuses on creating products people love.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/userpilot.com\/blog\/how-to-optimize-your-product-metrics-for-growth\/\" \/>\n<meta property=\"og:site_name\" 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