{"id":42862,"date":"2026-07-05T07:03:55","date_gmt":"2026-07-05T14:03:55","guid":{"rendered":"https:\/\/maccelerator.la\/?p=42862"},"modified":"2026-07-05T07:03:55","modified_gmt":"2026-07-05T14:03:55","slug":"how-to-create-a-customer-journey-map-for-fintech-companies-2","status":"publish","type":"post","link":"https:\/\/maccelerator.la\/en\/blog\/startup-strategy\/how-to-create-a-customer-journey-map-for-fintech-companies-2\/","title":{"rendered":"The Fintech Customer Journey Map: Why Trust and Regulation Break the Standard Playbook"},"content":{"rendered":"<p>Your signups are growing. Your marketing funnel looks healthy. But somewhere between &#8220;created an account&#8221; and &#8220;moved their first dollar,&#8221; 40-60% of your users vanish \u2014 and you cannot explain why. <strong>Knowing How to Create a Customer Journey Map for Fintech Companies is the process of documenting every stage from awareness to advocacy while layering in two variables generic maps ignore: trust-building moments and regulatory friction points like KYC and verification.<\/strong> That second layer is what separates a fintech map from a SaaS map \u2014 and why most founders diagnose the wrong problem.<\/p>\n<p>Here is the situation you are probably in. You hit product-market fit. Revenue is climbing. But there is a leak between signup and first funded transaction, and you have no idea whether it is a UX problem, a trust problem, or a compliance-friction problem.<\/p>\n<p>The generic customer journey map \u2014 the one you copied from a SaaS blog \u2014 will not tell you. It was never built to. In consumer fintech, the single largest drop-off often sits inside identity verification, a step SaaS maps treat as invisible plumbing.<\/p>\n<p>This article shows you how to build a map that actually diagnoses that leak. Not a whiteboard exercise. A diagnostic tool.<\/p>\n<h2>Why Fintech Journey Maps Fail When You Use a SaaS Template<\/h2>\n<p>The standard SaaS journey map is a clean line: Awareness \u2192 Consideration \u2192 Signup \u2192 Activation \u2192 Retention. Each stage flows into the next. The friction is assumed to be low. The user&#8217;s biggest question is &#8220;does this solve my problem?&#8221;<\/p>\n<p>Fintech breaks that model. Your user&#8217;s biggest question is not &#8220;does this work?&#8221; It is <strong>&#8220;will I give you my money and my identity?&#8221;<\/strong><\/p>\n<p>That question does not live in one stage. It acts on every stage. And the SaaS template has no column for it.<\/p>\n<p>There are two forces the standard map ignores completely. Treat them as overlays that run across the entire journey, not as boxes you add at the end.<\/p>\n<ul>\n<li><strong>Trust escalation.<\/strong> The psychological threshold a user crosses before handing over sensitive data or money. It rises at every stage. A confusing email at the wrong moment resets it to zero.<\/li>\n<li><strong>Compliance friction.<\/strong> Mandatory steps \u2014 KYC, verification, disclosures, anti-fraud checks \u2014 that you cannot remove. You can only sequence them. The SaaS map assumes friction is a bug. In fintech, some of it is the law.<\/li>\n<\/ul>\n<p>These are not optional add-ons. They are the reason your funnel behaves nothing like the template promised.<\/p>\n<p>Consider a payments startup we worked with. They copied a well-known SaaS activation map and spent months optimizing the top of the funnel \u2014 ad copy, landing pages, signup flow. Conversion at those stages improved. Funded transactions did not move.<\/p>\n<p>Their real leak sat between identity verification and first deposit. Users completed KYC, then stalled. The map they borrowed had no box for that gap, so they never looked there.<\/p>\n<blockquote><p>&#8220;Most fintech founders optimize the funnel they can see. The money leaks out of the funnel the SaaS template told them didn&#8217;t exist.&#8221; \u2014 Alessandro Marianantoni<\/p><\/blockquote>\n<p>When the friction is invisible on your map, you optimize everything except the thing that is actually costing you money. That is the trap.<\/p>\n<h2>Key Takeaways<\/h2>\n<ul>\n<li>A fintech customer journey map documents awareness-to-advocacy stages, then overlays trust escalation and compliance friction across every stage \u2014 the two variables generic maps omit.<\/li>\n<li>The largest leak in consumer fintech usually sits inside onboarding and verification, not in the marketing funnel most founders obsess over.<\/li>\n<li>A journey map built on internal assumptions is a hypothesis, not evidence. You need behavioral data, qualitative signals, and a regulatory-constraint map before you draw a single box.<\/li>\n<li>Prioritize fixes by revenue proximity \u2014 a small leak right before first deposit is worth more than a large leak at the top of the funnel.<\/li>\n<li>If you are post-PMF with unexplained drop-off, this is exactly your stage. Pre-PMF, a lighter hypothesis map is enough.<\/li>\n<\/ul>\n<h2>The 5 Stages That Actually Matter in a Fintech Journey<\/h2>\n<p>Forget the generic five stages. Here is a fintech-specific skeleton you can start mapping against today. At each stage, the user is asking a trust or regulatory question \u2014 and that question, not the feature, drives the drop-off.<\/p>\n<p>This is the structure, not the full method. The method is the data and the prioritization that come later. But this gives you the frame.<\/p>\n<h3>Stage 1: Awareness \u2014 &#8220;Is this legit and safe?&#8221;<\/h3>\n<p><strong>Emotional state:<\/strong> skeptical. Fintech carries fraud baggage. A user&#8217;s first instinct is suspicion, not curiosity.<\/p>\n<p><strong>Drop-off risk:<\/strong> they bounce before evaluating because your brand does not signal safety \u2014 no security proof, no recognizable partners, no trust signals.<\/p>\n<p><strong>Track:<\/strong> bounce rate on your first-touch pages, and whether trust-signal placement changes it.<\/p>\n<h3>Stage 2: Evaluation \u2014 &#8220;Do I trust them with my money and data?&#8221;<\/h3>\n<p><strong>Emotional state:<\/strong> cautiously interested, actively looking for reasons to say no.<\/p>\n<p><strong>Drop-off risk:<\/strong> missing social proof, unclear regulatory status, no visible answer to &#8220;what happens to my data?&#8221;<\/p>\n<p><strong>Track:<\/strong> time-on-page for security and pricing content, and the conversion rate from evaluation to signup.<\/p>\n<h3>Stage 3: Onboarding &#038; Verification \u2014 &#8220;Is this worth the friction of KYC?&#8221;<\/h3>\n<p><strong>Emotional state:<\/strong> committed enough to start, but the invasive asks trigger second thoughts.<\/p>\n<p><strong>Drop-off risk:<\/strong> the biggest single leak in consumer fintech. Every verification field is a chance to lose them. Abandonment during KYC routinely outweighs every other stage.<\/p>\n<p><strong>Track:<\/strong> completion rate per verification step. Not the whole flow \u2014 each step. This is where you find the exact field that kills you.<\/p>\n<h3>Stage 4: First Value \/ First Transaction \u2014 &#8220;Did the money actually move?&#8221;<\/h3>\n<p><strong>Emotional state:<\/strong> hopeful but anxious. This is the moment of maximum vulnerability \u2014 real money, first time.<\/p>\n<p><strong>Drop-off risk:<\/strong> they completed verification but never funded. The gap between &#8220;verified&#8221; and &#8220;first deposit&#8221; is where the payments startup above was bleeding.<\/p>\n<p><strong>Track:<\/strong> time between verification completion and first transaction, and the percentage who never complete it.<\/p>\n<h3>Stage 5: Retention &#038; Advocacy \u2014 &#8220;Do I trust them enough to do more?&#8221;<\/h3>\n<p><strong>Emotional state:<\/strong> relieved it worked, deciding whether to deepen the relationship.<\/p>\n<p><strong>Drop-off risk:<\/strong> one bad security scare, one confusing statement, one failed transaction resets trust to zero and they leave.<\/p>\n<p><strong>Track:<\/strong> repeat transaction rate, referral rate, and support tickets tagged around trust or security concerns.<\/p>\n<p><strong>The insight most founders miss: your trust map and your compliance map are different maps.<\/strong> Compliance friction is where the law forces friction. Trust friction is where your design creates it. Confusing the two means you fix the wrong one.<\/p>\n<h2>How to Choose Your Mapping Approach: Evaluation Criteria That Matter<\/h2>\n<p>There are three ways to build this map. None is universally right. The correct choice depends on your data, your blind spots, and your budget. Here are the three, judged fairly.<\/p>\n<ul>\n<li><strong>DIY from scratch<\/strong> \u2014 your team maps it using internal knowledge.<\/li>\n<li><strong>Generic templates<\/strong> \u2014 you pull a framework from a tool or blog and fill it in.<\/li>\n<li><strong>Guided mapping<\/strong> \u2014 you build it alongside operators who have seen the pattern across many companies.<\/li>\n<\/ul>\n<p>Judge all three against five criteria that actually matter.<\/p>\n<ol>\n<li><strong>Fintech-specificity.<\/strong> Does the approach account for trust and compliance overlays? Templates almost never do. DIY does only if your team already knows to look. Guided input brings it by default.<\/li>\n<li><strong>Quality of data inputs.<\/strong> Do you have real behavioral data plus qualitative signals? No approach saves you if the inputs are assumptions. This is method-agnostic.<\/li>\n<li><strong>Speed to insight.<\/strong> Templates are fastest to a first draft. DIY is medium. Guided is slower to start but faster to the correct answer, because it skips the wrong turns.<\/li>\n<li><strong>Ability to see your own blind spots.<\/strong> This is where DIY is weakest. You cannot see the pattern you have never seen. Outside eyes exist specifically for this.<\/li>\n<li><strong>Cost.<\/strong> Templates are nearly free. DIY costs your team&#8217;s time. Guided costs money \u2014 and the honest question is whether the leak it finds is worth more than the fee.<\/li>\n<\/ol>\n<p>Templates are fast and cheap, and genuinely useful for a first hypothesis. Use one on day one. But do not act on it. A generic template will confidently point you at a leak that is not your real leak.<\/p>\n<p>DIY is honest and grounded in your reality. Its failure mode is the blind spot. You map what you already believe, and the belief is the problem.<\/p>\n<p>Consider a B2B fintech founder at roughly $1.2M ARR. Sharp operator, strong team. They had mapped their journey internally three separate times. Each map was clean. Each missed the same thing.<\/p>\n<p>Their leak was a trust gap in the sales-to-onboarding handoff \u2014 the moment a signed customer got passed to a verification flow that felt cold and unrelated to the warm sales conversation they had just left. The team could not see it because they lived inside both systems and the seam was invisible to them.<\/p>\n<p>It took an outside perspective reframing the question \u2014 &#8220;where does the emotional temperature drop?&#8221; \u2014 to surface it. That is not intelligence. That is pattern recognition from having seen the same seam in other companies.<\/p>\n<blockquote><p>&#8220;The founder mapped it three times and got the same wrong answer three times. The value of an outside operator is not being smarter \u2014 it&#8217;s having seen this exact leak in a company you&#8217;ll never meet.&#8221; \u2014 M Studio operator<\/p><\/blockquote>\n<p>This is where guided mapping earns its cost. Building sales and onboarding infrastructure across a portfolio of ventures taught our team which trust seams predict drop-off. That pattern library is what founders access when they work through the map inside <a href=\"https:\/\/maccelerator.la\/en\/elite-founders\/#eluid0006ca88\" data-wpel-link=\"internal\">Elite Founders<\/a> \u2014 combining your data with cross-portfolio pattern recognition to find the non-obvious leak.<\/p>\n<p>Pick the approach that matches your real constraint. If your constraint is budget, DIY with a template as scaffolding. If your constraint is blind spots \u2014 and after three internal maps, it is \u2014 bring outside eyes.<\/p>\n<h2>The Data You Need Before You Draw a Single Box<\/h2>\n<p>Here is what nobody tells you about journey mapping: <strong>it is a data exercise first, and a whiteboard exercise second.<\/strong> Most fintech maps fail because they are built on internal assumptions dressed up as facts.<\/p>\n<p>A map built from opinion is a hypothesis map. A map built from evidence is an evidence map. Founders who act on hypothesis maps ship fixes to leaks that do not exist.<\/p>\n<p>You need three data inputs before you draw anything.<\/p>\n<h3>1. Quantitative behavioral data<\/h3>\n<p>Funnel analytics broken down by individual step. Drop-off per step, not per stage. Time-in-stage. The step where completion collapses is your suspect \u2014 but only the suspect, not the verdict.<\/p>\n<p>If you cannot see completion rates per verification field, that is your first fix. You are flying blind on the exact stage that leaks most.<\/p>\n<h3>2. Qualitative signals<\/h3>\n<p>This is where trust problems hide. Numbers tell you <em>where<\/em> users leave. They never tell you <em>why<\/em>.<\/p>\n<ul>\n<li>User interviews \u2014 especially with people who abandoned mid-onboarding.<\/li>\n<li>Support tickets tagged for confusion, security worry, or verification trouble.<\/li>\n<li>Cancellation and churn reasons, read for the trust language beneath the surface complaint.<\/li>\n<\/ul>\n<p>A lightweight starter method: interview ten users who dropped off during verification. Ask one question \u2014 &#8220;what were you thinking when you stopped?&#8221; Do not lead. The trust gaps surface in their own words.<\/p>\n<h3>3. Regulatory constraint mapping<\/h3>\n<p>List every mandatory step. KYC, AML checks, disclosures. Mark each as mandatory or self-imposed.<\/p>\n<p>This matters because founders assume friction is required when half of it is self-inflicted. You cannot remove a legal step. You can absolutely re-sequence it and rewrite the copy around it.<\/p>\n<p>Consider a founder who was certain price was driving churn. The plan was a discount. The data said otherwise.<\/p>\n<p>Interviews revealed the real cause: a confusing verification email that read like a phishing attempt. Users got it, felt unsafe, and quietly left. It was a security-perception gap, not a price gap.<\/p>\n<p>The fix was email copy \u2014 clearer sender, plain explanation of why the step existed, a security reassurance line. Activation recovered. They never touched the price.<\/p>\n<blockquote><p>&#8220;They almost cut price to solve a copywriting problem. That&#8217;s what happens when you map from assumptions instead of interviews.&#8221; \u2014 Alessandro Marianantoni<\/p><\/blockquote>\n<p>Frameworks like this \u2014 the difference between a hypothesis map and an evidence map \u2014 are what we break down in the <a href=\"https:\/\/ma-network.kit.com\/\" target=\"_blank\" rel=\"noopener nofollow external noreferrer\" data-wpel-link=\"external\">AI Acceleration newsletter<\/a>, delivered as tactical tools you apply the same week.<\/p>\n<p>Reach evidence before you act. Every hour you spend gathering the three inputs saves you a month of building the wrong fix.<\/p>\n<h2>Turning the Map Into Fixes: Prioritizing the Leaks That Cost You Money<\/h2>\n<p>A finished journey map is worthless until you rank the leaks by what they cost you. Most founders finish the map, feel accomplished, and then fix the leak that is easiest \u2014 not the one that matters. <strong>Rank every friction point by revenue impact, or the map was decoration.<\/strong><\/p>\n<p>Score each drop-off point on three dimensions.<\/p>\n<ol>\n<li><strong>Volume.<\/strong> How many users hit this friction point?<\/li>\n<li><strong>Revenue proximity.<\/strong> How close is this step to money actually moving?<\/li>\n<li><strong>Cost to fix.<\/strong> Copy change, or structural redesign?<\/li>\n<\/ol>\n<p>In fintech, weight revenue proximity heavily. A small leak right before first deposit is worth more than a large leak at the top of the funnel. The user near the money is warm, committed, and one obstacle away from paying you.<\/p>\n<p>A 5% leak at the funded-transaction stage often outvalues a 30% leak at awareness. The awareness users were never close to paying. The deposit users were one field away.<\/p>\n<p>Sequence your fixes into two buckets.<\/p>\n<ul>\n<li><strong>Quick wins:<\/strong> copy rewrites, reordering KYC steps, clarifying a disclosure, fixing a scary email. Days of work.<\/li>\n<li><strong>Structural fixes:<\/strong> trust-building content, compliance UX redesign, rebuilding a handoff. Weeks or months.<\/li>\n<\/ul>\n<p>Do the quick wins first, but only the ones high in revenue proximity. Then measure. Always measure before and after \u2014 a fix you cannot quantify is a guess you got attached to.<\/p>\n<p>Consider a lending startup we worked with. Their onboarding completion was leaking badly. The instinct was to rebuild the product flow \u2014 a structural, months-long project.<\/p>\n<p>Instead they reordered the verification steps. They moved the least-invasive ask first \u2014 a small, low-stakes field \u2014 before the sensitive ones. Nothing in the product changed. The sequence did.<\/p>\n<p>Onboarding completion rose meaningfully. Users who committed to an easy first step were far more willing to complete the invasive ones. That is trust escalation working in your favor instead of against you \u2014 and it cost a sprint, not a quarter.<\/p>\n<p>The lesson: the highest-leverage fintech fixes are often sequencing and copy, not engineering. You find them only when the map is scored by revenue proximity.<\/p>\n<h2>&#8220;We&#8217;re Too Early for This&#8221; and Other Objections, Answered Honestly<\/h2>\n<p>You have objections. Good. Here are honest answers, including the cases where you should not do this at all.<\/p>\n<h3>&#8220;We don&#8217;t have the budget for this right now&#8221;<\/h3>\n<p>Then start DIY. Use a free template as scaffolding and the three data inputs from this article to build an evidence map with data you already own. You do not need to spend money to begin.<\/p>\n<p>The real cost is not the mapping. It is shipping engineering time to the wrong leak. A founder who rebuilds a product flow when the fix was an email subject line has spent far more than any facilitated session would have cost.<\/p>\n<p><strong>Budget is a reason to be disciplined about data, not a reason to skip the map.<\/strong><\/p>\n<h3>&#8220;We can figure this out ourselves&#8221;<\/h3>\n<p>You can. Many should. If you have strong analytics, real interview discipline, and genuine willingness to be wrong, DIY works.<\/p>\n<p>The specific value of outside input is narrow and worth naming honestly: pattern recognition across companies you have never seen. That is what shortcuts the &#8220;we mapped it three times&#8221; trap.<\/p>\n<p>The $1.2M ARR founder was not less capable than you. They mapped it three times and missed the same seam three times because they lived inside it. Outside eyes are not smarter. They have just seen the seam before.<\/p>\n<h3>&#8220;We&#8217;re too early-stage for this&#8221;<\/h3>\n<p>Depends. If you are post-PMF with real, unexplained drop-off between signup and first transaction, you are exactly the right stage. This is your problem, today.<\/p>\n<p>If you are pre-PMF, a full map is premature. You do not have stable behavior to map yet. A lighter hypothesis map is enough \u2014 sketch the stages, note your guesses, move on. Come back when you have real users leaving.<\/p>\n<p><strong>The trigger is not your age. It is whether you have real drop-off you cannot explain.<\/strong><\/p>\n<h3>&#8220;We already have advisors and mentors&#8221;<\/h3>\n<p>Advisors give you their opinion. That is useful. But most advisors have not built onboarding infrastructure across a portfolio of fintech ventures, and general advice does not surface a specific verification-step leak.<\/p>\n<p>The question is not &#8220;do I have smart people around me?&#8221; It is &#8220;does anyone around me recognize this exact pattern?&#8221; If the answer is no, the advice is directional, not diagnostic.<\/p>\n<h3>&#8220;How is this different from a regular accelerator?&#8221;<\/h3>\n<p>A regular accelerator gives you a curriculum and a demo day. The work here is operational and specific to your leak \u2014 building the evidence map alongside operators who bring cross-portfolio pattern recognition and integrate strategy, execution, and communication in the same session.<\/p>\n<p>Drawing on 25+ years across Fortune 500 environments and work with 500+ founders across 30 countries, the frame is not &#8220;here is a template.&#8221; It is &#8220;here is your specific leak and the three ways to close it.&#8221; You can see the shape of that approach in the <a href=\"https:\/\/maccelerator.la\/en\/the-studio-approach\/\" data-wpel-link=\"internal\">Studio Approach<\/a>.<\/p>\n<h2>What Is a Customer Journey Map, and Why It&#8217;s Essential in Fintech<\/h2>\n<p>A customer journey map is a visual document of every stage a customer moves through with your product \u2014 from first awareness to loyal advocate \u2014 including their emotions, questions, and friction at each step. In fintech, it becomes essential because your customers are not just evaluating a product. They are deciding whether to trust you with their money and identity.<\/p>\n<p>That decision is emotional, repeated, and fragile. It escalates through onboarding and resets at any sign of danger. A map that ignores it \u2014 a generic SaaS map \u2014 describes a journey your customers are not actually taking.<\/p>\n<p><strong>Understanding what your customers really want and need in fintech means understanding what they fear.<\/strong> They want the service, yes. But underneath, they need to feel safe. The map that captures both is the one that finds your money leak.<\/p>\n<p>Seen in action, the map stops being a poster on the wall. It becomes a ranked list of revenue-weighted fixes, tied to real behavioral and qualitative evidence, sequenced from quick wins to structural work. That is the difference between a map that decorates a Notion page and a map that moves your funded-transaction rate.<\/p>\n<p>If you want to pressure-test where your specific leak sits, a focused <a href=\"https:\/\/maccelerator.la\/en\/live-presentation\/\" data-wpel-link=\"internal\">founders session<\/a> is the fastest way to get outside eyes on your funnel.<\/p>\n<h2>FAQ<\/h2>\n<h3>What is How to Create a Customer Journey Map for Fintech Companies?<\/h3>\n<p>It is the process of documenting every stage a fintech customer moves through \u2014 awareness, evaluation, onboarding and verification, first transaction, and retention \u2014 while overlaying two fintech-specific variables: trust escalation and compliance friction. Unlike a generic SaaS map, it treats KYC, verification, and disclosures as friction points that inject drop-off, and maps the psychological threshold users cross before handing over money and identity.<\/p>\n<h3>Why is How to Create a Customer Journey Map for Fintech Companies important for startups?<\/h3>\n<p>Because 40-60% of fintech signups routinely fail to complete onboarding or a first funded transaction, and a generic map cannot diagnose why. A fintech-specific journey map pinpoints whether the leak is a UX problem, a trust problem, or a compliance-friction problem \u2014 so you ship fixes to the leak that actually costs you money instead of the one that is easiest to guess at. For a post-PMF startup with unexplained drop-off, this is the difference between recovering revenue and rebuilding the wrong thing.<\/p>\n<h3>How do you implement How to Create a Customer Journey Map for Fintech Companies?<\/h3>\n<p>Start with data, not a whiteboard. Gather three inputs: quantitative behavioral data (drop-off per step, not per stage), qualitative signals (interviews with users who abandoned, support tickets, churn reasons), and a regulatory constraint map (mandatory versus self-imposed steps). Draw the five fintech stages, mark trust and compliance friction at each, then score every leak by volume, revenue proximity, and cost to fix. Ship the high-revenue-proximity quick wins first \u2014 copy and sequencing \u2014 measure before and after, then move to structural fixes.<\/p>\n<h3>When is a startup too early to build one?<\/h3>\n<p>If you are pre-product-market-fit, a full map is premature \u2014 you lack stable user behavior to map. Use a lightweight hypothesis map instead: sketch the stages, note your assumptions, and revisit once you have real users completing or abandoning your funnel. The trigger for a full evidence map is real, unexplained drop-off, not company age.<\/p>\n<h3>How is guided mapping different from doing it ourselves?<\/h3>\n<p>DIY is grounded in your reality but vulnerable to bl<\/p>\n<p><script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Article\",\n  \"headline\": \"\",\n  \"author\": {\n    \"@type\": \"Person\",\n    \"name\": \"Alessandro Marianantoni\",\n    \"jobTitle\": \"Founder & CEO\",\n    \"worksFor\": {\n      \"@type\": \"Organization\",\n      \"name\": \"M Accelerator\"\n    },\n    \"alumniOf\": [\n      {\n        \"@type\": \"Organization\",\n        \"name\": \"UCLA\"\n      },\n      {\n        \"@type\": \"Organization\",\n        \"name\": \"Google\"\n      },\n      {\n        \"@type\": \"Organization\",\n        \"name\": \"Disney\"\n      },\n      {\n        \"@type\": \"Organization\",\n        \"name\": \"Siemens\"\n      }\n    ],\n    \"description\": \"25+ years building for Fortune 500, UCLA faculty, worked with 500+ founders across 30 countries\",\n    \"url\": \"https:\/\/maccelerator.la\/en\/about\/\"\n  },\n  \"publisher\": {\n    \"@type\": \"Organization\",\n    \"name\": \"M Accelerator\"\n  },\n  \"keywords\": \"How to Create a Customer Journey Map for Fintech Companies\"\n}\n<\/script><br \/>\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Person\",\n  \"name\": \"Alessandro Marianantoni\",\n  \"jobTitle\": \"Founder & CEO\",\n  \"worksFor\": {\n    \"@type\": \"Organization\",\n    \"name\": \"M Accelerator\"\n  },\n  \"alumniOf\": [\n    {\n      \"@type\": \"Organization\",\n      \"name\": \"UCLA\"\n    },\n    {\n      \"@type\": \"Organization\",\n      \"name\": \"Google\"\n    },\n    {\n      \"@type\": \"Organization\",\n      \"name\": \"Disney\"\n    },\n    {\n      \"@type\": \"Organization\",\n      \"name\": \"Siemens\"\n    }\n  ],\n  \"description\": \"25+ years building for Fortune 500, UCLA faculty, worked with 500+ founders across 30 countries\",\n  \"url\": \"https:\/\/maccelerator.la\/en\/about\/\"\n}\n<\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Your signups are growing. Your marketing funnel looks healthy. But somewhere between &#8220;created an account&#8221; and &#8220;moved their first dollar,&#8221; 40-60% of your users vanish \u2014 and you cannot explain why. 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