--- title: Why 90 of users abandon apps during onboarding process description: Learn why 90% of users abandon apps during onboarding, when they leave, what triggers drop-off, and how better design choices improve early retention. image: https://weareaffective.com/hubfs/learning-centre-images/why-90-of-users-abandon-apps-during-onboarding-process.webp --- [Skip to content](https://weareaffective.com/learning-centre/why-90-of-users-abandon-apps-during-onboarding-process#main-content) [![we\_are\_affective\_logo\_200](https://weareaffective.com/hs-fs/hubfs/we_are_affective_logo_200.png?width=175&height=48&name=we_are_affective_logo_200.png "we_are_affective_logo_200")](https://weareaffective.com) - [Home](https://weareaffective.com) - About Us - [Our Story](https://weareaffective.com/about) - [How We Work](https://weareaffective.com/how-we-work) - Our Services - [App Planning & Strategy](https://weareaffective.com/app-planning-strategy) - [App Design](https://weareaffective.com/app-design-agency) - [App UX Design](https://weareaffective.com/app-ux-design) - [App UI Design](https://weareaffective.com/app-ui-design) - [App Technical Architecture](https://weareaffective.com/app-architecture) - [Existing App Audits](https://weareaffective.com/app-audit) - [Case Studies](https://weareaffective.com/case-studies) - [Pricing](https://weareaffective.com/pricing) - [Learning Centre](https://weareaffective.com/learning-centre) - [Get Started](https://weareaffective.com/get-started) Expert Guide Series # Why 90 of users abandon apps during onboarding process Table of Contents Download numbers are a comfortable lie. An app can rack up a hundred thousand installs and still be dead in the water by Thursday, because the people who downloaded it on Monday never made it past the first screen. The 90 per cent abandonment figure that circulates in product conversations is not an outlier result from a poorly built app. It describes what happens to the vast majority of apps, including well-funded ones built by experienced teams, because the problem is not usually technical. The problem is that the first few minutes of an app experience are treated as a formality rather than as the most emotionally loaded moment in the entire product lifecycle. > The first few minutes are the most emotionally loaded moment in the entire product lifecycle. Users arrive with a question, does this do what I need it to do, and do I trust it enough to find out? The app has somewhere between three seconds and two minutes to answer that question before the user leaves and almost certainly does not come back. What we see again and again is that teams design onboarding around what they want users to do, rather than around [how users actually feel when they arrive](https://weareaffective.com/learning-centre/what-curiosity-looks-like-in-a-first-session-and-why-most-products-design-past-i). Those are different problems entirely, and solving the wrong one is how you end up with a polished onboarding flow that still haemorrhages users before they reach step three. This article is about why that gap exists and what it costs. We will move through the specific moments where users leave, the psychological reasons they leave at each one, and the design decisions that make the difference between a product that retains and one that loses people before they have even seen what it does. ## The 90 Per Cent Figure: What the Data Actually Shows The 90 per cent figure is real, but it is not a single event. It accumulates across several distinct exit points, each with its own cause. [Business of Apps](https://www.businessofapps.com/guide/mobile-app-retention/) reports that 77 per cent of daily active users stop using an app within the first three days of installation. By the end of day one alone, 25 per cent have already gone for good. These are users who never had enough of an experience to form a view either way. The abandonment clusters into three windows. The first few seconds sort for technical performance: slow loading, freezing, crashes, and excessive storage demands will end the session before a single screen of content has loaded. The next window, from around 60 to 120 seconds, is where onboarding design does its damage. Forced registration, confusing flows, invasive permission requests, and the absence of any felt value all fire in this window. Beyond that, the first three days determine whether anyone comes back. What the 90 per cent figure actually shows is that most products have not solved any of these windows. They have solved one, or part of one, while leaving the others intact. A technically clean app with a frustrating registration flow still loses users in minute two. An app with smooth onboarding but no reason to return still falls off the retention cliff at day three. The figure is a composite of multiple failures, which is why addressing it requires looking at each window separately rather than reaching for a single design fix. ## The Abandonment Timeline: When Users Leave and Why The first three to four seconds produce what we call immediate abandonment. Slow loading times and sluggish interactions trigger a split-second judgement that the product is not worth the effort. This window is almost entirely technical, and it is the one development teams have the clearest data on, because analytics capture it easily. The 60 to 120 second window is where design begins to do the damage. This is where onboarding decisions play out: how many screens, what they ask for, whether there is any felt value before the product asks for trust. A user who has downloaded a fitness app after deciding they want to change their routine arrives with a degree of motivation. That motivation is not infinite. Every screen that asks for something before delivering anything draws on it. By screen six of an orientation flow that has not yet shown them what the product actually does, the motivation account is empty. Beyond two minutes, the causes shift again. Hidden costs, a lack of retention mechanisms, and apps that drain battery or consume excessive storage all drive churn in the first three days. These are problems the user could not have known about before downloading. They feel like betrayal rather than confusion, which is why they generate negative reviews and uninstalls rather than just quiet departure. Each window requires a different diagnosis and a different response, and the timeline is the first thing worth mapping before any redesign work begins. ## UX/UI design built around *real* psychology We design app interfaces around how people actually think and behave. User research, psychology-driven UX/UI design and technical specs delivered as one complete package. [See how we work](https://weareaffective.com/how-we-work) [Get started](https://weareaffective.com/get-started) No commitment ## Forced Registration and the First 120 Seconds Forced registration is one of the most well-documented causes of early abandonment, and one of the most persistently common design decisions. When a product demands that a user creates an account before they have experienced anything, it is asking for a level of commitment the relationship has not yet earned. The user has no evidence the product is worth their personal information, their password, or the two minutes of form-filling. We see a drop-off rate of between 15 and 20 per cent in uninstalls at the point of forced early registration. That is not a marginal loss. For a product with 50,000 downloads in its first month, that figure represents between 7,500 and 10,000 users who leave before they have seen anything. The business case for delaying registration until after the user has experienced value is straightforward when the number is stated that plainly. The deeper problem is psychological. Asking someone to register before they have seen what they are registering for creates a [trust asymmetry](https://weareaffective.com/learning-centre/when-users-blame-themselves-for-your-confusing-app-youve-already-lost-them). The product is asking for something real, an email address, a password, personal details, in exchange for something the user can only take on faith. Faith is not what people feel when they are three seconds into their first session of a new app. Curiosity, maybe. Mild optimism, sometimes. Faith has to be earned, and the registration gate arrives before there has been any opportunity to earn it. Delay registration until after a user has completed at least one meaningful action in the product. Give them a reason to hand over their details, rather than demanding those details as the price of entry. ## The Trust Sequence Problem: Asking for Too Much, Too Soon Registration is one version of a broader problem: asking for things in the wrong order. Trust is not a single moment. It builds through a sequence of smaller steps, and each step has to be proportionate to how much trust has been established so far. Asking for something that requires high trust before low-trust steps have been completed breaks the sequence and triggers drop-off. We worked on a map-based fitness social network designed to connect people for runs and cycle rides. Users were dropping off at a specific point in the flow: the moment they were asked to share their precise location with a potential match. The location-sharing request came before users had any opportunity to converse with or learn anything about the other person. We were asking for a high-trust action, sharing your physical location with a stranger, before the product had given users any way to establish even basic familiarity. Moving that step later in the sequence, after users had been able to exchange messages and learn something about who they were meeting, resolved the drop-off at that point. The principle generalises. Every request for personal data, location, payment details, or notification permissions is a trust ask. The sequence of those asks determines whether users feel the product is reasonable and reciprocal, or extractive and presumptuous. [Localytics](https://localytics.com/) found that apps requesting permissions in the first session see up to 60 per cent lower opt-in rates compared to apps that wait until the user understands the value being unlocked. The timing of the ask matters as much as the ask itself. ## Design Friction as an Emotional Experience, Not Just a UX Error Friction in onboarding is usually discussed as a usability problem: too many taps, too many fields, too many steps. That framing is accurate but incomplete, because friction is an emotional experience, and the emotion it produces depends heavily on the context in which it appears. We ran a teardown on a meditation app, and the design contradiction at its core was striking. The visual layer was working well. Soft gradients, breathing animations, and slow transitions were all doing the right thing behaviourally, they slowed users down and created a sense of ease. But the flow asked users to pick a goal (sleep, stress, focus) before they had done anything in the product. That single step introduced a decision at a moment when the user was least equipped to make one. Decision-making creates friction, and friction increases anxiety. For most products, a bit of anxiety in onboarding is a manageable cost. For a meditation app, it is a catastrophic contradiction. The promise of the product is calm. The experience of choosing a goal before your first session is the opposite of calm. As we put it at the time: asking someone to choose a goal in that state of mind adds a decision, and decision is friction, which increases anxiety rather than giving them relief. The visual design and the information architecture were working against each other, and the onboarding flow was undoing the app's entire value proposition before the user had experienced any of it. Map the emotional state a user is likely to be in when they open your app for the first time. Design the first three screens around that state, not around what you want them to do. ## Premature Decision Points and the Cost of Getting the Order Wrong The meditation app teardown made the decision-point problem visible in a particularly clear way, but premature decisions appear across product categories and damage retention in each of them. A decision is a cognitive load event. It requires the user to hold multiple options in mind, assess them, and commit to one. That process takes effort, and effort in the first minute of a new app is a cost the user did not sign up for. Goal-selection, preference-setting, and personalisation flows all have legitimate places in an onboarding sequence. The question is where that place is. Asking a user to tell you what they want before they have any idea what the product offers puts the decision in the wrong sequence. They are choosing between options they do not understand, in a context they have not yet had time to form a view on, under the mild stress of being new somewhere. The better sequence is to let users experience the product first, even briefly, and then to ask. A user who has completed one session of a meditation app, or one workout on a fitness product, or one browse through a skincare range, has a [felt reference point](https://weareaffective.com/learning-centre/why-do-some-apps-feel-like-they-were-made-just-for-you). Their answers to personalisation questions will be more accurate and more considered, and the act of answering will feel like tailoring rather than gating. The order is not a minor detail. Getting it wrong costs users at the exact moment they are most likely to become long-term members. ## When the App Store Has to Do the App's Job There are product decisions that move the onboarding problem outside the app entirely, and those decisions carry a specific cost that is worth understanding clearly. We built an anonymous messaging app that required upfront registration as a structural feature of the product. Anonymous messaging with no account infrastructure creates problems around abuse and moderation that the registration requirement was solving. The registration gate was not a design error. It was a product decision made for real reasons. But that decision had a direct consequence for how we had to approach everything else. Because we could not drip-feed value inside the app, the registration wall meant users had to commit before they could experience anything, all the messaging that would normally unfold through use had to be front-loaded into the App Store presence instead. The [screenshots, the listing copy, the preview content](https://weareaffective.com/learning-centre/thought-leader-series-turn-empty-states-in-your-mobile-app-design-into-bold-bran): all of it had to communicate what the product was, why it was worth registering for, and what a user would find on the other side of that gate. We needed to be much clearer with all of that upfront, so there was a lot of out-of-app optimisation that we would not have needed to do if the onboarding could have delivered value before asking for commitment. The lesson is that every structural constraint on onboarding has a corresponding obligation elsewhere. If the app cannot do its own convincing, something has to do it instead. Knowing which of those you are building shapes how you allocate time and budget across the whole launch. ## How Small Expectation Signals Reduce Drop-Off Not all onboarding improvements require structural redesign. Some of the most effective changes are about setting expectations rather than removing steps. Users abandon processes partly because they do not know how long those processes will take. Uncertainty is uncomfortable, and an onboarding flow with no visible end point feels longer than it is, because the user has no way to calibrate their patience. We worked on a fitness product that required users to move through a series of orientation questions before they could access the core experience. The questions themselves were reasonable, they helped personalise the product and were worth asking. The drop-off in that section was not about the questions. It was about the absence of framing. Users did not know how many questions there were or how long it would take. We made one change: telling users at the start of the section how long it would take. That was the whole intervention. Super simple, not a technical change, but just telling people what to expect meant they went into that section in a much more prepared emotional state. Drop-off in that section fell, and the change cost almost nothing to implement. Progress indicators, step counts, and time estimates are all versions of the same signal. They tell users where they are in a process and, crucially, when it will end. That information lowers the psychological cost of continuing, because continuing feels finite rather than open-ended. [Andrew Chen's analysis](https://andrewchen.com/new-data-shows-why-losing-80-of-your-mobile-users-is-normal-and-that-the-best-apps-do-much-better/) shows that 77 per cent of daily active users are lost within three days, and the gap between that figure and the 40 to 50 per cent drop-off seen by the best products is largely a function of how well the early experience manages user expectations. Tell users at the start of any multi-step onboarding section how many steps there are and roughly how long it will take. The information costs nothing and measurably reduces abandonment. ## The Retention Cliff at Day Three The three-day retention cliff is one of the most consistent patterns in mobile product data. On average, 77 per cent of daily active users stop using an app within the first three days of download. Even the best products see a 40 to 50 per cent retention drop after three days. The gap between those two figures, 77 per cent versus 40 to 50 per cent, represents the difference between a product that communicates its value clearly in the first session and one that does not. Day three is not arbitrary. It sits at the intersection of [habit formation and novelty decay](https://weareaffective.com/learning-centre/why-the-first-thirty-days-decide-the-next-twelve-months-of-retention-in-beauty-a). The novelty of a new product carries users through day one and, for some, into day two. By day three, the novelty has faded and something more substantive has to carry them forward. If the first two days have not established a clear reason to return, a habit loop, a feeling of progress, a social connection, a piece of content they want to come back for, the product loses them at the point where novelty runs out. This means onboarding cannot be thought of as the first screen or even the first session. The onboarding job is complete when a user has internalised a reason to return, and that often takes two or three sessions to establish. Designing for day three retention means asking, during the first session, what will bring this user back tomorrow? That question should shape what you show them, what you ask them, and what you leave them wanting. ## Feature Quantity Versus Experience Quality One of the most common patterns we see in products with high abandonment rates is a surfeit of features in the onboarding flow. Teams build something, and because they have spent months thinking about every capability, every feature feels important enough to introduce during onboarding. The result is a new user who is shown twelve things they do not yet know how to want, and who leaves before discovering the one thing that would have made them stay. The 88 per cent of users who are less likely to return after a bad experience are reacting to a product that made the first experience feel hard, confusing, or overwhelming. A product that does three things well and surfaces them clearly in the first session creates a better first experience than a product that does fifteen things at varying levels of quality and surfaces them all at once. | Approach | User experience | Retention risk | | --- | --- | --- | | All features, first session | Overwhelming, no clear path | High | | Core feature, done well | Clear value, immediate reward | Low | | Progressive disclosure | Value grows with familiarity | Low to medium | The argument for feature restraint is about what users can process and act on in a first session. Cognitive load during onboarding is already high: new interface, new conventions, new decisions. Adding feature density on top of that does not showcase the product's richness. It confirms the user's suspicion that this is going to be complicated. ## Why One-Size-Fits-All Onboarding Fails Most of Your Users Generic onboarding assumes two things that are both wrong. The first is that users arrive in a rational, calm, and consistent state. The second is that users are essentially similar in how they process new information and what they need to feel confident. Neither holds when you look at what actually brings people to a product. Take a skincare app. One user downloads it because a dermatologist recommended it after a consultation about a skin condition. Another downloads it because they saw it in a magazine feature about new beauty tools. A third downloads it because their routine has stopped working and they are frustrated. All three are downloading the same app, but they arrive with different emotional states, different levels of urgency, different baseline knowledge, and different definitions of what a successful first session looks like. A single onboarding flow cannot address all three in a way that feels relevant to any of them. > Generic onboarding focuses on features rather than feelings, missing the emotional state that shapes every first impression. The practical fix is to branch onboarding early based on use case rather than demographics. Asking a user why they downloaded the product, and meaning it as a routing question rather than a data-collection exercise, lets the product present itself in a frame that matches why they are there. This is the difference between a product that listens at the start and one that broadcasts regardless of who is in the room. Linear onboarding, where every feature is presented upfront in sequence, produces an average completion rate of 53 per cent, according to [Chameleon's dataset of 15 million interactions](https://usertourkit.com/blog/progressive-disclosure-onboarding). Contextual, behaviour-triggered disclosure, where information appears as it becomes relevant, brings that figure to 75 per cent. The difference is in whether the content is timed to the user's actual state. ## What Good Onboarding Design Actually Looks Like Good [app onboarding design](https://weareaffective.com/app-onboarding-design) starts before the app opens, with a clear account of how someone arrived at the product and what state they are likely to be in when they do. Mapping use cases does not mean asking users to fill in a survey. It means the design team doing the work of imagining the real-world situation that preceded the download: what the user was feeling, what they were hoping for, and what would make the first two minutes feel like the product understood them. From there, the sequence is about earning each next step rather than demanding it. Deliver something of value before asking for anything in return. Introduce complexity progressively, starting with the feature that most directly addresses why the user is there. Hold registration until after a user has had a felt experience of the product. Time permission requests to moments where the value of granting permission is visible and immediate rather than abstract. 1. Map the real-world situation that brought the user to the product, not just the in-app starting state. 2. Surface the single most relevant feature for that use case in the first 60 seconds. 3. Set expectations for any multi-step section with a time estimate or step count. 4. Delay registration until after the user has experienced something worth registering for. 5. Sequence permission requests to moments where the value of granting them is obvious. 6. Design day three retention into the first session by giving users a clear reason to return. The fitness product that reduced drop-off by simply telling users how long the orientation section would take is a useful reminder that good onboarding does not always mean a wholesale redesign. Sometimes the gap is a single missing signal that would cost an afternoon to add. The starting point is always the analytics: [where are users leaving](https://weareaffective.com/learning-centre/how-to-read-a-user-session-recording-for-emotional-signal-rather-than-task-compl), and at what point in the sequence does that drop-off happen? The answer to that question usually points directly at the problem. ## Conclusion The 90 per cent abandonment figure is the product of specific decisions made at specific moments in the onboarding flow, and most of those decisions are fixable once the cause is understood clearly. Forced registration in the wrong sequence, premature decision points, onboarding that ignores the emotional state of the user, and feature density that overwhelms rather than reassures: these are design problems, and [design problems have design solutions](https://weareaffective.com/learning-centre/5-things-that-make-the-difference-between-so-so-apps-and-stellar-apps-what-your-). The harder shift is conceptual. Onboarding is the period during which a user decides whether the product is worth their continued attention, and that decision is shaped as much by how the product makes them feel as by what it shows them. A product that treats its first two minutes as a formality is gambling that users will persist despite a poor start. A product that treats those two minutes as the most important design problem it has will lose far fewer people before they reach the experience that would have made them stay. The gap between 77 per cent three-day churn and 40 to 50 per cent three-day churn is the gap between products that earn trust in sequence and products that assume it from the first screen. That gap is measurable, and the work of closing it is specific and actionable. If your onboarding drop-off is a problem worth solving, [let's talk about your onboarding experience](https://weareaffective.com/get-started). ## Frequently Asked Questions What does the 90 per cent app abandonment figure actually mean? The 90 per cent figure represents the proportion of users who download an app but stop using it very quickly, often before they have seen what the product can do. It is not caused by a single failure but accumulates across several distinct exit points, including the first few seconds, the first two minutes, and the first three days after installation. When are users most likely to abandon an app? Abandonment clusters into three main windows. The first covers the initial few seconds, where technical issues such as slow loading or crashes drive users away, then comes the 60 to 120 second window, where poor onboarding design does the most damage, and finally the first three days, which determine whether users return at all. Why do users leave during the onboarding process specifically? Users arrive with a fundamental question about whether the app does what they need and whether they trust it enough to find out. When onboarding is designed around what the team wants users to do rather than how users actually feel on arrival, that question goes unanswered and the user leaves. What kinds of design decisions cause users to drop off in the first two minutes? Forced registration, confusing flows, invasive permission requests, and a lack of any felt value are the main culprits in this window. These issues fire quickly and give users no sense that continuing is worth their time or trust. Can a technically well-built app still suffer from high abandonment rates? Yes, and this is a common and costly misconception. An app can be technically clean and still lose the majority of its users if the onboarding flow is frustrating or if there is no compelling reason for users to return after the first session. Why do high download numbers not reflect whether an app is actually successful? Download figures capture installs, not engagement or retention, so they can look impressive while the product is effectively failing. A large proportion of users who install an app never make it past the first screen, meaning the download count and the active user base can be very far apart. What is the most emotionally significant moment in an app's product lifecycle? The first few minutes of a user's experience carry the greatest emotional weight, because that is when trust and relevance are either established or lost. Most teams treat this period as a formality rather than as a critical design challenge, which is a central reason abandonment rates remain so high. Is high onboarding abandonment a problem unique to smaller or poorly funded apps? No, the 90 per cent figure applies broadly, including to well-funded products built by experienced teams. The issue is not primarily one of resources or technical quality but of how the first experience is designed and what priorities shape it. ## Related Articles [![Why the Second Version of a Product Often Loses the Feeling the First One Had](https://weareaffective.com/hubfs/learning-centre-images/why-the-second-version-of-a-product-often-loses-the-feeling-the-first-one-had.webp)](https://weareaffective.com/learning-centre/why-the-second-version-of-a-product-often-loses-the-feeling-the-first-one-had) ### [Why the Second Version of a Product Often Loses the Feeling the First One Had](https://weareaffective.com/learning-centre/why-the-second-version-of-a-product-often-loses-the-feeling-the-first-one-had) There is a feeling some products have that is almost impossible to describe but immediately obvious... by [Simon Lee](https://weareaffective.com/learning-centre/author/simon-lee) [![Why Do Users Trust Certain App Screenshots Over Others?](https://weareaffective.com/hubfs/learning-centre-images/why-do-users-trust-certain-app-screenshots-over-others.webp)](https://weareaffective.com/learning-centre/why-do-users-trust-certain-app-screenshots-over-others) ### [Why Do Users Trust Certain App Screenshots Over Others?](https://weareaffective.com/learning-centre/why-do-users-trust-certain-app-screenshots-over-others) A person scrolling through an app store makes a download decision faster than they think they do.... by [Simon Lee](https://weareaffective.com/learning-centre/author/simon-lee) [![What are the real costs of App Store optimisation?](https://weareaffective.com/hubfs/learning-centre-images/what-are-the-real-costs-of-app-store-optimisation.webp)](https://weareaffective.com/learning-centre/what-are-the-real-costs-of-app-store-optimisation) ### [What are the real costs of App Store optimisation?](https://weareaffective.com/learning-centre/what-are-the-real-costs-of-app-store-optimisation) App Store Optimisation rarely appears on a launch budget. 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