How Do I Set Realistic Growth Targets for My Mobile App?

Most apps lose about three quarters of their users within the first three days after download. I've seen this pattern play out dozens of times with clients who come to me after their app has already launched, wondering why nobody's sticking around. And you know what? The problem almost always starts months earlier—before a single line of code was written. It starts with targets that make absolutely no sense.

Here's what typically happens: someone builds an app and sets growth targets based on what they want to happen rather than what's actually realistic for their market, their budget, and their timeline. They'll say things like "we need 100,000 downloads in the first month" without considering that their entire addressable market might only be 50,000 people. Or they'll aim for engagement rates that even the biggest apps in their category struggle to achieve. Its like planning a road trip without checking if you've got enough fuel to get there.

Setting unrealistic targets doesn't just waste money—it destroys team morale and leads to desperate decisions that can sink your app before it finds its audience

I worked with a healthcare startup that launched with wildly optimistic projections. When they didn't hit those numbers in the first few weeks, they panicked and changed everything about the app—the onboarding flow, the core features, even the pricing model. The result? They confused their early users and actually made things worse. If they'd started with honest, research-backed targets, they would've seen they were actually performing quite well for a new healthcare app in their niche. They could have focused on steady improvement instead of chasing impossible numbers. This guide will help you avoid that mistake by showing you how to set targets that are challenging but actually achievable given your specific situation.

Understanding What Growth Actually Means for Your App

Growth is one of those words that gets thrown around constantly in the app world, but I've learned its a lot more nuanced than most people think. When someone says "we want our app to grow," what does that actually mean? More downloads? More active users? Higher revenue? The answer changes depending on what kind of app you're building and what stage you're at.

I mean, I've worked on apps where 100 new users per month was brilliant growth—think of a specialised B2B healthcare app connecting surgeons with rare equipment suppliers. Compare that to a consumer social app where anything less than thousands of new sign-ups per week might signal you've got a problem. The context matters more than the raw numbers, and that's something that took me years to really understand. Before you set any targets, you need to research your market properly to understand what realistic growth looks like in your specific niche.

Here's the thing though: growth isn't just about getting bigger. Sometimes the best kind of growth is getting better at serving the users you already have. I've seen apps with modest download numbers generate serious revenue because they focused on retention and engagement rather than chasing vanity metrics. One fintech app we built had only 15,000 active users but those users were so engaged that the average session time was 12 minutes—that's basically unheard of in finance apps where most interactions are done in under two minutes.

The Three Types of Growth You Need to Track

Growth breaks down into three distinct categories, and you need to understand all of them:

• User growth—how many new people are discovering and downloading your app
• Engagement growth—how often existing users come back and what they do when they're there
• Revenue growth—how much money each user generates over their lifetime with your app

The mistake I see constantly is focusing entirely on user growth whilst ignoring the other two. Sure, getting downloads feels good and looks impressive in pitch decks, but if those users disappear after one session? You're basically pouring money into a leaky bucket. An e-commerce client once came to us frustrated because they'd spent £50,000 on user acquisition and had 30,000 downloads to show for it—but only 2% of those users ever made a purchase. That's not growth, that's just expensive noise. This is where understanding how different revenue models work becomes crucial for setting meaningful targets.

The Metrics That Matter (And the Ones That Don't)

Look, I'll be straight with you—most people track completely the wrong things when measuring app growth. Downloads sound impressive at board meetings but they tell you almost nothing about whether your app is actually successful. I've seen apps with 100,000 downloads that made no money and apps with 5,000 downloads generating six figures in revenue. The difference? They were measuring what actually mattered. If you want to track meaningful progress throughout your development journey, measuring the right milestones is essential from day one.

After building apps across healthcare, fintech and e-commerce for nearly a decade, I can tell you the metrics that genuinely predict success are often the unglamorous ones. Daily Active Users (DAU) and Monthly Active Users (MAU) give you a real picture of engagement; your DAU/MAU ratio tells you how sticky your app is. A healthy ratio sits around 20% for most consumer apps, though I've seen fintech apps hit 40-50% because people check their money daily. Retention is the big one though—if you cant keep users past day 7, you've got a problem. In my experience, 25% day-7 retention is decent for most categories, but subscription apps need to be pushing 40% or higher.

Session length matters but context is everything. A meditation app with 15-minute sessions is performing brilliantly; a news app with 15-minute sessions might be confusing users. I worked on a healthcare app where we obsessed over session length until we realized shorter sessions actually meant we'd made the booking process more efficient—exactly what we wanted.

What You Should Actually Be Tracking

• Retention rates (day 1, day 7, day 30)
• DAU/MAU ratio for stickiness
• Time to first value (how quickly users get benefit)
• Churn rate by cohort
• Revenue per user (not just total revenue)
• Activation rate (users who complete key actions)

Set up custom events in your analytics to track your specific value moments. For an e-commerce app, that might be "added second item to basket"—users who do this convert at 3x the rate of single-item browsers in most projects I've worked on.

Vanity metrics like total downloads or page views feel good but they dont pay the bills. I've had clients spend thousands driving downloads only to discover their activation rate was 12%. That means 88% of people who downloaded their app never even completed signup. Focus on the metrics that connect directly to your business model—whether thats subscription renewals, transaction volume or ad impressions per session. Everything else is just noise.

Industry Benchmarks: What Good Really Looks Like

Right, so you want to know what "good" looks like? I get this question constantly, and honestly, its more complicated than most benchmark reports will admit. Sure, I can tell you that the average Day 1 retention rate sits around 25% across all apps, but that number is basically useless without context—a meditation app and a banking app have completely different retention patterns, different usage frequencies, and different definitions of what an active user even means.

Let me share what I've learned from watching apps succeed and fail. In fintech, we typically see Day 1 retention between 30-40% for well-designed apps, but the real test comes at Day 30 where you're looking at 10-15% if you're doing well. One banking app we worked on started with 22% Day 1 retention, which seemed low until we realised most users only needed to check their account every few days—their Day 7 retention was actually 45%, which told us a completely different story about engagement. The mistake? Everyone was panicking over that initial drop-off when the user behaviour was perfectly healthy.

For e-commerce apps, conversion rates matter more than anything else. If 2-3% of your app users are making purchases, you're in decent shape; anything above 5% means you've got something special. But here's where it gets tricky—those numbers assume you've got quality traffic coming in. I've seen apps with 8% conversion rates that were still failing because their acquisition costs were mental and they'd targeted the wrong audience entirely. When you're building something specific like restaurant ordering apps, your benchmarks need to account for the unique behaviours in that industry.

Healthcare apps are a different beast altogether. We built a symptom checker that had 60% Day 1 retention but only 8% monthly active users, and that was actually brilliant performance. Why? Because people don't want to need a symptom checker every week. The app was there when they needed it, which is exactly what mattered. Gaming apps, on the other hand, need daily engagement to survive—anything below 20% daily active users and you're struggling to build the kind of habit-forming behaviour that keeps the lights on.

Session length is another metric that gets misunderstood constantly. Everyone wants longer sessions, but why? A food delivery app with 3-minute average sessions might be performing better than one with 8-minute sessions because users found what they wanted faster. We measured this with a restaurant booking app where reducing session time from 4 minutes to 2.5 minutes actually doubled conversions—people weren't browsing for fun, they wanted to book a table and get on with their evening.

Churn rates vary wildly too. Subscription apps should be aiming for monthly churn below 5%, but I've worked with fitness apps where 8-10% monthly churn was acceptable because they had strong seasonal patterns and excellent win-back campaigns. The key is understanding your user lifecycle; a 12-month meditation app subscriber is worth much more than three 4-month subscribers, even though the revenue looks similar on paper. This is where planning for long-term relevance becomes crucial for sustained growth.

One pattern I've noticed across hundreds of apps? The best performers aren't chasing every metric—they've identified their north star metric and everything else supports that. For a news app we developed, it wasn't daily active users or session time, it was stories read per week. Once we optimised for that single number, everything else fell into place. Retention improved, ad revenue increased, and user satisfaction scores went up. Sometimes less really is more when it comes to what you measure.

How Your App Category Changes Everything

I can't tell you how many times I've had a client come to me with targets that just don't make sense for their category. They've read about some gaming app hitting 50% retention after Day 7 and suddenly that's their benchmark for a B2B productivity tool. It's a bit mad really, because the expectations users have for a game versus a banking app are completely different—and your growth targets need to reflect that reality.

Gaming apps typically see Day 1 retention around 25-40% if they're doing well, but by Day 30 you're looking at 5-10% for most games. Fintech apps? They often start lower at 30-35% Day 1 retention but hold much better over time—I've worked on banking apps that maintain 20-25% retention after 30 days because people need them for regular tasks. E-commerce apps sit somewhere in between, usually around 20-30% Day 1 retention, but here's the thing: a user who returns once a month and makes a purchase is actually more valuable than someone who opens the app daily and never buys anything. If you're building something highly specialised like apps for construction workers, your retention patterns will be completely different from consumer apps.

The category your app lives in determines not just what good looks like, but what metrics you should be tracking in the first place

Healthcare apps have their own set of challenges—I built a medication reminder app that saw 60% Day 1 retention because its tied to daily necessity, but engagement patterns were completely different from social apps. Session length matters hugely in entertainment categories but means almost nothing for utility apps where quick in-and-out usage is actually preferable. And don't even get me started on comparing subscription app metrics to ad-supported ones; they operate under entirely different economics and user behaviours.

Setting Targets Based on Your Business Model

Your business model isn't just about how you make money—it fundamentally changes what growth targets you should be aiming for. I learned this the hard way when I built an app for a healthcare client who wanted to charge £4.99 upfront. They kept asking why our targets were so different from a free fitness app their competitor had launched. Well, because your economics are completely different, that's why. A freemium app can afford to acquire users at a higher cost because it has time to monetise them later through in-app purchases or subscriptions. But if you're charging upfront? You need immediate conversion, which means your entire funnel needs tighter targets from day one.

Freemium apps—the ones that are free to download but have premium features—need massive user numbers to work. You're typically looking at conversion rates between 1-5% for free to paid users, which means if you want 1,000 paying customers, you need somewhere between 20,000 and 100,000 downloads. That's a big difference. And here's where it gets tricky; your growth targets need to account for that conversion rate specifically. I worked with an education app that had brilliant content but they set their first-year target at 50,000 downloads without thinking about their 2% conversion rate. That meant they'd only have 1,000 paying users, which wasn't nearly enough to cover their development and marketing costs. We had to completely rethink their approach. Building features that create genuine word-of-mouth buzz becomes essential when you need those large user numbers to make freemium work.

Different Models Need Different Metrics

Subscription apps have their own unique challenge—churn. Its not enough to acquire users; you need to keep them month after month. I've worked with fintech apps where the monthly churn rate was around 8%, which might not sound terrible until you do the maths. If you're losing 8% of your users every month, you need to acquire that many plus more just to maintain growth. Your targets need to reflect this reality. One subscription app I worked on set a target of 10,000 new users per month but they were losing 7,000, so their net growth was only 3,000. The board thought they were failing at acquisition when actually their retention was the problem.

Match Your Targets to Your Revenue Timeline

E-commerce apps can be a bit mad really because they might have decent transaction values but low purchase frequency. You can't just track downloads—you need to set targets around active buyers and average order value. I worked with a furniture app where the average customer only purchased twice per year but spent £800 each time. Their growth targets focused heavily on building a loyal base of repeat customers rather than constantly chasing new downloads, which was the right call for their model.

Here's what you should be tracking based on your business model:

• Freemium apps: total downloads, conversion rate to paid, monthly active users, and time to first purchase
• Subscription apps: new subscribers, monthly recurring revenue (MRR), churn rate, and customer lifetime value
• Paid upfront apps: conversion rate from store page views to downloads, refund rate, and long-term engagement
• Ad-supported apps: daily active users, session length, ad impressions per user, and effective cost per mille (eCPM)
• Transaction-based apps: active buyers, purchase frequency, average transaction value, and gross merchandise value

One thing people often get wrong is setting the same growth percentage targets across all metrics. But different metrics mature at different rates. Your downloads might grow 50% month-on-month in the early days but your paying customers might only grow 20% because conversion takes time. That's normal. I've seen too many teams panic because their conversion metrics weren't keeping pace with their download growth when actually that's just how user behaviour works—there's a natural lag between download and purchase. This is particularly true for apps with complex integrations—for instance, when we calculated costs for loan calculator features, we found users needed multiple sessions before they trusted the tool enough to input real financial data.

The key is being honest about your unit economics from the start. If you're spending £5 to acquire a user but they only generate £3 in lifetime value, no amount of growth will save you. Your targets need to be built around getting those economics to work, which might mean focusing on retention improvements before scaling acquisition. I know that sounds obvious but you'd be surprised how many apps scale too quickly before fixing their fundamental business model issues.

Building a Growth Framework That Actually Works

Here's what I've learned after building dozens of apps—having targets is pointless unless you have a system to actually hit them. A growth framework isn't just a fancy spreadsheet; its a living document that connects your business goals to specific actions your team takes every single day. I worked with a fintech app recently where they had brilliant targets on paper, but no one could actually tell me what they were doing differently when installs dropped 30% month-over-month. That's not a framework; that's just wishful thinking.

Your framework needs three components working together. First is your input metrics—the things you directly control like ad spend, content production, or feature releases. Then you've got your output metrics, which are the results like DAU, retention rates, and conversion percentages. The bit most people miss? The connection layer. You need to understand how changing one input affects your outputs, and that only comes from consistent measurement over time. When we built a healthcare booking app, we discovered that adding one extra onboarding screen actually improved 7-day retention by 18% because users understood the value proposition better. Counter-intuitive, but the data doesn't lie. Understanding how onboarding psychology works can make a huge difference to your activation rates.

The Weekly Review Cycle

I recommend reviewing your framework weekly, not monthly. Monthly reviews mean you're flying blind for 30 days at a time, and in mobile that's an eternity. Your weekly review should answer four questions: what changed, why did it change, is it good or bad, and what are we doing about it? Keep it simple. I've seen teams create 40-slide decks that no one reads; we aim for a single page with clear red-amber-green indicators for each key metric.

Build your framework around actions, not observations. Every metric should have a corresponding "if X drops below Y, we do Z" statement attached to it—otherwise you're just collecting data for the sake of it.

When Your Framework Needs Updating

Your framework isn't set in stone. I update ours every quarter based on what we've learned about how different inputs affect outputs. For an e-commerce app we built, we initially thought push notifications were our main retention driver. After three months of proper measurement, we discovered that in-app messaging during browsing sessions had 3x the impact. We shifted resources accordingly and saw retention jump from 22% to 31% over the next quarter. The framework showed us where to focus, but only because we were willing to question our assumptions and adjust based on real data. You also need to consider how technology changes might affect your metrics over time.

When to Adjust Your Targets (And When to Stay the Course)

I've seen plenty of founders panic after their first month of less-than-stellar numbers, ready to throw out their entire growth strategy. But here's the thing—data needs time to breathe. You cant make smart decisions based on a fortnight of metrics, especially if you've just launched. The apps I've worked on that succeeded long-term were the ones where we resisted the urge to change everything at the first sign of trouble.

That said, there are clear signals that tell you when its time to adjust your targets. If you're three months in and your retention rate is below 10% when you'd projected 25%, that's not a blip—that's a fundamental problem with your product-market fit. Same goes if your cost per acquisition is consistently 3x higher than what your business model can support; waiting wont magically fix unit economics. I worked on a fintech app where we'd set aggressive user growth targets but our conversion from sign-up to first transaction was half what we'd projected. We could have kept pumping money into acquisition, but the smart move was to pause, fix the onboarding flow, and then reset our targets based on the improved conversion rate. Before making dramatic changes though, make sure you've got stakeholder alignment on what success actually looks like.

The flip side? Seasonal patterns can trick you into making premature changes. That fitness app that sees downloads drop 40% in December? Don't slash your Q1 targets just because people are eating mince pies instead of tracking calories. Look at year-over-year data, not month-over-month panic. Give your strategy at least 90 days before you declare it broken... unless your burn rate is so high that waiting means running out of runway. Then you need to move fast, even with imperfect data. It's about balancing patience with survival instinct, and honestly, thats something you only learn by getting it wrong a few times first.

Starting With Honest Numbers

After building apps across healthcare, fintech and e-commerce for the past nine years, I can tell you that the most successful projects all start with one thing—honest numbers. Not the numbers you hope to see, not the numbers that'll impress investors, but the real baseline metrics from your specific situation. I worked with a fintech app that set a target of 100,000 downloads in month one because their competitor had achieved that... three years ago with a completely different market and a massive PR budget. They hit 8,000 downloads and considered themselves a failure, when actually that was a solid start for their budget and category. Getting your pre-launch foundation right, including building an email list and understanding your market, sets you up for realistic target setting.

The truth is setting realistic growth targets isn't about being pessimistic; it's about giving yourself the space to actually grow. When you start with honest numbers—your actual budget, your real team capacity, your genuine market position—you can build targets that push you forward without crushing morale. I've seen teams give up on genuinely promising apps because they set fantasy targets and felt like failures when they didn't hit them. That's mad really, because those same metrics would've been celebrated if they'd started with reality.

Look at your industry benchmarks properly. Factor in your monetisation model, your category's typical retention rates, your actual marketing spend. Then set targets that stretch you but don't break you. The apps that succeed long-term are the ones that measure progress honestly, adjust based on real data, and celebrate genuine wins along the way. Your first month might not look like a hockey stick growth chart... and that's completely fine. Most successful apps I've worked on took 6-12 months to find their groove, but they got there because they started with numbers they could trust and built from there.