App Conversion Rate Benchmarks by Category
Real conversion benchmarks for major app categories, so you know whether your numbers are good, bad, or just average.
Most founders who ask "is my conversion rate good?" are asking the wrong version of the question. The right version is: "good compared to what, and at which step?"
A low trial-to-paid rate means something very different in a meditation app than in a project management tool. A modest install-to-register rate can signal a broken onboarding flow or a tight, intentional audience filter, depending on the category. Without a category-specific benchmark, you are reading a number with no frame around it.
This post collects published and widely cited industry benchmarks by major app category. It explains which funnel steps matter most for each type, and gives you enough context to know what to do with your own numbers.
Why Category Matters More Than the Overall Average
Overall app conversion averages get cited constantly and are nearly useless in practice. Blending consumer games, enterprise tools, and e-commerce apps into a single number produces a figure that accurately describes none of them.
Three structural reasons explain the variation:
Purchase intent differs. Someone downloading a barcode scanner has immediate, specific intent. Someone browsing a "top free games" chart is mostly curious. Intent shapes every downstream metric.
Price points differ. A low-cost sticker pack has almost no friction to purchase. A high-priced monthly subscription requires trust, repeated use, and sometimes team approval. The funnel is longer and conversion is lower, but revenue per conversion is much higher.
Monetization model differs. Freemium apps convert a small slice of a large base. Paid-upfront apps convert at the store listing before install. Each model demands different optimization priorities.
Keep those three factors in mind as you read the benchmarks below.
The Three Funnels You Should Be Measuring
Before the numbers: make sure you are measuring the right steps.
Store Listing Conversion (Impression to Install)
This is the percentage of people who see your store listing and tap install. It is shaped by your icon, screenshots, app name, and first few lines of description.
This metric belongs to App Store Optimization. It runs before the user ever touches your product.
Install to Register (or First Meaningful Action)
This captures how many people who install actually complete onboarding. "Register" is a proxy. For some apps the real signal is completing a profile, connecting an account, or finishing a tutorial.
This is where onboarding design lives.
Trial to Paid (or Free to Paid)
For subscription and freemium apps, this is the conversion rate from active free user to paying customer. It is the most discussed metric in mobile growth and also the most misquoted, because definitions of "active free user" vary widely.
Now, the benchmarks.
Benchmarks by App Category
Consumer Games
Store listing conversion for games is notably low on both platforms, and lower still on Android where volume and competition for attention are highest. Install-to-engagement numbers are high early: a large share of players will open the game a second time. But retention in the weeks after install falls sharply for casual games.
Monetization in games is rarely a clean trial-to-paid funnel. Most games rely on in-app purchases from a small fraction of engaged players. A commonly cited pattern is that a tiny minority of players accounts for the majority of in-app purchase revenue. If you are building a game, your job is less about conversion rate and more about identifying and retaining that paying segment early.
What to watch: Early retention and session depth. Conversion to first purchase often follows high engagement, not good paywalls.
Productivity and Utility Apps
Store listing conversion here tends to be higher than games because intent is clearer. Someone searching "expense tracker" wants an expense tracker.
Install-to-register rates for well-designed productivity apps are strong. Onboarding matters enormously here. Users are often willing to set up an account, but they will quit if the first session asks for too much before delivering value.
Trial-to-paid conversion for productivity apps with a short free trial is meaningfully positive, according to published Sensor Tower and mobile growth reports. Apps with a longer trial often see higher absolute conversions but similar or lower rates, because the extended trial attracts more casual testers.
What to watch: Time-to-value in the first session. Users who hit a clear "aha moment" in session one convert at multiples of those who do not.
Health and Fitness Apps
This category is crowded and heavily dependent on seasonality. January installs convert at higher rates than June installs because intent is stronger.
Store listing conversion is modest. Install-to-register is often high because fitness apps tend to use strong onboarding flows that personalize quickly. The question-and-answer onboarding pattern ("What's your goal? How active are you now?") is common because it works. It signals that the app will be tailored, and users invest time before they even see the paywall.
Trial-to-paid for fitness subscription apps lands in a positive range for well-built products. Apps that show progress data within the trial window convert significantly better. Apps that gate everything behind payment immediately see lower install-to-trial rates but higher trial-to-paid. That is a deliberate trade-off some teams make intentionally.
What to watch: Whether you are optimizing for volume or quality at the top of the funnel. The two strategies lead to very different product decisions.
B2B and Productivity SaaS (Mobile Companion Apps)
This category behaves differently from pure consumer apps. Most B2B mobile apps are companions to a web product. "Conversion" often means activating an existing web user on mobile, not acquiring a new customer through the store.
For standalone B2B mobile apps, store listing conversion is lower because the audience is smaller and more targeted. Trial-to-paid conversion is meaningfully higher. Published benchmarks from OpenView Partners and similar B2B SaaS research show mobile-first B2B tools achieving strong trial-to-paid rates when the trial experience is well-designed.
The reason is straightforward: B2B users who download a tool for work already have a problem they need solved. The conversion question is whether the app solves it quickly enough.
What to watch: Time to completing the core workflow. B2B users will pay if the app saves them time on something they already do repeatedly.
E-commerce and Shopping Apps
Store listing conversion for shopping apps is low because browsing intent is high and purchase intent at install time varies widely.
Install-to-account-creation rates are strong because the value exchange is clear: create an account, save your cart, get order updates.
Add-to-cart-to-purchase conversion is where e-commerce apps live or die. Industry benchmarks put mobile app cart conversion notably higher than mobile web, but lower than desktop web. Apps that use persistent carts, push notifications for cart abandonment, and saved payment methods close that gap considerably.
What to watch: Cart abandonment recovery. It is the highest-leverage intervention in e-commerce app monetization, and most small teams underinvest in it.
On-Demand and Marketplace Apps
Two-sided marketplaces are hard to benchmark cleanly because conversion depends on supply availability in the user's location. A food delivery app with great onboarding still converts poorly if no restaurants deliver to the user's address.
As a category, on-demand apps see a meaningful share of installs convert to a first order when supply is available. The gap between install and first transaction is often a supply or availability problem, not a product problem.
Trial-to-paid is rarely the right metric here. Order frequency and reorder rate matter more.
What to watch: First-session supply match. If the user sees availability, they order. If they do not, they churn and rarely return.
What to Do With These Numbers
Three things.
First, locate yourself accurately. Compare your metrics to your category, not to some global average. A modest trial-to-paid rate is fine for a fitness app and needs attention in a B2B tool.
Second, identify which funnel step you are actually behind on. Founders often work on the wrong problem. If your store listing conversion is at category average but your install-to-register is well below benchmark, more ASO work will not help. Fix onboarding first.
Third, be careful with averages. These benchmarks represent middle-of-the-road outcomes. Top-quartile apps in every category beat these figures, sometimes significantly. The benchmark tells you whether you have a problem. It does not tell you what good looks like when things are working well.
The Measurement Habit Matters More Than the Benchmark
Benchmarks are context, not targets. The most useful thing is to measure your own funnel consistently, so you can see movement over time and isolate which changes actually worked.
Most of the teams Goodspeed works with start by not knowing their funnel numbers at all. Getting those numbers visible is the first step. The benchmark tells you what to think once you can see them.
If you are building an app and want conversion tracking and growth tooling built in from day one, rather than bolted on after launch, that is worth thinking about before you ship, not after.
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