This article was updated in March 2026
There are lots of factors to be aware of when growing an app, such as tool stack alignment, traffic quality, and product-market fit, as well as time constraints and implementation strategies.
To reach a point where all the teams and stakeholders on the agency and app publisher sides are truly satisfied with the results, it’s important to properly manage expectations and tasks throughout the collaboration. From a publisher’s perspective, it’s important to be aware of the industry benchmarks, be open to possible quick adjustments, and understand the capacity of various teams to collaborate with one another using clearly defined success metrics.
In this article, we’ll shed light on these topics and offer guidance on how to properly define and manage retention and CRM expectations, updated with the latest benchmark data for 2025 and 2026.
Understanding retention rates
Growth teams always try to manage stakeholders’ expectations, but how realistic are they? The retention rate (RR in the mobile industry) is the percentage of people who continue to use an app over a given period of time (week, month, or quarter). In other words, it’s the number of users who still use an app a certain number of days after downloading. The more people retained, the better indication of an app’s long-term health. However, it’s sometimes the case that the publisher’s CRM expectations don’t correlate with industry benchmarks.
In the Phiture CRM/Retention Team, one of our main focuses is to increase retention and engagement rates for our publishers. Usually, the RR is calculated on Day 1, Day 7, and Day 30. These specific days reflect different characteristics of retention.
Day 1 is a good indicator that people aren’t deleting the app right after downloading. It also reflects whether the onboarding experience delivered enough value for users to come back within 24 hours.
Day 7 means they’ve been retained for a week, indicating that the activation strategy is good or the onboarding flow is working, and that the app is beginning to form a habit.
And Day 30 suggests that a habit has been strongly formed around the product and the user might, depending on other factors, be considered “engaged.” It’s widely regarded as a proxy for product-market fit.
Retention rate benchmarks by app category (2025–2026)
Understanding where your app stands relative to the industry is essential for setting realistic goals. According to data compiled from sources including Adjust, AppsFlyer, Statista, and Business of Apps, cross-industry averages in 2025–2026 settle at roughly 25–26% on Day 1, 11–13% on Day 7, and 5–7% on Day 30. However, these averages obscure enormous variation by category.
Here is a breakdown of approximate retention rates by app category, based on recent industry data:
| App Category | Day 1 | Day 7 | Day 30 |
| News | ~27% | ~15% | ~11–13% |
| Banking / Finance | ~30% | ~17% | ~6–11% |
| Shopping (Marketplace) | ~33% | ~16% | ~8–9% |
| Shopping (General) | ~24% | ~10% | ~5–6% |
| Social / Messaging | ~25–29% | ~9–10% | ~4–5% |
| Gaming (Hyper-Casual) | ~32% | ~8–10% | ~2–4% |
| Gaming (Mid-Core / Hardcore) | ~28% | ~10–12% | ~3–5% |
| Health & Fitness | ~20% | ~8% | ~3–4% |
| Productivity | ~17% | ~8% | ~4% |
| Education | ~14–15% | ~6% | ~2–3% |
| Travel | ~16% | ~7% | ~3–4% |
Sources: Statista (H1 2024), AppsFlyer, Adjust, Business of Apps (2026), Sendbird.
News and banking apps consistently lead in long-term retention, which is driven by habitual use patterns and high perceived utility. Marketplace apps (such as Amazon and eBay) outperform general shopping apps considerably, thanks to product diversity and built-in purchase cycles. On the other end of the spectrum, education and travel apps tend to see the steepest drop-offs by Day 30, as learning tends to happen in structured bursts and travel usage is inherently episodic.
It’s also worth noting that iOS consistently outperforms Android in retention. According to Business of Apps, average Day 1 retention on iOS is approximately 24%, dropping to 3.7% by Day 30, whereas Android averages around 21% on Day 1 and just 2.1% by Day 30. Regional differences matter as well: Japan tends to show the highest 30-day retention rates globally, while China shows among the lowest.
For instance, if the industry benchmark shows that user retention barely reaches 5% by Day 30, it’s optimistic to expect a 25% RR. These updated numbers underscore how important it is to calibrate expectations to your specific category, platform, and region.
What counts as “good” retention?
Beyond raw benchmark numbers, it’s important to recognize that what constitutes “good” retention varies dramatically based on business model and customer type, not just app category.
A widely cited framework from Lenny Rachitsky and Casey Winters, based on a survey of 20 leading growth practitioners, offers useful reference points for long-term (six-month) retention. For consumer social products (such as Twitter or Facebook), 25% is considered good and 45% great. For consumer transactional products (like Airbnb or Lyft), 30% is good, and 50% is great. For consumer SaaS (such as Netflix or Spotify), 40% is good, and 70% is great. And for enterprise SaaS (such as Salesforce or Workday), 70% is good, and 90% is great.
In practice, this means that a 25% long-term retention rate could be excellent for a consumer social app but deeply concerning for a B2B SaaS tool. Understanding where your product sits on this spectrum is a prerequisite for any meaningful conversation about retention goals with stakeholders.
A useful complementary metric to consider alongside retention rate is the DAU/MAU ratio (sometimes called “stickiness”), which measures how often retained users actually return. A ratio of around 20% is generally considered good, while above 25% is considered excellent.
Managing challenges, expectations & results
There are plenty of factors to consider that might affect retention uplift and our ability to set realistic expectations with our publishers.
Not all app categories can boast the same degree of user retention, as the benchmarks above make clear. Sometimes, what is considered as “great retention” for one industry is average or even below average for another one. In this case, for each type of business model, there will be different characteristics of successful growth in user retention or engagement.
There are several challenges related to the app’s product, which can affect the publisher’s ability to improve retention. For example, if we’re comparing social apps with utility apps, apps with any social aspect like a feed or messaging features have a higher likelihood of regular interaction. They keep users engaged for longer periods due to the ever-changing and regularly updated content, whereas utility apps tend to be more static. Therefore, it might just be easier for social apps to pull their users back as it requires less cognitive load.
Another consideration is product-market fit. Some of the main indicators of product-market fit are, for example, a flattening retention curve, positive qualitative data, or decent sales. Simply put, if the app doesn’t have product-market fit, all the usual tricks to increase the retention rate won’t bring substantial results.
Traffic quality is another factor. If user traffic in the app is poor in terms of conversion to paying members, it will be almost impossible to impact trial starts and membership conversion rates. Using a product analytics tool like Amplitude or Mixpanel will help to analyze the performance of traffic coming from different sources and understand how the acquisition strategy should be changed, and if there’s a need to redistribute the paid acquisition channels. It’s nonetheless important to have a clear view of the volume of monthly/yearly users to understand how many users you can test and, therefore, how long it takes to reach a statistically significant result.
When it comes to analyzing the retention results, it’s crucial that stakeholders can quickly react to changes the growth strategy may require to reach the desired outcome. For example, A/B testing the onboarding screens or moving the APN prompt further/closer in the onboarding journey may significantly affect the user’s experience. This is something the publisher always has to keep an eye on and be open to testing different options.
We also encourage publishers to hone their focus on 1–2 initiatives at a time rather than trying to tackle all areas of the lifecycle at once. For example, onboarding and activation could be a good place to start as the results would have a knock-on effect on longer-term retention and engagement rates.
On the tactics side, a few levers are proving especially effective in 2025 and 2026. AI-driven personalization of onboarding flows and messaging is becoming increasingly important, as in-app messages and personalized experiences have been shown to boost retention by as much as 30%. Push notification strategy also continues to be one of the highest-leverage tools available; data shows that users who receive even a single push notification within their first 90 days are significantly more likely to remain active. And helping users reach a meaningful “first win” within their initial session (completing a workout, saving money, finishing a lesson) tends to have a substantial positive effect on Day 1 and Day 7 numbers.
The long game
In general, driving retention impact is a more long-term strategy than other marketing initiatives. Sometimes, even if you have signs of good uplift in all of your retention campaigns, it takes time to see the real and proven aggregate impact of all lifecycle campaigns.
Let’s say, for example, we want to know the number of users retained on D30 after implementing a new onboarding flow. In this case, we have to wait until the moment existing users finish the old onboarding and other users start the new one and complete it. Only after we get the results can we compare, and this step alone might take 1–2 months depending on the length of the onboarding and the sample size required to reach statistical significance.
In terms of technical considerations, a properly aligned tool stack, clear taxonomy, and reliable data will be a win-win when it comes to fast retention growth.
The wrap-up
To summarize, there are a lot of factors that might impact CRM expectations and results. Among these factors are tool stack alignment, absence of product-market fit, app traffic, and internal restrictions. Setting realistic goals around CRM programs, grounded in up-to-date benchmarks for your specific category, platform, and business model, and choosing the proper metrics of success, as well as balancing expectations and actions, are the key to effective collaboration between the growth teams and the publisher. The more frank, the better.
Here at Phiture, we’re always happy to receive comments and feedback from our readers. If you have any follow-up questions or would perhaps like to recommend some additional reading or frameworks, don’t hesitate to get in touch.
Read also: How to Use User Research to Optimize App Store Presence (ASO Edition)
And more about Apple Benchmarks:
Read our article “Apple’s Peer Group Benchmarks Explained” or download our Apple Benchmark Dashboard here
FAQ
What is a good app retention rate in 2026?
A good app retention rate in 2026 depends on your app category, platform, and business model. Cross-industry averages are roughly 25–26% on Day 1, 11–13% on Day 7, and 5–7% on Day 30, but some categories perform much better or worse than those benchmarks.
How is app retention rate measured?
App retention rate measures the percentage of users who return to an app after a specific period of time. The most common checkpoints are Day 1, Day 7, and Day 30, which help teams evaluate onboarding, activation, and early habit formation.
Why do retention benchmarks vary by app category?
Retention benchmarks vary because user behavior is different across app types. News, banking, and marketplace apps tend to retain users better because they provide frequent, recurring value, while travel, education, and some gaming categories often see steeper drop-off due to more episodic usage patterns.
What does Day 30 retention tell you?
Day 30 retention is often used as a proxy for habit formation and early product-market fit. If users are still active after 30 days, it usually suggests the app is delivering repeat value beyond the initial install or onboarding experience.
What counts as good retention for different business models?
Good retention depends not only on category but also on business model. What is considered strong retention for a consumer social app may be weak for a SaaS or enterprise product, so benchmarks should always be interpreted in context.
Why is product-market fit important for retention?
Without product-market fit, retention improvements are usually limited. Even strong CRM, onboarding, or lifecycle messaging cannot fully compensate for a product that does not solve a meaningful problem or deliver consistent value to users.
How does traffic quality affect app retention?
Traffic quality has a direct impact on retention because not all acquired users are equally likely to engage or convert. If acquisition channels bring in low-intent users, retention and monetization metrics will often underperform regardless of lifecycle improvements.
What are the best ways to improve app retention in 2026?
Some of the most effective ways to improve app retention in 2026 include optimizing onboarding, helping users reach a meaningful first win quickly, improving push notification strategy, and using personalized lifecycle messaging based on behavior.
Why does retention improvement take time?
Retention is a long-term metric, so it takes time to measure real impact. For example, if you change onboarding, you may need weeks or months before enough users complete the new flow and generate a statistically reliable Day 30 result.
What should stakeholders expect from a CRM and retention strategy?
Stakeholders should expect retention and CRM programs to be iterative, data-driven, and closely tied to product, traffic quality, and testing capacity. Success usually comes from setting realistic benchmarks, focusing on the right metrics, and aligning teams around a small number of high-impact initiatives.
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