15 key indicators of web application effectiveness

The success of a mobile or web app does not depend only on the number of downloads. In today's dynamic digital world, it is crucial to measure and optimize the app's effectiveness with precise metrics (KPIs). This is the only way to understand how users are using the app, what features are most effective, and what needs improvement. In this article, we'll take a look at 15 key indicators that will help you assess the effectiveness of your app, and discuss how to optimize them using examples from major technology companies.

1. Churn Rate.

Definition: Churn rate measures the percentage of users who stopped using an app during a given period. It is a key indicator for subscription and SaaS applications.

Example:

  • Netflix: The company analyzes the churn rate to predict the outflow of subscribers and implement strategies to retain them, such as exclusive content or personalized recommendations.
  • Spotify: Offers free premium trial periods to lower the churn rate and tie users to the service.

How to lower it?

  • Better user segmentation and content personalization.
  • Reminder system for application features.
  • Improve UX and eliminate problematic bugs.

2. retention rate.

Definition: Retention rate determines how many users return to the app after a certain period of time (e.g. 7, 30 or 90 days).

Example:

  • Duolingo: The app sends push notifications reminding users of lessons to encourage regular use.
  • Snapchat: Retention is raised through "Snap Streaks" features that reward daily use of the app.

How to improve retention?

  • Gamification and rewards for regular use.
  • Push notifications tailored to user activity.
  • Regular application updates introducing new features.

3. Daily Active Users (DAU) and Monthly Active Users (MAU)

Definition: DAU indicates the number of active users per day and MAU per month. The DAU/MAU ratio indicates the level of engagement.

Example:

  • Facebook: Regularly monitor DAU/MAU to determine how often users return to the platform.
  • TikTok: Optimizes the recommendation algorithm to keep users coming back to the app every day.

How to increase DAU/MAU?

  • Adding engaging content on a regular basis.
  • Personalization of notifications and interactions.
  • Making it easier to share content with friends.

4. Average Session Duration.

Definition: It measures how long the average user uses an app during a single session.

Example:

  • YouTube: Automatically plays consecutive videos to extend the session time.
  • Instagram: Increases average session time by introducing Reels and Stories.

How to extend the session time?

  • Offer personalized content.
  • Introducing autoplay and endless scrolling functions.
  • Intuitive navigation so the user doesn't have to leave the app.

5. customer Lifetime Value (CLV)

Definition: CLV determines the total financial value the user generates for the company over the lifetime of the application.

Design:

Example:

  • Amazon Prime: Offers subscription to maximize CLV through customer loyalty.
  • Netflix: Invests in exclusive content to increase customer stay time.

How to increase CLV?

  • Personalization of offers and promotions.
  • Loyalty programs.
  • Improve the customer experience and UX of the application.

6 Cost Per Acquisition (CPA) - The cost of acquiring a user

Example:

  • Uber: The company invests large amounts of money in social media advertising campaigns or referral bonuses. It then divides the amount spent by the number of new users to determine how much it cost to acquire one passenger/driver.
  • Revolut: Encourages app installation through referral programs with cash rewards; calculating at the end what the total number of new registrations was against the promotion costs incurred.

How to lower it?

  • Optimization of marketing campaigns (better ad targeting).
  • Use of whisper marketing and referral programs.
  • Testing different advertising channels and investing in those with the highest effectiveness.
  • Reinforce positive reviews and feedback in app stores.


7. Conversion Rate - The percentage of users performing the desired action

Example:

  • Netflix: A desirable action is to start a subscription after seeing the free trial period. The company counts the number of people who switched to a paid subscription after the free period against the total number of testers.
  • Allegro: Tracks how many users actually make a purchase after visiting a product page, so it can test the effectiveness of the interface and product descriptions.

How to increase it?

  • Improved purchase path (fewer steps to complete the transaction).
  • Personalized recommendations (e.g., based on browsing and purchase history).
  • A/B testing of different elements of the application (e.g., the "Buy Now" button in a different place or different size).
  • Clear and attractive offer for users.


8. Bounce Rate - Percentage of users leaving the application after a short period of time

Example:

  • Onet (news app): If a user turns on the app, but closes it after 2-3 seconds without reading any article, this affects a higher Bounce Rate.
  • Online store In the form of an app: If a user quickly abandons it, seeing, for example, an unreadable layout, ads or long loading times, this results in a high rejection rate.

How to lower it?

  • Reduce application loading time (code and resource optimization).
  • Improving the first impression (clear onboarding, clear interface).
  • Eliminate annoying ads at the start.
  • Deliver relevant content right from the start screen.


9. net promoter score (NPS) - User loyalty index


Design:

  1. Users answer the question: "How likely are you to recommend our app to a friend?" On a scale of 0 to 10.
  2. We divide users into:
    • Promoters (9-10)
    • Passive (7-8)
    • Critics (0-6)
  3. NPS = (% Promoters) - (% Critics).

Example:

  • Apple: It regularly surveys NPS, asking iPhone or iPad users about their propensity to recommend a product to others. A high NPS means loyal customers who are willing to share positive feedback.
  • Internet banking (e.g., mBank).: Depending on the feedback awarded in the app examines the percentage of people who actively recommend their services, compared to those who advise against.

How to improve it?

  • Systematic collection of feedback and quick response to customer comments.
  • Improve functionality that is most desired by users.
  • Create loyalty programs and referral bonuses for apps.
  • Open and transparent communication of changes in the application (changelog, newsletters).


10. App Store Conversion Rate - Effectiveness of the app page in the store.


Design:

App Store Conversion Rate=Number of app installs from its store pageNumber of wysˊwietlenˊ app pages×100%

Example:

  • Mobile game (e.g., "Candy Crush"): Analyzes how many people who went to the game's App Store / Google Play page actually downloaded it. Optimizing graphics, description and reviews helps increase the conversion rate.
  • Financial applications (e.g. Revolut): With eye-catching screenshots and high ratings in the app store, they convince users to download faster.

How to increase it?

  • Neat, eye-catching icons and app screenshots.
  • Good descriptions of functionality, including highlighting key benefits.
  • Positive reviews and high average ratings in the store.
  • Frequent updates to show that the application is constantly being developed.


11. time to first purchase

Example:

  • Allegro: Measures how much time elapses between registration and completion of the first transaction to see if new features (such as welcome coupons) encourage faster purchases.
  • Booking.com: Observes how long a user browses offers in the app before booking - knowing this, it can better target offers on specific days.

How to shorten it?

  • Offering coupons or discounts for the first purchase.
  • Clear and simple instructions on how to pay and finalize the transaction.
  • Reminders and push notifications for users who delay purchases for a long time.
  • Use of recommendations based on user interests.


12. Feature Adoption Rate - How quickly users adopt new features

Example:

  • Facebook: When "Stories" was introduced, they measured how many users started creating and viewing them at a certain time after the update.
  • LinkedIn: When the new "Skills" section was added, it was checked to see how many people complete it and how quickly they decide to do so.

How to increase it?

  • Clear communication about the new feature (pop-ups in the app, email notifications).
  • Providing video guides and tutorials.
  • Facilitate access to new functionality (e.g., a shortcut on the home screen).
  • Incentives to use (e.g., bonuses, loyalty points, free trials).


13. Load Time - How fast the application loads.

Design:

  • Charging time is the most commonly measured indicator, in seconds, from the launch of an application (or screen) until it is fully interactive.
  • For subsequent screens: the time to move to the next screen/action in the application.

Example:

  • TikTok: Users expect fast transitions between videos. When delays occur, the risk that users will stop using the app increases.
  • Mobile banking (e.g., PKO BP).: The app needs to display the balance and transaction history quickly - if it takes too long, users lose trust and patience.

How to shorten it?

  • Optimization of resources (compression of graphics, minimization of scripts).
  • Use of cache technology (storing critical data locally).
  • Regular code refactoring (removal of unnecessary libraries and dependencies).
  • Efficient data management from the API (asynchronous loading, pagination).


14. customer support response time.

Example:

  • Amazon: Famous for its quick support; if a user reports a problem, a response usually appears within minutes or faster in chat.
  • Bolt (formerly Taxify): It ensures that drivers and passengers get prompt responses to transit issues, increasing confidence in the service.

How to reduce it (speed up the response)?

  • Implementation of chatbots and automation of answers to frequently asked questions.
  • Well-organized support team working in different time zones.
  • A system for prioritizing requests (e.g., premium users served first).
  • Regular training for customer service staff and clear division of tasks.


15. retention rate - User retention rate

Design:

Retention Rate=Number of active usersˊw after a periodˊlength of time (e.g., after 7 / 30 days)Number of all new usersˊw from a given period×100%.

In practice, it can be counted in many ranges, such as 1 day, 7 days, 30 days after installation.

Example:

  • Slack: Measures how many new team members (workspace) are still actively using the app after 30 days. This allows them to implement onboarding improvements to retain as many customers as possible.
  • Dropbox: After registration, it checks whether the user regularly uploads files to the cloud to assess whether he/she uses the tools effectively and remains active.

How to improve it?

  • Put in place an effective onboarding process (guides, notifications with first steps).
  • Take care of regular push reminders (but not pushy) to encourage people to reopen the app.
  • Develop features to facilitate daily use (e.g., automatic data synchronization).
  • Introduce gamification mechanisms (badges, rewards for activity) - they often mobilize users to return.

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