Table of Content

1. Convert—Engage—Retain Users
2. Popular App Analytics KPIs—Track User Metrics
3. In-App Sessions and User Behavior = Tracking Activities
4. App Monetization
5. How unique is your app? Where is the value of your app?
6. Analytics Help with App Marketing

App analytics tools help gather data insights that can impact your business by giving you information you can use for better decision-making. The app analytics data ecosystem consists of devices, mobile apps, and users that interact and create data that must be processed and analyzed to predict a situation.

App analytics is the management and use of data with the right tools and methods. App analytics tools are tailored specifically to mobile apps and measure the effectiveness of users’ interactions with the app features. Analyzing the data helps businesses understand the navigation behaviors and user engagement within their mobile apps.

Convert—Engage—Retain Users

Successful apps commonly measure active usage, engagement, retention, conversion, revenues, locations, and crashes. Depending on the specific business domain or industry, some metrics are more important than others. App analytics provide valuable user information and help run experiments to optimize your app.

A good app analytics tool is Google Firebase, as it integrates easily with your app and popular tools such as Jira, Slack, Data Studio, Google Analytics, and Google Cloud. Other popular app analytics tools are App Annie, AppsFlyer, Amplitude, MixPanel, and App Analytics. In addition, our teams can use third-party tools and build customized solutions that extract data and embed analytics in Tableau.

Popular App Analytics KPIs—Track User Metrics

Monitoring your app KPIs will help you understand user behaviors in order to optimize your App Store Optimization (ASO) and paid search, as well as understand users’ intent and streamline your design marketing strategies.

• Retention Rates
• Cost Per Acquisition (CPA)
• Lifetime Value (LTV)
• Conversion Rate to Install (CR)
• Number of Installs
• Daily and Monthly Active users

Explore data analytics to assist decision-makers and discover solutions to increase business performance and excel in your market.

In-App Sessions and User Behavior = Tracking Activities

You can measure how frequently a behavior occurs as well as an app’s perceived utility to understand the product’s habit-forming potential. Each business and behavior have a different frequency and rules for analyzing it. The perceived utility is the rewarding and useful behavior that a product offers.

Product designers rely on this information to create new habit-forming products while also solving problems. We use app analytics to understand what habits a business model requires, how the problem is being solved currently, and why there is a need to solve the problem. Then we can understand which behavior will convert into a habit.

• Real-time Usage Analysis
• Demographic Analysis
• Time Spent
• Location Segmentation
• Customer Satisfaction
• Trends

But how do we make a product part of a user’s daily routine? First, we must create a trigger, a subtle cue that influences behavior effectively. A trigger moves the user to take an action that becomes a habit over time. Mobile apps provide choices (cues) to act on the desired behavior. Our UX research team can guide you on how to drive new user acquisition and create engagement.

App consulting teams can help to leverage insights and reports from app analytics products with UX and Dev teams to build better user experiences.

App Monetization

Intelligent business decisions from analytics will help you craft your monetization model and strategy.

Krasamo can help you choose which app model is right for your app:

• Premium. A tailored solution with unique features that charges a fee to download and has high engagement rates.
• Freemium (Free). A free model with upgrades and the possibility of converting to premium when users are willing to pay a fee for more features. Freemium is a monetization model suitable for many app types but it requires balancing the value of free vs. paid versions.
• Subscription-Model App. Starts as a free version and charges a fee to subscribe for content or media (paid subscription). Free users are monetized with ads or a certain amount of free content.
• Ecommerce App. A free app that acts as a showroom and a tool for specific users to purchase goods.
• Ad-Supported Apps. Apps that are free to users because advertisers place ads on the app using an ad platform that tailors advertising to users based on their interests, location, and other factors. Therefore, using ads in apps is suitable for specific users and app goals.
• In-App Purchasing (IAP). A free app that will offer a digital product which charges a fee at certain moments, usually for gaming apps. This model can be combined with other models and show advertising selectively to non-paying users.
• In-App Purchasing (IAP) + Ads. This model caters to segments of in-app purchasing with offers while interacting with free users with ads. By adding segmentation and advertising to IAP, the increase in revenue can be considerable. In addition, the app can function with machine learning capabilities to target advertising according to user behaviors.

Understanding your audience behaviors and users before designing your app or improving your current app is key to fine-tuning your monetization strategy.

How unique is your app? Where is the value of your app?

The model you choose will depend on the specifics of your business and its users. App analytics solutions will assist you with these decisions, helping you understand your audience engagement and finding the right way to promote your app.

Analytics Help with App Marketing

How are customers finding your app? Setting up an app analytics tool will help determine the best mix of channels to promote your app, improving visibility and conversions.

• App Store Optimization (ASO)
• Search Engines
• Social Media Engagements
• Paid Advertising (Paid Triggers)
• Marketing Events