In 2025, mobile apps will remain one of the main channels through which businesses interact with their customers.

Competition in this segment is rapidly increasing, users expect personalized experiences, and changes in Apple’s and Google’s privacy policies make data collection and usage more complex. In this environment, mobile analytics becomes mission-critical — it helps businesses understand how people use their products, what motivates them to stay or leave, and how to allocate marketing budgets effectively.

Just like web analytics, mobile analytics tracks how users interact with a product — in-app events, screen views, clicks, purchases, or cancellations. The key difference is that mobile analytics also accounts for the specifics of mobile platforms (iOS, Android), traffic sources, install attribution, and post-install behavior. This allows businesses to see the entire user lifecycle — from the first touchpoint with an ad to repeat interactions and monetization within the app.

That’s why companies today are looking for tools that go beyond simply counting installs — solutions that help build long-term relationships with users, test hypotheses, and scale business results effectively.

What Is Mobile / Product Analytics

Mobile analytics is the process of collecting and analyzing data about how users interact with mobile applications. It covers the entire user journey — from the moment an app is installed to actions taken inside it, such as purchases, content views, push notification interactions, or cancellations. The main goal of mobile analytics is to reveal how people actually use the product and what drives their decisions.

Product analytics is a subset of analytics focused on understanding how users interact with a product’s features and functionality. It’s not just about traffic or conversions — it’s about whether the features you release actually solve user needs. With product analytics, you can identify which screens break the user flow, which features remain unused, and where friction or drop-offs occur in the customer journey.

How Mobile and Product Analytics Benefit Businesses

Mobile and product analytics help answer the key questions that drive business growth:

• How many users have installed the app, and where did they come from?
• Which marketing channel brings the most high-quality users with strong LTV?
• How do new users behave on their first day, and what affects their retention?
• Why do some users reach the cart but never complete the purchase?
• Which features are used most often, and which ones are ignored?
• How have product changes impacted key metrics such as ARPU, churn, or time in app?

Marketing vs. Product Analytics

Although these two areas are closely related, they address different business needs:

• Marketing analytics (attribution): shows which channel a user came from, how much it cost to acquire them, and which ad campaigns perform best. This is the domain of tools like AppsFlyer or Adjust.
• Product analytics: helps you understand how users interact with the app itself — which features deliver value and where drop-offs occur. These insights often come from tools like Firebase, Mixpanel, or Amplitude.

At the same time, Firebase holds a unique position — it combines product analytics with marketing capabilities, providing data on both in-app user behavior and ad performance through its integration with Google Ads and GA4.

Together, these two types of analytics create a complete picture — from the effectiveness of marketing spend to the quality of the user experience within the product.

Data Analytics Platforms: An Overview

To build an effective mobile strategy, businesses need tools that do more than just count installs. They need platforms that provide a holistic view — showing where users come from, how they behave inside the app, and what drives their long-term value.

Key Platforms

• Firebase

A Google product that combines product analytics, backend services, and seamless integration with Google Analytics 4. Firebase is both a beginner-friendly and powerful tool — offering everything from user behavior and event tracking to push notifications, A/B testing, and crash reporting. It’s a convenient and free starting point, allowing businesses to launch analytics quickly without additional licensing costs — an especially valuable advantage for startups and companies testing early hypotheses.

• AppsFlyer

One of the leading platforms for marketing analytics and attribution. Its strengths include multichannel attribution, deep integrations with ad networks, and advanced anti-fraud modules that help filter out fraudulent traffic. It’s a premium, paid solution typically chosen by mid-sized and large companies that actively invest in performance marketing and want full control over traffic sources, user LTV, and campaign effectiveness.

Alternatives and Complements

• Adjust — a competitor to AppsFlyer with similar functionality, including attribution, anti-fraud protection, and network integrations. It’s often chosen as an alternative due to differences in pricing models or regional availability.
• Mixpanel — a user-friendly product analytics tool that allows for deep analysis of in-app behavior, funnel tracking, segmentation, and retention reporting.
• Amplitude — another powerful product analytics platform focused on behavioral and cohort analysis, as well as hypothesis testing.
• Branch — specializes in deep linking and mobile attribution. It’s often used as an additional tool to improve tracking accuracy for installs and content interactions.

UAQL

Occasionally, in professional circles, you may come across the term UAQL (User Acquisition Query Language). It refers to an approach or toolkit that enables more flexible work with mobile attribution data — such as creating custom reports, combining data from multiple platforms, and building specialized metrics. While it’s not widely known, UAQL can be valuable for data-heavy teams that require a high level of customization and advanced analytical capabilities.

Firebase — Features, Advantages, and Limitations

Firebase is a Google ecosystem that brings together tools for developing, maintaining, and analyzing mobile applications. In the context of analytics, its most important module is Firebase Analytics (now integrated into Google Analytics 4), which enables tracking of user behavior within the app and building reports around key events.

Simply put, Firebase is an all-in-one solution — covering everything from data collection to user communication through push notifications, A/B testing, and Remote Config.

How Firebase Works in the Context of Mobile Analytics

Firebase integrates into an app via its SDK. After integration, every user interaction — opening a screen, making a purchase, viewing content, or clicking a push notification — can be recorded as an event. These events are then sent to Firebase Console and Google Analytics 4, where reports, funnels, retention tables, and other metrics are generated.

Through BigQuery integration, raw data can be exported for custom analysis, which is especially valuable for larger companies with advanced analytical infrastructure and in-house data teams.

Strengths of Firebase

• Google Integration: Seamless connectivity with GA4, Google Ads, and BigQuery, making it easy to unify data across services.
• Low Entry Barrier: The free plan makes Firebase an ideal starting solution for startups and small products, yet it’s also widely used by larger companies — primarily for product analytics and integration within the Google ecosystem.
• Comprehensive Functionality: Includes analytics, crash logging, push notifications, A/B testing, and more.
• Flexibility: Allows you to create custom events and parameters to track the actions that matter most to your business.

Limitations of Firebase

• Multichannel Campaigns: Firebase is less effective for marketing attribution when working with multiple traffic sources. In such cases, an additional tool — like AppsFlyer, Adjust, or another MMP — is usually required.
• No Anti-Fraud Protection: Firebase lacks built-in tools for detecting or blocking fraudulent traffic (e.g., fake installs, click injection, etc.).
• No SKAN Optimization: Support for SKAdNetwork is basic, without the advanced analytics and automated modeling offered by dedicated MMP platforms.
• Product-Focused: Excellent for analyzing user behavior, but limited in cross-channel comparison and ad performance measurement.
• Learning Curve: While getting started is easy, creating advanced reports (via BigQuery or custom events) requires analysts with SQL and big data experience.

AppsFlyer and the AppsFlyer + Firebase Combination

AppsFlyer is a leading platform for mobile attribution and marketing analytics. Its main purpose is to show which channel a user came from, how much their acquisition cost, and what value they brought to the business. Thanks to deep integrations with hundreds of advertising networks, AppsFlyer enables marketers to get a complete picture of campaign performance and optimize their budgets more effectively.

Advantages Compared to Firebase

• Multichannel Attribution: Accurately tracks installs and in-app events across various ad networks — including Meta, Google Ads, TikTok, and programmatic platforms.
• Anti-Fraud Protection: Detects and blocks fraudulent traffic, helping businesses save marketing budget.
• Advanced Attribution Models: Supports flexible attribution settings — including last-click, multi-touch, and SKAdNetwork tracking on iOS.
• Extensive Integrations: Connects with over 10,000 partners and platforms, offering broad coverage for campaign data.

Compared to Firebase, which is primarily focused on product analytics, AppsFlyer is designed specifically for marketing performance and attribution accuracy.

When It Makes Sense to Combine AppsFlyer + Firebase

• Performance Marketing + Product Analytics: AppsFlyer shows which channel brought the user, while Firebase reveals what they do inside the app. Together, they provide a 360° view of the user journey.
• LTV Evaluation by Source: AppsFlyer tracks the install source, and Firebase tracks long-term user behavior — helping identify which channels attract the most valuable users.
• Campaign Optimization: The combination of AppsFlyer’s ad platform integrations and Firebase’s in-app event data enables automated campaign optimization — for example, targeting goals like purchase or subscription.

Pricing, API, and Support Features

• Pricing Model: Typically based on the number of installs or attributed events, with custom enterprise plans available for high-volume usage.
• API Access: AppsFlyer provides convenient APIs for exporting data to BI systems or internal dashboards.
• Channel Support: Integrates with major ad platforms such as Meta Ads, Google Ads, TikTok, Snapchat, Apple Search Ads, and various programmatic networks.
• SKAdNetwork Compliance: Offers full SKAdNetwork support, which is essential for iOS apps operating under the post–iOS 14+ privacy framework.

Platform Comparison: Key Selection Criteria

The right platform depends on your business goals. For some, the basic metrics available in Firebase are enough. Others may need a more advanced marketing solution with multichannel attribution and anti-fraud protection. Below are the key criteria typically used when evaluating mobile analytics platforms.

Key Criteria

• Multichannel Tracking: How well the platform tracks traffic sources across multiple ad networks.
• SKAdNetwork / iOS 14+ Compliance: Support for Apple’s privacy and attribution framework for iOS apps.
• Deep Linking: The ability to direct users to a specific section of the app after clicking an ad.
• Anti-Fraud Protection: Tools that detect and prevent fraudulent installs and fake traffic.
• API / Raw Data Access: Whether detailed, event-level data can be exported to custom BI systems for deeper analysis.

Platform Comparison Table

Recommendations by Business Scale

• Startups and Small Projects: Begin with Firebase — it’s free, quick to set up, and sufficient for basic analytics needs.
• Mid-Sized Businesses with Active Marketing: Consider AppsFlyer or Adjust — these tools provide stronger control over marketing efficiency and ROI tracking.
• Large Companies and Enterprises: The optimal setup is a combination such as AppsFlyer + Firebase (or Adjust + Mixpanel/Amplitude) — delivering a full analytics cycle from attribution to in-depth product insights.

How to Launch Mobile Analytics: A Step-by-Step Guide

Starting analytics the right way is the foundation for sustainable app growth and effective marketing investments. If data is collected incorrectly from the beginning, the business risks making decisions based on inaccurate or misleading information.

Key Steps

1. Create Accounts: Register accounts on your chosen platforms — for example, Firebase Console, AppsFlyer Dashboard, etc.
2. Integrate SDKs: Add the SDKs to your app (separately for iOS and Android). This ensures automatic event tracking and data transfer.
3. Set Up Events: Define key events — such as install, registration, add to cart, purchase, or subscription — and implement them in the app code.
4. Testing: Verify that events are being sent correctly on test devices before launching to production.
5. Data Validation: After the app is live, make sure all events appear correctly in your dashboards and reports.

Firebase Setup Specifics

• The SDK is integrated via Gradle (for Android) and Podfile (for iOS).
• Events can be tracked automatically (e.g., screen_view, session_start) or manually (e.g., purchase, sign_up).
• It’s recommended to connect Google Analytics 4 and BigQuery from the start to ensure scalability and advanced reporting capabilities.
• Firebase has a limit of up to 500 custom events, so it’s important to define and prioritize key events early on.

AppsFlyer Setup Specifics

• The SDK is integrated similarly for iOS and Android, but requires additional configuration for attribution.
• You’ll need to connect integrations with the ad networks you plan to use — such as Meta, TikTok, Google Ads, etc.
• It’s recommended to configure in-app events (e.g., first_purchase, subscription_start) early on to enable more precise campaign optimization.
• For iOS, make sure to properly implement SKAdNetwork — without it, attribution data will be limited or incomplete.

Nuances of Launching Multilingual Analytics / Language Support

• If your app supports multiple languages, it’s crucial to standardize event names and parameters. For example, use a single event name like purchase_completed across all languages, and track the locale through a parameter such as language (e.g., ua, en, pl).
• For push notifications and A/B testing via Firebase Remote Config, create separate user segments for each language version.
• In AppsFlyer, multilingual setup is handled through campaign-level targeting — segmenting audiences by country and language helps optimize ad spend and improve campaign relevance.

The Role of an Agency in Analytics Setup

An agency helps businesses transform raw data into actionable insights. It’s not just about configuring SDKs or building reports — it’s about creating a system where every marketing dollar and every product change is measurable through data-driven metrics.

Such agencies act as a bridge between analytics tools (such as Firebase, AppsFlyer, or Adjust) and business objectives, ensuring proper integration, accurate interpretation of results, and strategic recommendations for sustainable growth.

When to Involve an Agency

• You’re launching a mobile product and don’t yet have in-house analytics expertise.
• Your campaigns are scaling, but you lack clarity on which channels truly drive LTV-positive users.
• Your data is fragmented across multiple systems, and you need a unified reporting framework.
• You want an objective evaluation of your marketing efficiency and expert support in budget optimization.

Example Tasks an Agency Can Handle

• Implementation: Integrating Firebase or AppsFlyer SDKs, configuring attribution models, and defining key in-app events.
• Tuning: Auditing existing setups, fixing tracking errors, and optimizing event structures.
• Analysis: Building user cohorts, studying retention, and analyzing LTV by acquisition channel.
• Dashboarding: Creating interactive dashboards in Looker Studio, Power BI, or Tableau for clear and actionable data visualization.

Pitfalls, Risks, and Limitations

In mobile analytics, it’s crucial to remember that the platforms themselves set the rules. Apple’s introduction of AppTrackingTransparency (ATT) in iOS 14 requires users to explicitly grant permission for tracking. Similarly, Google is gradually implementing the Privacy Sandbox for Android, which limits access to user-level data.

As a result, some data becomes unavailable, and businesses must adapt their measurement strategies, shifting toward aggregated reporting, modeling, and privacy-compliant attribution methods.

iOS / SKAdNetwork / GDPR Limitations

• SKAdNetwork (Apple): Transmits only limited, aggregated data — often delayed and without user identifiers — which makes real-time campaign optimization challenging.
• GDPR and other privacy regulations: Require transparent data collection and processing with explicit user consent. Non-compliance can lead to substantial fines.
• Android Privacy Sandbox: Upcoming updates will further restrict access to personal identifiers, forcing marketers to rely more on modeled conversions and aggregated metrics.

Common Setup Mistakes

• Incorrect SDK integration: Data may not be collected at all or may be sent with errors.
• Double-counting installs or events: Common when using multiple platforms simultaneously (e.g., Firebase + AppsFlyer).
• Misconfigured events: For example, the business wants to track purchases, but the app only sends checkout_started.
• Inconsistent event naming conventions: Lack of standardized naming makes analytics and scaling far more complex.

How to Avoid These Mistakes

• Run test sessions on real devices before launch and verify that all events appear correctly in dashboards.
• Use a unified event taxonomy — consistent naming for all events and parameters.
• Perform regular audits of integrations and configurations to catch data gaps early.
• Comply with legal requirements: include tracking consent screens and keep your privacy policy up to date.
• Combine multiple data sources (Firebase, AppsFlyer, BI tools) to offset data loss caused by privacy and tracking restrictions.

Conclusion and Recommendations

Mobile analytics in 2025 is not just a reporting tool — it’s a strategic asset. Without it, businesses risk losing both customers and marketing budgets. It answers the essential questions: Where do users come from? How do they interact with the product? What drives long-term value? By combining tools — from Firebase to AppsFlyer — you can see your performance from multiple angles: marketing, product, retention, and monetization.

At newage., we help companies navigate this path with structure, not chaos — from tool selection and SDK implementation to testing, event modeling, and dashboard development. We integrate SDKs, set up custom event structures, configure attribution tracking, build retention and LTV analytics, and create interactive dashboards in Looker Studio, Power BI, or Tableau.

If you want to launch analytics from scratch, optimize your current setup, or scale your performance marketing, reach out to newage. — we’ll help you build a transparent and efficient analytics ecosystem that fuels your business growth.

FAQ

What is mobile analytics, and how does it differ from web analytics?

Mobile analytics tracks the entire user journey inside a mobile app — from installation to purchases or churn. It also accounts for platform specifics (iOS/Android) and integrates with ad networks for attribution. Web analytics, on the other hand, focuses mainly on website interactions and traffic sources.

Firebase or AppsFlyer: which one should I choose?

Firebase is best for product analytics — understanding user behavior, running A/B tests, and managing push notifications. AppsFlyer excels in marketing attribution and ad spend optimization. Many businesses use both tools together to combine marketing and product insights for a complete analytics setup.

Can I set up mobile analytics on my own?

Yes, but there’s a high risk of configuration errors — such as incorrect SDK setup or event tracking — which can lead to inaccurate data. That’s why many companies partner with agencies to save time and ensure a reliable, high-quality data foundation from day one.

What are the main limitations of mobile analytics?

Apple’s ATT and SKAdNetwork policies and Google’s Privacy Sandbox limit access to user-level data. Other common issues include double-counted installs, poor event modeling, and inconsistent event naming, all of which can distort analysis.

How can newage. help with analytics implementation?

As an analytics and performance agency, newage. helps businesses choose the right platform, integrate SDKs, configure attribution models, build a clear event tracking structure, and create insightful dashboards while performing comprehensive data audits. This ensures that your company can make truly data-driven decisions based on accurate and actionable insights.