What Is Mobile Analytics? A Complete Guide

Mobile analytics is the practice of collecting, measuring, and analyzing data from mobile platforms. This can include the mobile web but tends to focus on analytics for native iOS and Android apps, which we’re covering in this blog.

The goal is to understand how customers use your app and what parts they enjoy—this helps you optimize the mobile experience and drive key success metrics.

It might look at:

• User behavior, such as , taps, and
• , including download volumes, demographic data, and referral sources
• , like page views, app rating, or funnel analysis
• covering transactions, revenue, and completion rate
• Technical data, analyzing crashes or errors, feature usage, app versions, and devices or OS versions

Analysis that previously happened in Excel and SQL has mostly been replaced by a handful of tools that make following mobile app analytics best practices much easier. The field now brings together marketing, product design, engineering, and to help improve mobile products.

Analytics for mobile is simply listening to the data your app collects. might be more complex in practice, but it’s often overcomplicated—having a straightforward and data-informed approach makes things clearer.

Let’s break down the different steps to understand how mobile analytics works.

1. Tracking is added to the mobile app codebase to capture in-app events, , and more
2. Data points are captured in the background as users interact with the app—this is temporarily stored locally
3. The locally stored data is moved to the analytic’s platform cloud server on a regular basis, where it’s aggregated
4. The raw data is processed and structured so it can be queried and analyzed—advanced systems might preprocess the data automatically
5. Analysts examine trends in important metrics, and behaviors to gain insights
6. The insights help highlight opportunities to optimize parts of the mobile app experience to improve metrics
7. The team incorporates the optimization recommendations into the app via updates to its design, logic, workflows, messaging, etc

Ideally, this cycle should never end—continuously , analyzing it, and using the insights to make changes leads to a stronger app.

You might also integrate data from other sources—like ads, helpdesk, and —to enable analysis across further systems.

and mobile analytics are both vital to online and app-based businesses.

They have a few shared principles but differ in their approach to data collection, sources, and measured metrics.

Web analytics:

• Gathers data from your website, web apps, and some server logs
• Focuses more on and conversions
• Only deals with some browser or OS variation
• Uses referrers to provide data touchpoints
• Typically uses tags and server-side logging to collect data
• Has a generally more relaxed compliance

On the other hand, mobile analytics:

• Looks at native and hybrid apps, app stores, and attribution tools
• Emphasizes , , and churn
• Handles many device types, screen sizes, and OS versions
• Relies more on ad networks and deep linking
• Uses and platform APIs to gather data
• Has tighter app store and platform privacy rules

Mobile apps are crucial to our daily lives. They are often the primary way people interact with a brand and can become central to our daily tasks.

As a result, businesses need to understand how people use their apps on phones and tablets to give their users the best experience.

Here are a few reasons why mobile analytics are so vital:

• Optimize for small screens: Mobile analytics shows you exactly how mobile users navigate your app, highlighting issues with text size, button placements, or slow page loads. This enables you to tailor the design for taps instead of clicks.
• Personalization: The data shows where and when your mobile app traffic comes from. You can use this to to connect better with customers.
• Track app performance: You can get insightful data on app downloads, usage, demographics, and operating systems. This enables you to spot trends and make app improvements.
• Drive conversions: By gaining clarity on drop-off rates, breakdowns, and high-value , you can boost mobile commerce performance.

In short, it provides that crucial layer of visibility so you can better understand customer needs. The learnings help you tweak your design and marketing approaches to fit your app audience, bringing happier users and more business success.

Getting clear on the different types of ensures you choose the right tools to extract the data that will have the biggest business impact.

Here are the main ones to be aware of.

App monetization analytics

These look specifically at revenue metrics within your mobile app, such as subscriptions, in-app purchases, and ad revenue. Key indicators are and from installs to paying customers.

Advertising analytics

Ad performance analytics offer insight into your user acquisition campaigns. You can measure cost per install vs. (LTV) per user, on different networks, and see which creatives work best.

In-app analytics

In-app analytics track all usage within your app once it’s installed. This shows your most popular content, conversions on calls-to-action, and any issues driving drop-offs. Funnel analysis is crucial for product optimization.

Performance analytics

Performance analytics monitor technical aspects like crashes, load times, and API lag. You can detect bugs, troubleshoot issues quickly, and make improvements so mobile users have a smooth experience in your app.

Mobile analytics provide ongoing value throughout the entire app lifecycle, including during:

• Pre-launch: During development, analytics help inform decisions through early user testing. Use recordings to capture UX issues and to optimize .
• Launch: rely heavily on mobile analytics to track , organic discovery, retention metrics, and reviews. Early technical issues are also quickly flagged.
• Growth: In the growth phase, analytics focus on acquisition channel ROI, building repeat usage through personalized push messaging, and .
• Maturity: For established apps with , mobile teams shift to incremental refinements. Analytics guide A/B tests for feature iterations, new revenue opportunities, and expansion into other regions or platforms.
• Decline: If the metrics indicate a declining user base, analytics help diagnose the failing engagement. assesses whether new or loyal users are dropping off the quickest.

This ongoing intelligence uncovers successful metrics to amplify and address problem areas, enabling brands to better serve their mobile audience.

Implementing a analytics process for mobile apps is easier said than done.

With that in mind, let’s look at how a few businesses solved their and retention challenges with data and careful .

Like web analytics, the best mobile app analytics strategies are straightforward and flexible—here’s how the pros do it.

Pokémon Go

Niantic experienced massive success when it launched —essentially a rebrand from its previous game, Ingress.

Its skyrocketing popularity was down to:

• Tapping into the nostalgia of the Pokémon brand, attracting both older and younger millennials
• Reaching people beyond just players—local businesses also capitalized on increased foot traffic from the game
• Being more approachable for casual gamers, with fun, non-battle elements like finding Pokémon
• Retaining Ingress’s core augmented reality exploration gameplay but skinning it with instantly recognizable Pokémon characters

Although rebranding a moderately successful app is risky, Pokémon GO shows the value of using mobile analytics to reposition your product to have broader mainstream appeal.

Tinder

The better gets at making meaningful matches that lead to relationships, the more users it loses as those people delete the app.

However, this “built-to-churn” model isn’t all bad. Some churn means that Tinder has succeeded in its core value proposition of forging new connections—lapsed users help promote Tinder’s brand as life-changing.

Analyzing enables Tinder to identify these “good churn” patterns that signify user value, such as exchanging contact info. Rather than maximizing the number of (at the expense of value and meaning), the app focuses its mobile analytics on to relationships.

Its goal is to stick to its users’ motivation (finding a partner), not adhere to narrow retention metrics.

Instacart

to track user behavior across web, mobile web, and its mobile apps to understand how to optimize —getting first-time users to place their first grocery orders.

Instead of building its own analytics infrastructure, Instacart used the platform to:

• Bypass engineering distractions and data access bottlenecks
• Track and segment various platforms to diagnose conversion funnel drop-offs
• Redesign its landing page using A/B tests and behavior cohorts, increasing conversion rates by 10%
• Optimize its sign-up flows using funnel analysis

Amplitude empowered informed, product decisions across Instacart instead of just growth team guesses. It removed the company’s reliance on analysts, enabling teams to make faster iterations.

Mobile analytics unlocks several benefits for succeeding in the mobile app era.

Mobile is a popular device

As of 2024, comes from mobile devices. With smartphones being most people's primary internet access point, understanding mobile user behavior through analytics is essential.

Competition is fierce

App stores have millions of apps that lead to billions of downloads. Standing out in crowded app store categories requires constantly optimizing the . Mobile analytics offers the visibility to make quick, data-backed changes.

It's key for product development

Aligning app features and flows to how people actually use your mobile software is crucial for retention. Analytics measures user journeys to uncover and opportunities. This data-driven approach drives app improvements to enhance engagement.

Supports application monetization

Whether apps make money via subscriptions, in-app purchases, or ad revenue, mobile analytics tools help you track these metrics. Monitoring conversion funnels, pricing elasticity, LTV, and other financial KPIs contributes to monetization.

Here are four best practices to accelerate your app growth through analytics.

Track more than one primary metric

Rather than just monitoring daily or monthly active users, track other metrics like retention cohorts, session depth, days to churn, and others. Holistic behavioral metrics reveal much more than .

Cross-platform analytics are important

Understand the differences between iOS and Android users. Platform behaviors can go in different directions regarding engagement, conversions, demographics, and technical aspects like OS versions or devices.

Use the data to collaborate

Sharing your mobile analytics reports across product, engineering, marketing, and other departments helps align teams to core user trends. This breaks down silos for unified actions.

Don't ignore data consent

Respect choices in tracking permissions. Be transparent about data collection while providing opt-out mechanisms and maintaining compliance standards.

Bad data, bias, misinterpretation—there are many ways mobile app metrics can lead you astray if you aren’t careful.

Here are some mistakes you can (and should) to make the most of your app’s analytics.

Relying on default platform analytics

The analytics built into app stores provide basic download and revenue data but usually lack rich behavioral insights. You should invest in robust third-party analytics to track your users across different platforms.

Focusing on overall usage numbers

Superficial metrics like total downloads or daily active users alone don’t reveal why people churn or what drives conversion. Take the time to drill into behavioral cohorts too.

Ignoring platform differences

Don’t assume that iOS and Android have the same behaviors. Differences in usage, conversions, and technical capabilities often vary.

Lacking goals and benchmarks

Tracking analytics without clear goals for optimizing retention, engagement, or other targets is aimless. Ground your measurements in your desired outcomes.

Poor data governance

Failing to protect opens analytics tools to errors in reporting sources, collection tools, visibility constraints, and other gaps that degrade trust.

Ready to level up your mobile app analytics from superficial metrics to actionable insights that fuel growth?

equips mobile businesses with behavioral data to confidently meet their retention, engagement, and goals.

Its cohort analysis, real-time streams, and machine learning alerts empower product, marketing, and engineering teams to deliver top-notch app experiences.

Stop guessing what your users want—Amplitude’s flexible and privacy compliance help you understand their needs and reconfigure your plans to meet them.

Watch your app’s usage, conversions, and loyalty surge as you make vital refinements to outpace your rivals.