data collection for app analysts

Dear app analysts, you’re drowning in data. Global data creation is forecasted to skyrocket to 394 zettabytes by 2028. Yet, many of you struggle to collect data efficiently. It limits the ability to analyze app performance and user experience.

If you don’t do something about it quickly, you’ll miss out on gaining valuable insights, retaining players, and increasing your app’s profit. The right data collection techniques will set up your app for long-term success.

Key Data Collection Statistics

Data collection is crucial for app development. But many companies struggle with overwhelming volumes of data. This makes it more challenging to generate actionable insights. The following statistics demonstrate this.

  • 51.38% of iOS apps have collected user data globally in 2024.
  • 87.9% of Fortune 1000 companies prioritized investing in data collection and analytics in 2024.
  • 78.5% of this survey’s respondents say data collection/analytics positively impact user loyalty and profit.
  • 49% of companies surveyed by Harvard Business Review can’t consistently collect large data volumes and turn them into actionable insights.
  • 60%+ of the global workforce works while standing or in the field, increasing data collection opportunities from apps.
  • 87% of app users don’t respond to in-app surveys, making them unreliable for data collection.
  • 70% of this study’s respondents are overwhelmed by collecting and interpreting large volumes of data.

Now that you get its impact, let’s pinpoint methods for better data collection to analyze your app’s performance.

10 Data Collection Techniques for App Analysts

Using any technique for data collection is better than nothing at all. But the more techniques you use, the more reliable you’re eventual findings will be. 

We’ve highlighted 10 techniques app analysts should use, including analytics solutions for each one. Seven of them are mainly for collecting quantitative data, while the remaining three are qualitative.

Quantitative Data Collection Techniques

Quantitative data refers to data that can be counted and measured. This includes metrics for engagement (CTR, Heatmap aggregates), user interaction (DAU/MAU, session duration, etc.), and performance. 

Here are some techniques that app analysts can use to collect quantitative data.

TechniqueHow it WorksPros (+) and Cons (-)Top Tools
1. In-app analyticsTracks user interactions and behavior, highlighting user journeys and patterns.+ Real-time, quantitative data.
– Doesn’t reveal the root causes of user actions.
Mixpanel, Amplitude, CleverTap
2. A/B testingTests different versions of app features, highlighting what’s more user-friendly.+ Provides strong data to improve app feature development.
– Requires high traffic and user volumes for meaningful results.
Amplitude, Firebase, GameAnalytics, MixPanel
3. HeatmapsVisualizes where users scroll, click, and engage on an app’s interface, informing UX optimization.+ Easy to read, understand, and interpret.
– Doesn’t provide qualitative insights on user behavior and motivation.
Hotjar, Mouseflow, GameAnalytics, Smartlook, FullStory
4. Session recordings (can also collect qualitative data)Records user sessions, presenting usability issues and pain points.+ Provides a detailed overview of user behavior.
– Analyzing large data volumes can be time-consuming.
Amplitude, UXCam, Smartlook, LogRocket, FullStory
5. Device and OS dataCollects data on device types, screen resolutions, and OS versions to optimize performance.+ Good for device-specific problems (e.g. bugs).
– Doesn’t highlight user behavior or preferences.
Firebase, Amplitude
6. User demographicsAccumulates user demographic data (gender, age, location) to personalize features.+ Deeper insights into who is using the app.
– Users can supply false information, making data inaccurate.
Google Analytics, Firebase
7. Cohort analysisTurns shared user behaviors and characteristics into groups to analyze long-term retention.+ Makes user analysis more organized.
– Can be difficult to implement and analyze.
Mixpanel, Amplitude

Qualitative Data Collection Techniques

Qualitative data consists of non-numerical findings, providing insights into user experiences, feelings, and concepts. Typical examples include user feedback, reviews, comments, and reactions.

The three techniques below are exclusively for collecting qualitative data.

TechniqueHow it worksPros (+) and Cons (-)Top Tools
8. User FeedbackLeveraging user feedback and ratings in the app to improve features.+ Users can submit feedback directly in the app.
– Data might be unreliable due to biased feedback.
Google Analytics, Firebase, Alchemer, Apptentive
9. App Store ReviewsProvides insights on app features and performance.+ Useful for improving app features
– Can be biased, therefore unreliable.
Appfollow, Mixpanel, Amplitude
10. User Surveys and Questionnaires Gathers user feedback, opinions, and preferences.+ Great for gathering insights into user preferences.
– Notorious for low response rates.
SurveyMonkey, Google Forms, TypeForm

FAQs

What is Data Collection in App Analytics? 

When it comes to app analysis, data collection is the gathering of quantitative and qualitative data to better understand an app’s performance and user experience. 

Why is Data Collection Essential for App Analytics?

For data analysts, many benefits come from collecting data to measure their app’s performance. It allows developers to:

  • Make data-driven decisions
  • Understand user behavior and preferences
  • Troubleshoot issues and fix bugs
  • Improve monetization models
  • Optimize the app’s design and features
  • Devise stronger user retention strategies
  • Identify trends for future development.

What are the challenges of collecting data for app analytics?

Collecting data for analyzing apps still presents obstacles. Here are some examples:

  • Collecting large data volumes: Many companies are overwhelmed by the need to collect and interpret large volumes of data. Consider tools for collecting large data sets, streamlining data collection, and drawing valuable insights.
  • Unreliable techniques: Some data collection methods, like in-app surveys, prove to be less reliable than others. Research other strategies and tools to maximize your app analysis’s level of detail.
  • Lack of resources or expertise: Data collection and analytics can impact loyalty and profit. In fact, 80% of businesses see revenue increases thanks to real-time data. However, many companies lack the necessary resources to fully reach their potential.

Time to Start Collecting…

To effectively analyze your app, you need to use powerful data collection tools and techniques. Depending on your budget and timeline, we recommend combining some of the techniques mentioned above. This way, you can collect and analyze many data types at once to give you a bigger picture of your app’s overall performance.

By leveraging quantitative and qualitative techniques, you can alleviate some of the challenges of collecting data. Then, you can gain actionable insights, optimize your user experience, and boost retention.

1 Comment

  1. Jonny

    Super useful article! I feel a lot calmer about handling big data now!

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