Understanding Users: The best In-App Analytics Tools for Product Optimisation

in app analytics

Whether you have an app or an apple cart, it is a universal business truth that it’s only by understanding your user that you can optimise your product. That is where in-app analytics come into play. Once you have cold, hard data to illustrate user preferences and pain points, you can make data-driven decisions on what needs to be done. And not only that, but you can also allocate resources accordingly, prioritising projects according to where you can make the most impact.

Optimising your app helps to increase engagement, conversion and ultimately, revenue. When you combine this basic level of optimisation with a more sophisticated segmentation of your users – understanding what kind of person responds to what element – you can begin to personalise their experience. And as we know, personalisation pays. 

What do in-app analytics tools offer? 

To integrate an in-app analytics tool, you will need to integrate a software development kit (SDK) into your app. This collects data on user events, actions, and behaviours which is then analysed by the analytics platform and fed back as insights and reports via their dashboards. 

An analytics tool will allow you to measure your own defined events and user behaviours, but could include most – if not all – of the below. 

  • User events
    • App open
    • In-app purchases
  • User behaviour
    • Session duration
    • Frequency of app use
    • User flow
    • Drop off points
  • Conversion tracking
    • Completed purchases
    • Registration
  • Segmentation by
    • Demographic
    • Geographies
    • Customer value
  • Other (dependent on tool capabilities)
    • Funnel analysis
    • Heatmaps 
    • A/B testing

Popular in-app analytics tools

(in alphabetical order)

As is the case when selecting any tool, in-app analytics tools vary, and different tools are suited to businesses of different sizes, technical capabilities and stage of growth. We’re here to guide you towards the one that will best suit your needs – you’ll find a selection of the best below, listed alphabetically. 

Amplitude

Why we like it:

Amplitude Analytics stands out in the market by offering a comprehensive platform that combines advanced user behaviour analysis, robust event tracking, cohort analysis, real-time analytics, data visualisation, and scalability. Product teams like it because it  empowers them to make informed decisions and drive impactful results. Developers like it because of the level of customisation and control provided. 

Key features:

  • Funnels, cohort analysis, and path analysis to understand user behaviour and journey 
  • Customisable dashboard
  • Robust APIs for data accessibility and data export capabilities

Best suited to: 

From start-ups to enterprise (around 1M active users), and those looking for something more tailored to developers.                                                                          

CleverTap

“CleverTap is an All-In-One Customer Engagement Platform that drives customer lifetime value by acquiring deep customer insights, enabling experimentation and hyper-personalization at scale tailoring a true omnichannel experience. The platform is powered by TesseractDB that ensures data granularity, security, unlimited data storage, faster data processing and instant AI/ML based recommendations. With CleverTap, businesses can truly understand, optimize and engage with customers while creating meaningful digital relationships in today’s dynamic market.” – Pravin Laghaate, Vice President, Europe, and UK, CleverTap.

Why we like it:

CleverTap’s Behavioral Analytics feature helps companies gain a comprehensive understanding of user behaviour, optimise user journeys, segment users effectively, measure engagement, identify churn risks, and make data-driven decisions. The product is primarily focused on customer engagement and retention, so it’s particularly useful for clients who want to manage their in-app analytics and customer engagement in one platform.

Key features:

  • Advanced segmentation capabilities, including Recency, Frequency, Monetary segmentation, predictive segmentation, and cohort analysis.
  • Churn Prediction and Retention identifying at-risk users
  • Customer Journey Mapping identifies bottlenecks or drop-off points.

Best suited to: 

Great for small to medium sized businesses who want to bring together audience analytics, segmentation, multi-channel engagement, product recommendations, and automation into one unified platform. In terms of analytics, there isn’t much in it between the ‘advanced’ and ‘cutting edge’ plans. 

FullStory

“FullStory’s DXI is more than simple in app analytics — it provides the all-important insight into the digital experience. It allows brands to see everything — including all their quantitative and qualitative experience data, captured automatically and retroactively — in one place. FullStory empowers brands to pinpoint customer pains and cure them, while uncovering new insights to build better experiences that boost revenue. Our industry-leading Private by Default approach means brands can have DXI up and running in mere minutes without risking user privacy.” – Andrew Fairbank, VP EMEA, FullStory

Why we like it:

They’re classed as a ‘digital experience platform’ as they recreate user sessions using event based data, therefore combining product analytics with qualitative session insights. This enables you to not only understand what is happening in the app, but also delve into the why. This includes developer-related metrics such as “rage clicks” and “dead clicks”, giving more context to those analysing the data collected.   

Key features:

  • Session replay, so you can watch users interact with your app
  • Searchable User Analytics, allowing you to filter user sessions based on things like user attributes, actions, or errors
  • Some auto-captured events to minimise initial setup time

Best suited to: 

Any business that values understanding user behaviour, optimising the user experience, and improving customer satisfaction. 

Firebase and GA4

Why we like it:

If the app is built on Firebase then it’s super simple to integrate with and combine Firebase with the GA4 property. 

Key features:

  • Export and use data with other Google Marketing Platform products, such as Google Ads or Google Optimise
  • Built on Firebase so doesn’t require an additional (potentially performance slowing) SDK
  • Crash reporting

Best suited to: 

The Firebase SDK is known for its ease of integration, making it accessible for developers. Additionally, it offers scalability and reliability, allowing apps to handle large user bases and peak loads without significant infrastructure management.

Heap

Why we like it:

Heap offers automatic data capture, which means businesses don’t need to manually instrument their code or define tracking events. It automatically captures user interactions and behaviours, allowing companies to gain insights without extensive setup.

Key features:

  • Retroactive analysis, meaning you can define new events or behaviours and apply them to historical data.
  • Visual representation of user flows, highlighting popular paths, drop-off points, and user behaviour patterns.
  • User data redaction, role-based access control, and data retention settings to maintain data privacy and security.

Best suited to: 

Heap’s ease of use and automatic data capture make it accessible to startups and small to mid-sized businesses with limited development resource. 

Mixpanel

”At Mixpanel we prioritise design and usability, which allows data to be easily accessible across an entire organisation without sacrificing a deep level of analysis. Our recent addition of marketing analytics further breaks down barriers and brings marketing and product teams together, combining best in breed product analytics with marketing data to provide a comprehensive view of the user journey.”Ross Walker”, Head of Sales Engineering

Why we like it:

MixPanel specialises in product analytics and the platform has been built with an excellent and intuitive UI, which means any teams can access the platform and its features with minimal effort. 

Key features:

  • Advanced funnel and cohort analysis
  • Flexible and customisable dashboards and reports
  • Multiple integrations and APIs

Best suited to: 

Product-led businesses that focus on in-depth user behaviour analysis, data-driven decision making, and product experience optimisation.

Conclusion

In a competitive marketplace, understanding how your customers use your app is non-negotiable. You can bet your marketing spend that your competitors are analysing user data, so it’s crucial that you do the same.  User data empowers you to make agile decisions, respond quickly to changing user preferences and seize any opportunities for optimisation. 

Faced with any decision and armed with the right tool, you can become: 

  • Quicker, as the tool analyses thousands of data points fast
  • More confident, as you base your verdict on data not intuition
  • Better at selling your idea to the wider business and able to use data to justify your direction
  • Fair, sidestepping any internal bias or motivations
  • Consistent, using the same process to tackle every point of decision
  • More successful, effectively driving impact in your key business goals

As we’ve outlined above, the real question isn’t whether you should use an app analytics tool, but which is the best fit for your business. After that, it’s just a matter of letting the data guide your development decisions, providing you with a roadmap that evolves based on your users’ behaviour.

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Smokehouse Yard, 44-46, St John Street, London, EC1M 4DF 🇬🇧