Iuliia Chistiakova UX Researcher

    Customer Analytics Software for Best UX

    Customer analytics software is a key component in data-driven decision making. A recent Gartner survey underscored this, with 84% of participating leaders deeming it crucial for achieving their 2023 goals.

    These tools help us make smarter product choices, create better user experiences, and amplify ROI. However, if you’ve ever tried integrating multiple tools, you’ve probably faced frustration with technical complexity, data silos and scattered information.

    At Surf, our data-driven design approach has been refined over 12+ years, utilizing top-tier tools and technologies across various business sectors and project scales.

    In this article, we’re excited to share our insights on:

    • What are main examples of popular analytics software? 
    • What are the challenges faced when integrating it?

    Let’s jump right in.

    We love data. It helps us create products that people want to use — and drive business growth.

    Learn about our culture

    Examples of customer analytics software

    Google Analytics might be the first thing that pops into your head when thinking about customer analytics software. Yet, there are many specialized tools tailored for product and UX analytics, too. 

    Here are 4 that the team at Surf frequently uses:

    1. Amplitude Mobile Analytics

    Amplitude focuses on event-driven insights for mobile apps. What makes this platform powerful is the ability to turn large amounts of data into charts, and its user-friendly interface. Together, these features make it a powerful platform for visualizing user behavior in the product.

    How we use it

    At Surf, we use it to find insights into user behavior and understand how customers interact with the product. This helps us to pin-point areas for improvement and prioritize what to work on next.

    For instance, when a client approached us to develop a video streaming app, we used Amplitude along with two other tools.

    Amplitude Mobile Analytics helped us to map user behavior within the app. Its intuitive interface simplified the learning curve for the client’s team, while its powerful visualization options, even with enormous data sets, facilitated a deeper understanding of viewing habits.

    The outcome? Our collaborative design effort with the client was so fruitful that numerous users opted to watch videos on our app instead of YouTube.

    2. Firebase Analytics

    Firebase Analytics is the main analytical tool in the Firebase suite. It automatically collects data on how people use your app, and allows you to define your own events to track.

    You can then view this data in the Firebase console, or export it to BigQuery for more detailed analysis. Similarly to Amplitude, Firebase Analytics is particularly strong when it comes to tracking in-app events and learning more about users activity within the app.

    How we use it

    At Surf, we often use this software together with Firebase A/B Testing to find winning UI solutions, engagement strategies, and element placements.

    For example, in another  project we carried out for a top regional pet shop chain, we integrated the app with three systems: Firebase, Google Analytics, and App Metrica.

    Being proponents of the lean methodology, we were aware of the need for continual design iteration. Therefore, an accurate tracking method for A/B test results was necessary. That’s where Firebase Analytics helped us.

    Together with other tools it also helped the client to keep an eye out for any unusual activity in the app. For instance, if a large number of users suddenly uninstalled the app or if there was an unexpected inflow from countries where the company doesn’t operate.

    3. AppMetrica

    AppMetrica is another solution that has gained a world-wide following thanks to its real-time data updates, deep linking, GDPR-readiness.

    But what sets it apart for us is Attribution Tracking: We use this feature to determine where users come from, which can help optimize marketing efforts. We often rely on this data to deliver geo-specific promotions and identify regions where certain marketing campaigns overperform.

    How we use it

    AppMetrica helps us understand where users came from — be it performance marketing, SEO, or a link in the YouTube video description.

    4. Google Analytics 

    This software is the backbone of web analytics for countless projects. It helps marketers learn who their users are, where they come from and how they interact with website content.

    Google Analytics also integrates with other Google products like Google Ads to deliver accurate ROI information and customer flows.

    How we use it

    At Surf, we use Google Analytics for website optimization and marketing campaign management. It gives us insight into attribution funnels, performance of different campaigns across channels and regions, and marketing ROI.

    Lean how we apply data-centric approach to deliver high-performing apps

    Browse case studies

    Specialized tools to consider

    Other apps that marketing and product teams often use include Mixpanel, an event-focused tool which is similar to Amplitude, and Kissmetrics, an analytics suite that connects events to individual users.

    All the apps we’ve mentioned give a wide view of user behavior. Each one has its strong points and weak spots, and in most cases, they can be used in place of one another.

    But there will be times when you need specific data, and that’s when you should consider using more specialized tools.

    • Crazy Egg. This tool focuses on session recordings and heatmaps to find and optimize dead zones on your websites.
    • Looker. Developed by Google, Looker is a cloud application that lets you visualize custom datasets by integrating with over 50 databases. It’s a powerful solution for enterprises that work with massive datasets.

    How to eliminate data dead-zones with a holistic approach to analytics

    To acquire the complete and accurate information when it’s needed necessitates a comprehensive approach. Often, this means adopting multiple platforms. Collectively, your analytical toolkit should cover:

    • Attribution
    • App usage
    • Financial metrics

    Take Google Analytics for instance. It’s a fantastic tool for your marketing team to assess ad performance and fine-tune marketing campaigns. However, it won’t offer much insight to your UX team about app usage — simply because that’s not its primary purpose.

    At Surf, we often use a combination of web and event-based product tools. This approach helps us understand the user journey from the first interaction with the brand until purchase.

    A holistic suite of analytics tools can look like this:

    • Google Analytics: to measure website and marketing performance
    • Amplitude: to understand how users interact with the app
    • Firebase Analytics: to measure results of A/B tests

    Analytics software integration challenges

    While utilizing multiple analytics solutions can bridge data gaps, it does come with its own set of challenges due to the increased complexity.

    • Inaccurate attribution. Mobile apps operate in a complex ecosystem with multiple platforms (like iOS and Android), app stores, and advertising networks. Tracking how users found your app can be difficult because each of these elements may use different identifiers. And if you can’t accurately track where your users are coming from, it’s harder to understand which of your marketing efforts are most effective. Using a tool that specializes in Mobile attribution, like AppMetrica, can help to rectify this issue.
    • Data сonsistency issues. When multiple analytics tools are in play, there is a high risk of receiving inconsistent data across platforms. This could lead to confusion and hamper accurate, data-driven decision making. To combat this, it’s crucial to standardize the metrics and events you track as much as possible across platforms.
    • Integration complexity. Each platform has its unique API and integration methods. This can complicate the integration process, increasing the project cost and development time. That’s why it’s vital to collaborate with an experienced development partner who understands how to integrate these tools.
    • Skill gap. Every analytics tool comes with its learning curve, and finding or training staff to effectively use each tool can pose a challenge. This could potentially slow down the process and lead to under-utilization of the tools.

    At Surf, our product experts know how to integrate, set up, and use the relevant tools effectively and seamlessly integrate a comprehensive analytics suite into your existing technologies and business processes.