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Analytics Made Easy - StatCounter

By Jonathan Lee, Product Manager at Liferay

Product analytics is a collection of tools and processes that enables your team to track user behaviour on your website or applications. It consolidates the data into a single location, allowing you to visualise data holistically. Product analytics provide key metrics about your product, enabling you to enhance features, identify issues, and correlate user behaviour with long-term success.

How is this different from conventional analytics?

Most analytics tools measure SEO or page views performance, which is great for marketing endeavours. However, product analytics captures more in depth interactions of the user throughout the entire flow of your applications.

Why is this important?

Product managers, UX designers and engineers frequently engage in lengthy discussions about whether to add a new feature, eliminate an existing feature, or redesign a UX in some way. In reality, nobody in the room is the end user.  Why not use data, and real time metrics to assist in making smarter and more accurate decisions.

When used properly, analytics can be extremely beneficial in a variety of areas in the development team. Developers can use the data to optimise features, eliminate bugs, and potentially resolve user issues early on. UX designers can use product analytics to see how users navigate the features, which ones are confusing, which ones are  popular and which features are abandoned. Additionally, product managers can also make product decisions based on metrics, resulting in the delivery of features that the user truly desires.  And finally, customer support can use the data to forecast the volume of tickets that may be generated by specific areas of the application.

How do we do it?

Follow these important steps:

1. Planning

Planning occurs while a business is still in the process of developing a feature and product. At this point, a goal for how the product should be perceived by the users should be established. Additionally, this is the point at which the signals that can be used to track users and measure these objectives should be considered.

The heart framework helps evaluate various aspects of a product using five metrics:

  • Happiness: the degree to which users are satisfied with the product. Customer satisfaction is typically quantified through surveys, app reviews, app rates, or net promoter scores (NPS)

  • Engagement: the degree and frequency at which users interact with a product. For instance, how frequently do users log in? How frequently do they search and how frequently do they click on search results

  • Adoption: the number of customers who have begun to use the product or one of its features

  • Retention: the percentage of users who return to the product following their initial use. For subscriptions, this will be measured by the number of people renewing subscriptions.

  • Tasks: are users able to complete tasks easily and efficiently

To plan using the heart framework, goals, signals and metrics must be identified.

2. Implement

Here, you want to track user interactions and store it in a convenient location for later analysis. This is referred to as event tracking. Utilising codes enables the tracking of more complex interactions and provides greater flexibility than a no-code option (for the less technical person).

3. Analyse

Analysis can determine who has accessed features and how frequently.  Each step can have its own event triggered when the user completes, as well as a final event triggered when the user checks out. A funnel chart can be used to visualise data, as it can show the drop point for each step, assisting in determining which steps are causing problems.

Integrating product analytics into the development process is critical and should be completed prior to launching a product. Collecting data as soon as possible enables user feedback to aid in making more informed decisions.