Longitudinal research in UX

Torresburriel Estudio
4 min readJan 16, 2025

--

One thing is clear, and that is that most of an app’s chances of success come from the work that is done afterwards, once it has been taken into production.

The iteration of processes can help us to more effectively get right where there is the most friction with users, and how to mitigate it. But this is not information that can be hypothesised: as UX teaches us, observation and direct user research is what helps us to verify these steps.

Photo by Matt Howard on Unsplash

Longitudinal UX research is not the kind of study that generates quick or immediate results. It is a way of analysing user interaction with a product over an extended period of time, often months or even years.

The goal is to gain deep insight into how their experience evolves, how they use the product, and how their behaviours and needs change over time. Unlike usability testing or single-session studies, longitudinal studies allow for the identification of patterns and variations that may not be evident in short-term interactions.

When is longitudinal research useful in UX?

This type of research is particularly useful in contexts where changes in user behavior are critical to a product’s success. For example:

  • Subscription apps: Success depends on keeping users engaged and ensuring continued payments over time.
  • Management systems: Users need to adapt to new features or workflows, and usage typically spans several months.
  • Health products: Apps for fitness or meditation track user progress over time, focusing on habits and routines.

Longitudinal studies are also valuable for identifying how user needs evolve at different stages, such as onboarding, regular use, and adapting to updates or new features.

How to structure longitudinal UX Research

Conducting longitudinal research requires careful planning to gather useful and actionable data. Here is a basic framework to follow:

1. Define the objective

Start with a clear understanding of what you aim to learn. Are you looking to track behavioral changes over time? Monitor the adoption of new features? Measure shifts in user perception?

For example, in an educational platform, you might study how students use the tool over an entire semester — tracking usage peaks during exams or drops in motivation after holidays.

2. Select participants

Participants must be carefully chosen to represent the target audience. Additionally, they need to commit to participating throughout the entire study.

Since long-term tracking can be costly, studies often use small, highly segmented groups. Cohorts of participants grouped by behavior or characteristics are also common.

3. Establish checkpoints

Tracking occurs through checkpoints, which are specific times when data is collected — weekly or monthly, depending on the study’s duration and nature.

For example, in a wellness app, users could complete a monthly survey over six months about usage, satisfaction, and any changes in habits or goals.

4. Choose data collection methods

A combination of methods provides a more comprehensive picture in longitudinal research. Common techniques include:

  • Periodic surveys: Quantitative data on satisfaction, preferences, and usage.
  • Follow-up interviews: Qualitative insights into evolving user experiences.
  • User diaries: Logs of thoughts and experiences in digital or physical formats.
  • Usage data analysis: Tracks actual user behavior, such as clicks and activity metrics, to observe patterns over time.

5. Analyze data

Analysis in longitudinal research is not something that should be left to the end of the study. In fact, it is advisable to conduct partial analyses throughout the process, as this allows for adjustments to be made and to ensure that the data collected are relevant.

At the end of the study, you can look for patterns of change. For example, do users show more frustration as they become more familiar with the product, how does frequency of use evolve over time, and what design elements seem to influence user retention?

6. Report findings

Once the data have been analysed, it is time to report the findings. It is essential that the results are well organised and clear. The structure of the report can follow an outline such as:

  • Executive summary: Key insights and conclusions.
  • Data analysis: Highlighting patterns and trends.
  • Recommendations: Design decisions based on the data.

Example of longitudinal UX Research

The Headspace meditation app conducted a six-month longitudinal study to analyze user behavior. The goal was to understand why many users abandoned the app after just a few weeks, despite positive initial experiences.

Source: Headspace

The study began with a satisfaction survey and in-depth interviews to uncover user motivations. Monthly surveys and interviews followed, focusing on experiences, motivations, and barriers.

Findings revealed that while users were initially motivated by mindfulness benefits, many dropped off when they didn’t see quick results or struggled to integrate sessions into their routines.

In response, the team improved onboarding to set better expectations about progress and added personalized notifications to help users build consistent habits.

Now that you understand longitudinal research in UX, it’s the perfect time to integrate it into your design process — creating products that work today and evolve alongside your users’ needs.

--

--

Torresburriel Estudio
Torresburriel Estudio

Written by Torresburriel Estudio

User Experience & User Research agency focused on services and digital products. Proud member of @UXalliance

No responses yet