From Adoption to Commitment: How Connected Products Build Lasting User Relationships

In the connected-solutions space, well-marketed solutions often ignite like wildfire, with adoption rates skyrocketing. 

A more meaningful metric, however, is how many of those users remain active after one month, six months, or a year. Retention rates frequently decline over time as initial excitement fades and the product is quietly abandoned.

Yet there is a science behind sustaining engagement over the long term. Products that endure success follow recognizable patterns: they design a user journey in which relevant experiences are unlocked in a deliberate sequence over time. Users are given just enough value to remain engaged, while respecting their learning curve and avoiding cognitive overload.

This user journey can be summarized in broad terms as following:

1 — Self-awareness phase: A new snapshot of oneself At the outset, users are introduced to an exciting new experience, with access to novel data sets and the ability to monitor aspects of their health and performance that are relevant to their lifestyle. 

Data is presented both in real time, often represented with scores and indexes to be easily interpreted, and also logged over extended periods. Users can observe physiological and behavioral signals and are presented with trends representing how their data has evolved over time.

This initial experience is often reinforced through social sharing, community building, and gamified elements such as streaks and leaderboards, which add extrinsic motivation and help prolong this phase.

2 — Motivational phase: Short-term actionability and control

After the initial period, as novelty begins to fade, users are introduced to actionable information and insights. Current and historical data are transformed into near-term predictions that can influence users’ behavior, enhancing their sense of control over their lifestyle and their ability to plan short-term interventions to improve health and performance.

Users remain engaged with the product when they perceive it as supporting their decision-making and reinforcing the feeling that their actions meaningfully influence their life.

However, insights are not always easily actionable, which can lead to frustration. There is a fine line between providing helpful guidance and becoming an annoyance—bed-time recommendations that are impractical or unrealistic are a common example.

When well designed, actionable insights are amplified through proactive and timely notifications, increasing engagement and reinforcing the perceived relevance of the solution.

3 — Engagement phase: The path to personal goals

This phase begins as the users develop habits and build trust in the solution, seeing it as a reliable everyday companion that positively supports and shapes their life. At this stage, users move beyond basic awareness and motivation and seek guidance to actively refine and optimize their behaviors and routines.

It is now time to evolve short-term engagement into a long-term commitment between the user and the solution. Users are prompted to select meaningful long-term goals, often with proactive guidance derived from insights into their interactions with the product. Once these goals are set, the solution should provide a clear, personalized path to achieve them—typically through a scheduled program that delivers daily tasks and customized guidance. 

The experience becomes highly tailored, often incorporating adaptive challenges that promote mastery and self-discipline. Users develop a stronger personal identity around their progress, viewing the product as an essential tool for continuous growth and self improvement. 

In this phase, solutions may become aggregators of third-party programs, leveraging the credibility of experts while maintaining their core value in data collection and analytics. This creates a win-win situation: data enables experts to develop effective programs, and experts help sustain the long-term value of the solution.

Data interpretation and adaptive programs can be enhanced with AI; however, successful solutions are built on trust and credibility and still require human interaction.

Phase	What Happens	Key Features	User Focus
1 — Self-awareness	Users discover new data about themselves and their health.	Real-time feedback, trend monitoring, social sharing, gamification (streaks, leaderboards)	Curiosity, excitement, initial motivation
2 — Motivation	Actionable insights guide users to take short-term control.	Personalized insights, near-term predictions, proactive notifications	Empowerment, self control, decision-making, short-term action
3 — Engagement	Users build trust and commit to long-term goals and routines.	Long-term goal setting, personalized programs, daily tasks, adaptive challenges, expert program integration	Habit formation, mastery, continuous growth