| name | stelow-product-health |
| description | Product health monitoring through signals in tension. Monitor both effectiveness and user well-being by observing tension between success signals and counterbalance signals, focusing on removing unwanted side effects. |
| metadata | {"frequency":"rare","category":"research","context-cost":"low","author":"calionauta","author-url":"https://github.com/calionauta"} |
| disable-model-invocation | true |
Product Health: Signals in Tension
The Problem of Single Signal Optimization
In a world that pushes for incessant number optimization, it's easy to fall into the trap of pursuing signals in isolation — focusing on what grows fastest or looks most impressive (like number of new users or frequency of use).
This practice carries silent risks: the "cobra effect" — when trying to solve a problem with one signal, we end up generating unexpected negative consequences in other areas. Optimizing a single signal can lead to a product that "works", but generates unwanted human costs: addiction, anxiety, loss of time, or superficial use that doesn't deliver real value.
The Proposal: Sets of Signals in Tension
Instead of seeking the absolute signal, monitor the "pulse of the system" through sets of signals in tension. The intention is to monitor both the effectiveness of the solution and the user's well-being, focusing on removing unwanted side effects instead of just adding more growth numbers.
For each set, there is a success signal and one or more counterbalance signals. By observing the tension between them, you get a more comprehensive and balanced view.
The 3 Essential Sets of Signals
1. Tension: Speed vs. Quality of Activation
Success Signal — Did the User Experience Initial Value?
What to observe: identify the most important action a new user needs to take to experience core value for the first time. Think of the "aha! moment" — the instant when the person perceives the purpose of the solution.
Intuitive Examples:
- Task organization app: "a new user who creates and completes their first task in the first 3 days"
- Meal delivery service: "a new customer who places and receives their first order in the first week"
Justification: this action represents the first delivery of real value — the point at which the user experiences the central purpose of the solution.
Counterbalance Signal — Was Activation Superficial?
What to observe: look for a signal that reveals whether activation was an isolated event, without continuity. Helps avoid the team forcing the user to an action that doesn't translate into real engagement.
Intuitive Examples:
- Task app: "the percentage of users who created and completed the first task, but did not return to the app in the next 7 days"
- Delivery service: "the percentage of customers who placed the first order, but did not place a second order in the following month"
Justification: protects against "gamifying" activation — where the user is led to a one-time action without genuine engagement.
2. Triple Tension: Habit vs. Progress vs. Well-Being
This set is the heart of monitoring a healthy system, seeking balance between continuous use, real user progress, and ensuring that the product doesn't generate hidden costs.
Success Signal — Is the Product Becoming a Habit?
What to observe: identify a key action that, when repeated, shows that the solution has integrated into the user's routine. A frequency that indicates consistent and intentional use.
Intuitive Examples:
- Language learning platform: "the percentage of users who complete one lesson per day for 3 consecutive weeks"
- Financial management tool: "the percentage of users who record their expenses weekly for one month"
Efficacy Counterbalance — Is the Habit Not Generating Progress?
What to observe: look for a signal that shows whether continuous use is, in fact, leading the user to progress in their main purpose. We want to avoid "treadmill habit" — there's activity, but no progress.
Intuitive Examples:
- Language learning platform: "the percentage of users who complete lessons regularly, but don't advance levels or don't improve on proficiency tests"
- Financial tool: "the percentage of users who record expenses, but don't decrease their spending or don't reach their savings goals"
Well-Being Counterbalance — Is the Habit, Even if Effective, Harmful?
What to observe: identify a signal that monitors the "human cost" of use. Ensures that the product doesn't become extractive or addictive, generating anxiety, loss of time, or other negative impacts.
Intuitive Examples:
- Language learning platform: "responses to a survey about the level of stress or frustration with learning" or "the percentage of use sessions that exceed X hours per day, indicating potentially compulsive use"
- Financial tool: "responses to a survey about perception of financial control versus anxiety" or "the number of times the user accesses the application outside business hours, indicating excessive worry"
Justification: ensures that the habit is healthy. Protects against creating an "extractive" or addictive product that solves a problem but generates anxiety, loss of time, or other hidden costs.
3. Tension: Depth for the Faithful vs. Accessibility for Newcomers
As a product evolves, optimization for more experienced users can, unintentionally, make life difficult for those who are arriving. This set seeks the balance between these two needs.
Satisfaction Signal — Are We Essential to Our Base?
What to observe: for users who have been engaged for longer, what signal shows how indispensable the product has become to them?
Intuitive Examples:
- Video editing software: "the percentage of users with more than 6 months of use who would answer 'very disappointed' if the software ceased to exist"
- Online community: "the frequency of contributions from veteran users in complex discussions"
Counterbalance Signal — By Pleasing the Base, Are We Worsening the Experience for Those Arriving?
What to observe: monitor the experience of new users, ensuring that the evolution of the product for the "faithful" doesn't create barriers for "newcomers".
Intuitive Examples:
- Video editing software: "the completion rate of the initial tutorial by new users" or "the satisfaction level (CSAT) of users with less than 30 days of use"
- Online community: "the rate of new members who make their first post or comment in their first week"
