Fair · Transparent · Interpretable

Scoring Methodology

Indie Pledge is dedicated to building a transparent recommendation ecosystem. We are publishing our core scoring logic and principles here.

Activity Board

Answers: "Is this product being actively maintained?"

Primarily based on effective update frequency in the last 90 days, combined with staleness penalties.

Treasure Board

Answers: "What is the real user experience like?"

Primarily based on blended rating quality and bug report rates.

Activity Board Details

Core Baseline: Effective Updates

The base score is entirely based on effective updates in the last 90 days. We apply a layer of filtering:

  • Only 1 effective update per day is counted.
  • Pure marketing announcements are excluded.
  • Duplicate updates are normalized and removed.

Staleness Penalty

The longer the time since the last effective update, the higher the penalty. Long-term inactivity can result in negative scores.

E.g., Over 6 months of inactivity triggers a severe penalty.

Engagement Bonus

Claimed products that continuously maintain their roadmaps and publish social content receive a minor bonus.

Note: Bonuses have a hard cap. Perfect scores require hardcore update frequencies.

Tie-Breaker Mechanism

When multiple products have the same activity score, we tie-break sequentially by:

  1. Effective updates in the last 90 days
  2. Days since the most recent effective update

Treasure Board Details

Rating Quality & Smoothing

To prevent a tiny number of reviews from pushing a product to the top, we use Bayesian smoothing and multi-source blending:

Low Sample ScoringEven with few reviews, we calculate a score, but apply deductions based on global averages. Very low samples do not rank in Top 10.
Multi-Source BlendingWe blend App Store ratings with internal user reviews. Significant discrepancies result in extra deductions.

Bug Report Rate Penalties

Real user feedback on crashes and errors is a crucial indicator. Reputation = Rating Quality + Bug Health.

  • High bug rates reduce the score, while active responses provide minor trust restorations.
  • If a highly-rated product has a significant bug rate, its reputation score is capped.

Why Scores Change

Rolling 90-Day Window

A recent update does not prevent an older one from rolling out of the 90-day window, which may lower the base score.

New Activity Not Counted

Marketing-heavy, duplicate, or same-day repeated posts may not be counted as effective updates.

Bonus Signals Shifted

Roadmap maintenance, social content, and claim status provide bonuses. If these signals weaken or expire, the score will adjust.

We Want More Than Up or Down

We are continuously improving score explainability. Timeline descriptions aim to clarify whether a change was due to rolling windows, staleness penalties, or filtered updates.

How to Read the UI

Activity Example

Activity Score: 68
Today: -6 | Rolling 90-day window
Effective updates in 90 days: 11
Latest activity: 2 days ago
Latest effective update: 2 days ago

This helps distinguish between recent product activity and whether the system treated it as an effective update.

Reputation Example

No Reputation Yet
Not enough rating data yet, so it is not ranked.
Pending Rating
The sample size is still small, so it stays out of the formal ranking for now.
Formal Reputation Score
Once rating samples and bug signals are sufficient, the system shows a more stable reputation score.

Values Behind the Boards

Activity Is Not Marketing

We reward verifiable iteration and continuous maintenance, not bursty marketing activity.

Reputation Is Not Praise Inflation

We use sample thresholds, smoothing, and bug signals to avoid inflated scores from a small number of positive reviews.

Whether early-stage iterating rapidly or mature in a stable phase, you can shine in your respective dimension.