Recommendation Simulator
How different objective functions produce dramatically different recommendations from the same seed content.
The algorithm decides what you hear next
Most audio platforms optimize for one thing: engagement — keeping you listening as long as possible. This tends to recommend more of the same: the same speaker, the same style, the same narrow slice of content. Rejoice is exploring what happens when you optimize for something different.
This simulator runs three recommendation engines side by side on the same starting content, so you can see exactly how the results diverge:
Engagement Mode (Spotify-style) — Recommends the most similar content, biased toward popular items and the same content type. Tends to create echo chambers.
Discovery Mode (Rejoice's approach) — Actively diversifies across artists, content types, and scripture. Penalizes recommending the same speaker twice. Surfaces content you wouldn't find otherwise.
Theological Depth Mode — Prioritizes content with scripture references, shared biblical connections with the seed, and longer-form material. For users who want to go deeper.
The diversity metrics below each column count how many unique artists, content types, scripture books, and themes appear in the results — a simple way to measure how broad or narrow each approach is.
- Engagement mode typically recommends 10/10 items from the same content type and often a single speaker — a textbook echo chamber
- Discovery mode finds 10x more unique artists and spans multiple content formats from the same seed
- Depth mode surfaces 35+ unique scripture books vs. Engagement's 13, revealing far richer theological connections