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How ranking thinks about your room

Visibility is not “online = sorted high”—the system blends economic activity with viewer satisfaction signals so busy, trusted rooms float and rough experiences sink.

Platform Strategy · Ranking Algorithms 1 video lesson Read-along guide Free for models
Part 1

Tokens per hour, ratings, and private-show trust

The lesson frames ranking as a weighted score—money velocity first, then reputation when two rooms look similar on earnings.

Lesson video: Ranking—velocity, ratings, and how they stack.

Algorithm = weighted scorecard. The site blends live behaviors into a placement score; showing up is necessary but not sufficient. Think in signals, not superstition.

Tokens per hour

Earning velocity is framed as the dominant input: steady tips, goals, and spend in a window read as active, retentive rooms—so the system has reason to surface you more often.

Public ratings as trust

Stars are not a full substitute for income, but they act as a confidence layer: when two rooms look similar on money, better satisfaction metrics win the tie. Strong ratings also support profile click-through, which feeds more entries and more chances to convert.

Private ratings weigh heavier

Because privates are higher-stakes spend, private feedback can steer recommendations to big spenders and amplify positive loops—happy whales return, which props up the same tokens-per-hour core the ranking system cares about.

Use the model, do not rage at it

Schedule for your peaks, structure shows that retain and convert, protect experience quality, and treat ratings as part of the business—not a personal insult when they dip.

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