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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 Algorithms1 video lessonRead-along guideFree 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 metricswin 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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