Work Hours Tracker - Timesheet vs ChatGPT
Revenue, downloads, ratings and category context for two iOS apps. Figures are estimates and should be read as ranges, not exact totals.
Work Hours Tracker - TimesheetKanstantsin Markau - Productivity
ChatGPTOpenAI OpCo, LLC - Productivity| Metric | Work Hours Tracker - Timesheet | ChatGPT | Readout |
|---|---|---|---|
| Estimated revenue / mo | $*** - opens with trial | ~$267M | ChatGPT |
| Revenue band | $*** - opens with trial | $267M (point est.) | Use range + confidence |
| Estimated downloads / mo | $*** - opens with trial | ~19.0M | ChatGPT |
| Download band | $*** - opens with trial | 19.0M (point est.) | Use range + confidence |
| Rating | - | 4.83 | ChatGPT |
| Rating count | - | 8.9M | ChatGPT |
| Tracked keywords | — | 22 | ChatGPT |
| Category | Productivity | Productivity | Same market |
Which app is bigger?
Work Hours Tracker - Timesheet and ChatGPT are compared inside Productivity with monthly revenue, downloads, rating, review volume, keyword footprint, category placement and range context. ChatGPT leads on monthly downloads in the current readout, and ChatGPT wins the revenue readout (the exact figures open with the paid plan), ChatGPT wins demand, ChatGPT has deeper review volume, and ChatGPT has the larger tracked keyword footprint. The better app depends on the job: choose the revenue leader when you need monetization proof, choose the download leader when reach matters, and choose the higher-rated or deeper-reviewed app when market trust is the constraint. Read both ranges rather than only the midpoint, then open the category hub and related collections to see whether this pair is an outlier or a normal category pattern.