Combine follower time zones into a weighted activity model to pinpoint when your posts will reach the highest share of awake, scrolling audience members.
Social platforms serve global audiences. Determining when to post so that the majority of your followers are awake and receptive can noticeably improve engagement. This calculator models audience availability by aggregating follower percentages across time zones and simulating each hour of your day.
The algorithm evaluates every hour between 0 and 23. For each follower group with percentage and UTC offset , it converts your local hour to their local hour using
If falls within the typical awake window of 8:00–22:00, that group contributes its weight to the score. The hour with the highest score is recommended. Written compactly, the scoring function is
where is an indicator that returns 1 for hours between 8 and 22 inclusive and 0 otherwise. You can adjust the window by editing the script if your analytics indicate different peak times.
Suppose your analytics show the audience mix below. The calculator recommends a local posting hour that maximizes the share of people currently active.
| Scenario | Top offsets | Share | Suggested post time |
|---|---|---|---|
| Americas & Europe | UTC−5 (50%), UTC+0 (30%), UTC+9 (20%) | 100% | 17:00 local |
| Global launch | UTC−8 (40%), UTC+1 (35%), UTC+10 (25%) | 100% | 09:00 local |
| Asia-heavy community | UTC+5 (45%), UTC+8 (35%), UTC−4 (20%) | 100% | 16:00 local |
Strategic timing is one part of a resilient posting plan. Combine the insights here with analytics dashboards and editorial calendars to confirm whether engagement improves.
The awake window of 8:00–22:00 is a baseline. Some niches prefer late nights or lunch breaks. Track post performance and update the window or follower mix regularly. Seasonal shifts, holidays, and platform algorithm tweaks can all move the optimal hour.
Consider pairing this tool with the social media engagement rate calculator, planning campaigns in the social media content calendar planner, and validating follower growth trajectories via the follower growth calculator.