How we measured this

Two things, kept separate, both from our own data:

• When posts perform. For 2.6 million posts, we compared each post's likes to that same author's usual likes. That controls for follower count: a 500-like post from someone who normally gets 2,000 is a weak post, and we treat it that way. We turn that into a score from 0 to 100 for every day-and-hour slot, separately for each country.

• The best day for reach. Separately, for 10,798 creators (831,350 posts), we looked at real impressions and found which weekday gave each creator their widest reach, then counted the winners.

A few honest notes, because timing data is easy to fake:

• Hours are local. When we say "8am in the US," we mean US Eastern. For France it is Paris time, for India it is IST. We say the time zone every time.

• Scores compare within a country, not across. A 100 in Germany and a 100 in the US are both "the best slot in that country." They do not mean Germany beats the US. Never compare the scores between countries.

• This is correlation, not a promise. These are the slots where good posts happened to land. Posting at 8am does not magically earn reach. It tips the odds, it does not rewrite them.

• We do not have reliable data by industry, job title, or B2B versus B2C, so we will not invent it. Anyone who gives you a precise "best time for B2B SaaS recruiters" is guessing.