The tricky thing I’ve come across is that since the web is still so new, a lot of the research available to us is conflicting. We really need more time and more studies to get definitive answers about what works best, and the fact that our audience members are constantly changing their own activity patterns makes it even harder to work out for sure. Looking at the latest social media stats seems to only confirm that.
So my suggestion would be to use this guide as just that—a guide to help you work out what to test for your own audience, so that you can see what actually works best in your specific case.
Dan Zarrella has some more great stats on this topic, but he makes a good point about the pros and cons of the timing you choose. One thing Dan suggests we consider is that if we post during time of higher traffic, we’re more likely to have higher bounce rates and get lost amongst the noise of other content being published.
On the other hand, posting at times when fewer people are online will garner less traffic and engagement, but give our posts more prominence and less competition against other content.
- 70% of users say they read blogs in the morning
- More men read blogs at night than women
- Mondays are the highest traffic days for an average blog
- 11am is usually the highest traffic hour for an average blog
- Comments are usually highest on Saturdays and around 9am on most days
- Blogs that post more than once per day have a higher chance of inbound links and more unique views
Timing depends on the individual
Timing is difficult to get exactly right, and a big part of this is because we all have different schedules and routines for checking email or using social media. An experiment by online retailer eBags showed this point perfectly. Looking at the latest social media statistics the range of different schedules seems to only increase too.
The company thought that when users were signing up to an email list, that was probably a good time of day for them to be online, so sending emails to them at that same time of day would work best. By analyzing the behavior of each individual user, eBags sent out emails to users at the same time of day they had signed up for the email list.