Scheduling your Tweets is an art form. First, you have to pick the piece of content, then craft the copy, the CTA, build the link, and finally send it off.
In the past, I’ve spent a lot of time focusing on the intricacies of that last step. I ran tests and even wrote a blog post about how to find your top time to Tweet. For me, knowing when your audience is online and ready to engage is essentially like having the keys to the kingdom.
Recently, I heard something about the topic that caught my attention:
A colleague achieved higher engagement by timing Tweets to coincide with the flow of an every day business meeting.
They were seeing spikes in engagement towards the end of typical meeting times. Attention begins to wane… minds begin to wander… fingers begin to browse. Did that just blow your mind? Well, it blew mine so I did what any analytical community manager would do – I dug into my own data.
I wanted to see how engagement varied minute-to-minute. For example, is engagement at 9:20 a.m. different than engagement at 9:45 a.m.? I run a pretty tight ship in terms of my Tweet scheduling. I usually run on the standard 15 minute increments; 2:00, 3:15, 5:30, 6:45, etc. It was crucial for me to control for this, so I added the secondary axis which charts how many Tweets have been sent at that minute marker. This is something that any marketer can do in Excel by inputting their own Twitter data.
- There are extreme peaks in engagement on the 15-minute intervals (my Tweeting schedule).
- After excluding those scheduled Tweets, you’re able to see some interesting points to back up my colleague’s theory. On the 28th and 56th minute, there are significant engagement peaks. If you entered a meeting at the beginning of an hour or half-hour, those would be prime times for your meeting to wind down and your attention to wander.
This data certainly is not conclusive, but it is something to think about. You want to be online when your audience is online, and give them content when they’re more likely to read it. Since our audience is digital marketers, we know they’re online frequently during the day. But how do we drill down even further? Data is nothing without context, and that context can only come from understanding your audience.
When is yours online?