Timing is incredibly important for organic reach and for the overall success of the content you’re posting to Facebook. Here’s what we know about how the two connect in the News Feed, and how predictive analytics can help.
If you manage a social media profile, you’ve probably wrestled with figuring out exactly when to post the content you worked so hard to create. If so, you’ve done it for a good reason: timing is critical in social media marketing, whether you’re posting to chronological-feed platforms or algorithmic ones. To get the best social marketing results possible, optimizing your organic reach is a must.
There’s a lot of advice out there on when the right time to post is for different platforms. There’s loads of data to point you one way or the other: average user activity, peak interaction times based on location, average activity for different days of the week.
Wading through all of that information can be confusing and an inefficient use of time. We’ve simplified it all by compiling the three most important factors you need to take into consideration when determining the most effective time to post.
Control for Quality
A lot of the information you will gather will be based on historical data. While it is useful to monitor how your posts have engaged your audiences in the past, there is an obvious limitation to this – how much of a post’s performance can you attribute to timing, and how much of it is just because of the quality of that content? Look for overall trends in engagement, but make sure to check that a particularly engaging post isn’t skewing the numbers.
Check For Opportunities Not Taken
It doesn’t help that charts chronicling your engagement at different times of day and days of the week are skewed by when you’ve posted in the past. If you’ve never posted at 8 am, you’ll never see engagement at that hour, and will never know that it could be exactly when you need to post. Here, the Facebook Insights chart “When Your Fans are Online” could be of help.
This is a sample graph from Facebook Insights showing you when users are online for this particular sample page.
But just because people are online doesn’t mean they’ll engage with your content – so watch this in tandem with engagement throughout the day to get a clearer picture – after all, your audience’s behavior isn’t totally unified, and there will be variation in how people interact with your content.
Each Page’s Engagement Trends Are Unique
Consumer behavior online on social media differs by your audience’s profile. Each Page’s community will be unique in their content consumption, so you always need to look for trends within your own communities to see when they most readily engage with your content.
While it might be possible to maximize visibility for a page through trial and error, it’s a costly and timely exercise that needs to be repeated often because audience behavior changes over time. Doing it without data is difficult.
To give marketers an advanced yet easy-to-use solution for Facebook, we created PrimeTime – a machine learning algorithm that analyzes how Fans of your Page engage with content in the News Feed, and uses that to suggest the optimal posting time for every new piece of content for each Page.
The PrimeTime algorithm is integrated into our publishing solution and recommends when you should schedule posts based on predicted uplifts in visibility. This means that you can create better organic reach without leaving your content creation process thanks to PrimeTime’s machine learning.
It’s much more than a back-end audience activity chart analyzer.
To optimize your post’s visibility with PrimeTime, all you need to do is use the suggestion when you schedule your content. This allows you to increase the exposure of your posts for every Page, each time you post, without having to spend hours poring over incomplete data.
We believe the future of social media marketing is in leveraging big data to create simple, easy-to-follow insights. It’s what we’re doing today to make your social marketing easier, more visible, and more cost-effective.