Now you know how your reach is compared to the norm, but it’s important to remember that reaching isn’t the only important thing, either. By no means.
It’s about people viewing your posts and taking action instead of scrolling without thinking. It’s easy to assess your own.
On your spreadsheet, examine the Lifetime active users column on your worksheet. This will give you the engagement for each post. Add them all up (hint: use the sum function rather than manually) to determine your total arrangement throughout the month. You can then divide the total number of users reached to calculate your engagement rate click here.
In the report, the average engagement percentage was 3.6 percent of a Page’s reach. So you can evaluate your engagement rates to the average.
What if it’s low? What can you do to get higher engagement rates?
This is the second great thing about spreadsheets: they allow you to determine what’s working and what’s not. For instance, you can organize all the updates on your spreadsheet in order of engagement rates and quickly identify patterns that show what people enjoyed most, least, etc.
Pay attention to things like:
- What kind of update
- Posting time
- The day of the week
- Message phrasing (A question? A statement? Funny? Serious?)
Be cautious even if you don’t see any immediately apparent patterns
Particularly when looking at a brief period, such as just a month. Go back to Your Insights webpage and export the data to a broader range of data, such as several months, and you might notice some things that aren’t evident in a smaller data set.
The kinds of content you publish
The algorithm changes on Facebook are usually influenced by how people interact with the News Feed – which means that the kind of content you share is crucial.
For instance, Facebook found that users prefer sharing URLs by using a link preview instead of embedding them in the captions of images – therefore, previews of links have a more significant impact.
Similarly, Facebook found that people are more likely to enjoy live video broadcasts than recorded ones, which is why live video is the most popular option in News Feed. News Feed.
Facebook does not just search for things it likes when it’s working out the reach of your posts. Instead, it is looking for what it doesn’t like.
Click-bait sites, for example, are a frequent sufferer of algorithmic changes – most likely because they’re made to increase clicks and drive traffic but don’t prove to be very valuable. This strategy worked well in the past; however, users disapproved of it, and Facebook began devaluing these types of links and decreasing their impact.
(One method it used to spot click-bait was by checking engagement levels. However, Facebook also tracks how long you remain on a webpage after clicking through your News Feed. If you’re not staying for the very time, it could mean that the link was clickbait.)
Facebook and users like content that receives engagement naturally.
Because Facebook can detect similarity-bait as a form of like-bait, it could reduce the reach of an update such as the one shown above, and a page that regularly posts this type of content could decrease its distance in time.
However, another type of announcement that “>encourages engagement – for example, by beginning conversations, for instance, is much more effective.
A marketing strategy doesn’t need to include “bait” in the name to cause Facebook to make people dislike it; however, it is read more.
For instance, Facebook has found that users don’t like feeling fooled by headlines – whether fake posts or deliberately false posts, it’s the kind of content that can affect your page’s reach in the long run.
Facebook decides if an article is false through user feedback and reports based on user feedback. Those kinds of essays are just one aspect of a giant puzzle. What users are looking for
The algorithm of Facebook doesn’t just rely on engagement to decide if users are satisfied with the content they’re seeing – since, as we’ve witnessed, such metrics have been easily altered over time.
Instead, by asking for and analyzing user feedback in time, the platform has developed a method of accurately predicting how useful you will find the information in your News Feed without engaging with it.