October 7, 2011
Despite the name, less than 2% of Daily Active Users for your Facebook Page actually engage with your content [Tweet This]
Without a doubt, the most confusing number in the current default version of Facebook Insights is a metric called “Active Users”.
Basically, an active user is counted anytime someone visits your fan page or views a story about your fan page. If a user views content without engaging, they’re still counted as an Active User. If someone generates both a pageview and a story impression, they will only count as one active user.
If a user tags the fan page in a status update, than all the user’s friends who saw that status update are counted as active users, even though all they saw was the name of your fan page in their friend’s status update. Based on my testing, only logged-in Facebook users appear to be counted. Pageviews from logged-out visitors are omitted.
Because this is so confusing, I’m really excited that in the upcoming version of Facebook Insights, they’ve reworked this metric into “Who You Reached.”
We benchmarked 1,000 fan pages to see what their Daily Active Users were doing:
Just in case the table isn’t clear:
For every 1000 daily active users a page has, you can expect that on average 816 of those active users will have viewed a status update, 286 of those active users will have visited the fan page, 13 will have liked a status update, 5 will have commented on a status update, and 3 will have left a wall post.
If you prefer median values instead of mathematical averages, you can expect 979 of those active users will have viewed a status update, 74 of those active users will have visited the fan page, 7 will have liked a status update, 2 will have commented on a status update, and 0 will have left a wall post.
This study had more than 100,000 data points across 1,000+ pages that each had 10,000+ fans, so it should be fairly accurate.
These benchmarks do assume that a user took a maximum of one action per-category, per-day. This is not always true for post likes, post comments, and wall posts.
The averages were calculated by generating a per-page-average each activity for each of the 1,000+ fan pages in the dataset. Then I averaged all the per-page-averages together to get a sample-average for the activity. I suspect several smaller, fast-growing fan pages skewed the average because their rates of growth would be so high relative to their number of active users. Spikes in fan growth are closely correlated with spikes in pageviews.
I also sorted all the per-page-averages from least to most, and then found the middle value to get the median value.