The ViralSpoon statistics aren't meant to be the endpoint of analysis, but rather the basis for further content planning. The insights gained can be used directly to target future content more precisely. One option is to regularly check which topics generated particularly strong engagement. For example, once a month you can look at the posts with the most comments and then define the successful topics again as priorities in content planning.
The statistics can likewise be used to compare different content formats with each other. This makes it possible to see, for example, whether carousel posts perform better than single images, or whether text slides generate more engagement than classic photos. AI content creation makes it possible to create different formats, while the performance data provides clues about which of them resonate particularly well with your own audience.
The results can also help with weighting the individual social media channels. If, for example, LinkedIn achieves significantly more impressions than Facebook, it can make sense to shift the content focus more strongly toward LinkedIn. However, this doesn't automatically mean abandoning less successful channels entirely, but rather prioritizing the available resources according to actual performance.
The optimal publication time doesn't need to be analyzed manually on top of that. This task is handled by automatic publishing, which delivers posts at optimized times on the respective channels.
