Predicting Facebook Post Popularity
The role that social citations play in the search marketing landscape is increasing dramatically. And don't think for a moment that smart software solution developers are not fully aware of that fact.
Adobe, for example, recently announced new predictive capabilities for its social media optimization platform Adobe Social (part of the Adobe Digital Marketing Suite).
What makes the development so interesting is that Adobe uses historical data — in aggregate and at the customer-specific level — to predict engagement levels (as well as sentiment) around a specific type of Facebook post. The platform can recommend keywords, content types and even timing that could lead to a better response (deeper engagement et al).
Adobe Social users can see the estimated range for the amount of Likes, comments, and shares a post will receive, as well as identify other metrics that matter to them (which Adobe will then track and predict in the future). Before posts are published, the service will notify users if post elements exist that could be improved — for example, perhaps there is a better time to schedule a post.
Rumor has it that Adobe will quickly expand beyond Facebook (and that's good news as, apparently, Google+ is gaining ground on Facebook which is (also apparently) losing millions of users.