Adobe is announcing new predictive capabilities for Adobe Social — capabilities that should be particularly helpful to marketers wondering why some social media posts take off while others fall flat.
Bill Ingram, vice president for Adobe Analytics and Adobe Social, walked me through the new features earlier today in advance of the Adobe Summit in London. Adobe is using historical data — both in aggregate and at the customer-specific level — to predict the likely engagement level and sentiment around a specific Facebook post, and it can recommend keywords, content types and timing that might lead to a better response.
The predictions integrate directly into Adobe’s social publishing tools. Customers can open a widget showing the estimated range for the amount of Likes, comments, and shares a post will receive. They can also identify other metrics that matter to them, and Adobe will track and predict those as well. And before publishing, the service will notify them if there are things that could be improved — for example if it would be better to schedule a post for later, because the customer’s account posted similar content a few minutes prior.
To provide these kinds of recommendations, Ingram said that Adobe is analyzing the content of the posts, for example looking at keywords and content types (i.e. images vs. video). He also said that while there are other products that provide general content suggestions for social media updates, Adobe has access to unique user data, and that the product is “tuned to get smarter as data flows into the system.”
Adobe plans to release the predictive capabilities this summer and to add support for social networks beyond Facebook later this year.
In addition, the company is announcing a partnership with SapientNitro that integrates the marketing agency’s EngagedNow product with Adobe’s Marketing Platform.
And it’s releasing its latest Digital Index report. Most interestingly, the company says that globally, tablets are now driving more website traffic than smartphones (based on an analysis of 150 billion visits to more than 1,500 websites between January 2012 and February 2013).