Advertisers can focus much less attention on an intraday bid and budget changes. Instead, they can take full advantage of Facebook’s automation features. Here are the most recent innovations and tools for Facebook advertising:
When you advertise on Facebook, ideally you want to build campaigns that drive positive ROAS. With a click, you can now have Facebook perform all bid changes for you in real-time. Their algorithm has gotten very efficient at delivering results. To deliver this efficiency, Facebook’s new algorithm allows you to train it on which people are most valuable to your business.
Beyond the app installs, App Event Optimization (AEO) allows you to educate Facebook on the value of key events, like purchase or registration, and they will optimize your ads to deliver people who are most likely to take those actions. Although, not all people who purchase a product or service hold the same value for an advertiser. As such, Facebook has also enabled value-based bidding that allows advertisers to send the real values of each user into the Facebook algorithm and they will, in turn, find similar high-value people.
Dynamic creative optimization (DCO) selects the best elements to put into an ad based on audience segments and real-time feedback prior to the ad being served. The concept is simple — the right ad, right copyright audience, right time, right language and right device. Since algorithmically-driven creative is tested and optimized against an advertiser’s goals, dynamic ads typically outperform their static counterparts. DCO also works well in conjunction with value-based lookalike audiences to match the right ads with the highest value users for marketers. Further, DCO offers both creative deliveries at scale as well as testing with endless experimentation, all without human intervention required to drive continuous testing and optimization. It’s also possible to enable language testing through DCO to deliver the most efficient language based on performance.
You can create value-based lookalike audiences on Facebook, which are users who behave similarly to past paying customers based on their value. You can denote a value for different types of paying customers (high spenders, medium, low spenders), and by creating these custom seed audiences on Facebook, the platform can then target new users that look like and match the respective value of the custom audience.
Machine learning can analyze and process vastly more data in real time than an army of UA managers. Just like automatic bidding, overall ad budgets can be automated to increase and decrease based on performance metrics and rules set by marketers in real-time, around the clock. By allowing the algorithms to automatically budgets, advertisers get increased performance with a decreased need for human intervention.