Recent advancements in machine learning are significantly changing the advertising landscape. Over the past year, improvements in the technology have enabled marketers to start measuring real net profits from ads and allow small advertisers to effectively compete with large advertisers on a more even playing field. Thanks to machine learning, advertising platforms such as Facebook and Google can now automate decisions for marketers that have a huge impact on performance as well as time management. Before these advancements, user acquisition managers would have to manually adjust ad campaigns multiple times per day to optimize performance, but now machines are making the decisions and the actions for them. While it’s a win for performance-based advertising, will bots and automation ultimately replace the role of the UA manager?
One thing is for certain, marketers shouldn’t fear becoming obsolete. Rather, machine learning is opening the door for marketers to become more strategic. UA managers can now focus on strategy and how to address the changing market landscape rather than focusing on everyday obstacles like optimizing ad campaigns for marketplace fluctuations.
In particular, Facebook recently rolled out improvements in its automation tools for audience targeting, bidding and budget management, app event optimizations and dynamic ad serving. Each of these key new features has a critical impact on UA campaigns to make them vastly more effective for advertisers around the clock. Here, we deep-dive on these five automation features and how they are game-changers in this highly competitive landscape.
Facebook finds the right audience for you, effortlessly
Finding the right audience for a product or service can be challenging for advertisers. But with tools such Facebook’s lookalike audiences with value-based revenue enhancements, the process has gotten much simpler. Facebook uses a source audience, a database of existing paying customers, to find and create an audience that will behave similarly to your previous paying customers. Getting ads to the right audience at the right time with the right creative is certain to improve a campaign’s performance.
Around the clock bidding based on your goals
Marketers want to ensure that their campaigns are driving efficient financial returns on advertising spend (ROAS). With auto-bidding, advertisers will not lose any opportunity to reach their financial objective due to a low or high bid. Facebook allows advertisers to set automatic bids that they self-adjust to ensure a campaign’s optimal performance around the clock.
Gain long-term value from your app
While marketers are heavily focused on the first install or the first click, ultimately advertisers should focus on acquiring users who bring value to their businesses by meeting specific financial goals. Facebook’s app event optimization, for instance, delivers ads to users who are most likely to take valuable actions within apps, like subscribe or pay for a feature. This optimization feature allows advertisers to target users that will bring long-term value to their business.
Campaign budget optimization
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 goals set by marketers in real-time, around the clock. By allowing algorithms to automatically set and adjust ad set budgets, marketers get increased performance with a decreased need for human intervention and error.
Your ad, delivered to the right audience at the right time and place
Dynamic creative optimization (DCO) selects the best combination of elements to include in ads based on audience segments and real-time feedback. The concept is simple: right ad, right ad copy, right audience, right time, right language and right device. DCO offers both creative delivery at scale as well as endless experimentation, all without needing a human tasked with the analysis of continuous testing and optimization.
Facebook’s newest automation tools are now enabling UA managers more time to focus on the one key element that can’t be automated by machines today: high-performing ad creative. Constant creative testing—copy, video, images—all becomes imperative to achieve and sustain a positive financial return from advertising. Audiences quickly become bored with seeing the same creatives, and just as you’ve found a high-performing creative, you still need to plan to quickly replace it. UA managers will continue shifting their time away from campaign execution and more toward strategy and creative development.
Looking ahead, artificial intelligence plays a key role in the future of user acquisition, enabling endless experimentation of ad creative but we can also anticipate that AI will greatly scale creative production beyond human capacity. AI will eventually learn to create videos and develop copy at a greater capacity than people, but we are still years away from that reality, and the majority of this work still falls on creative teams and UA managers.
Outside of new creative, AI can run many key components of UA more effectively and more efficiently than people. So, where does this leave UA managers? Instead of spending time and overhead on quantitative tasks such as managing bids, budgets and manually optimizing creatives, they’ll be able to spend quantitative time focused on strategy, storytelling and creative concepts. For agencies, they’ll also be able to focus more on bigger impact, like campaign strategy and creative development, rather than task management. It’s never been a better time to start experimenting with AI and automated tasks to up-level your UA program strategy and creative delivery.
