It’s complicated. Personas have long been the holy grail of targeting. Take Jeff. Jeff is a 30– to-45-year-old father who loves the outdoors. We want to target him, but how? The answer has always been to build keyword lists and audience targeting matching the Jeff persona. But immediately, this limits our audience.
But, don’t we want to limit our audience? Here’s the reality: There are a finite number of Jeffs, and he might be expensive to capture. Your audience of 100,000 Jeffs is limited to 20,000 because, for most of them, you need to pay more than $100 to convert.
Brands should stop focusing on personas and instead turn to profitability. Is it really important for Jeff to convert if Megan, a single 56-year-old who loves the spa, is ready to?
This exemplifies why the changes Google is making to targeting actually do advertisers a favor. It puts targeting in the hands of the machines, which can find users faster and more accurately than marketers. That doesn’t mean marketers are out of a job. Actually, the opposite is the case. The key is leaning into what machines versus humans should be in charge of.
The machines know more about users than marketers do. The algorithms are watching what users are doing and categorizing them. This process will always take place, whether or not Google and other platforms share this information with advertisers.
Not only do machines have access to more information than marketers, but they act on information in real time. The fastest marketers can make decisions is a few hours after the searches and activity happened.
There’s still a lot that machines can’t do:
-- Machines don’t have the business information marketers have. They don’t know at which point a CPA sees diminished returns against profitability. Organizing and standing up offline data is an important role that a platform can’t achieve on its own. Platforms need the input from marketers on profitability and points of diminished returns to remain successful.
-- A machine can’t make optimizations to your website. Leveraging automation doesn’t mean there is no optimization to be done, it simply changes what we’re optimizing. Rather than negative keywords and placements, marketers can focus on conversion rate optimization, site structure, and content.
-- Machines are self-attributing and don’t play nice together. Facebook and Google will never share information with each other. Google will always show analyses and data that prove why brands should spend more money with Google. Humans are needed for our expertise in multi-touch attribution.
Ultimately, the loss of targeting information is a benefit. Instead of starting with narrow audiences and continuing to narrow said audience through cost per acquisition (CPA) and return on advertising spend (ROAS) goals, we can flip it.
By focusing first on CPA and ROAS goals, we can effectively scale to whichever user is meeting those goals. By letting go of targeting and focusing on results-based campaigns, brands can have the best of both worlds and drive both volume and efficiency.
Let go of your keyword and audience data. Let the machines show you who your “Jeff” is while they work their magic. But don’t forget where to maximize success.