If there is one thing Meta has been pushing on paid social practitioners over the past couple of years, it’s automation.
From automatically “enhancing” creative to fit the needs of the different placements (and people) on the platform to suggesting copy for your ads, Meta is making its ad platform as approachable as possible.
And that’s the goal. Not just to encourage digital laypersons to strike out solo and start spending ad dollars on it’s simple self-service platform but to make the ongoing tweaks necessary to keep the results flowing.
Their ambitions for turning ads manager into a paid social autopilot have reached a new altitude with AI-powered Advantage+ audience targeting.
Advantage+ targeting is the latest in Meta’s suite of (rebranded) automation products aimed at helping advertisers achieve better results.
Advantage+ targeting joins older products like Advantage+ shopping and Advantage+ creative to automate many of the setup and optimization needs of campaigns.
The goal is to achieve better results by “trusting the algorithm” and giving it the freedom and flexibility to make certain decisions without manual intervention – specifically:
When you see “Advantage+” on the Meta platform, you can easily replace that term with “Automated” and get the gist.
Dig deeper: Meta advertising: 5 best practices
Put simply, you’re letting Meta determine who should see your ads. You can (optional) provide “suggestions” on who to target. But Meta will use AI and performance data to determine who the right audience is.
If you would like to provide input, advertisers have two options:
Audience controls set the must-have criteria for your campaigns. Advertisers can select geographic locations, minimum age, custom audiences (lists) to exclude, and language. These are requirements, and Meta will not ignore them.
Advantage+ audience suggestions can also be made. By selecting custom audiences, age ranges, genders and even detailed (interests and behaviors) targets, you can help point Meta’s AI in the right direction to get things started.
Anything in the Advantage+ section will be treated as a suggestion but should help with the initial testing.
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Functionally, Advantage+ audiences are essentially the same as broad or open targeting.
With open targeting, you leave the detailed audience targeting blank (open) and give Meta the option to target anyone within the geo and age range you selected.
This has been a viable targeting option on Meta for a few years, given the platform’s ability to react quickly based on data. With open targeting, you’re essentially telling Meta that you don’t care who sees your ads as long as you get the result you’re looking for.
Advantage+ targeting is largely the same. Instead of telling them who to target, you’re telling them who not to target, and letting the machine test its way into the ideal audience.
Fewer restrictions = better results. At least, in theory.
We approached one of our clients, a major B2B company, with a proposal to test Advantage+ audiences with the goal of reducing average CPLs.
The company uses Meta lead generation forms to collect potential handraisers, who are then contacted by an internal sales team.
Meta is one of the company’s highest-volume channels, but quality is an ongoing issue. CPLs are cheaper than just about any other channel, but conversion rates pale in comparison to paid search, which is higher intent.
Our goal was to test Advantage+ audiences in as much of an optimal “real-world” scenario, not as a strict A/B test.
So, we added an Advantage+ audience to an existing campaign that contained an interest-based audience (based on the client’s target customer profile) and a website and engagement retargeting audience.
Over the next week, we let Meta (through Campaign Budget Optimization) decide how much to spend on what audience, using only the goal of maximum leads as our KPI.
After a week’s worth of data and following the completion of the learning phase, performance patterns started to emerge. Here’s what we observed:
The poorer post-lead conversion of the Advantage+ audience is sadly consistent with similar tests we’ve run for different clients.
Open targeting has also delivered poorer-performing B2B leads than even slightly targeted (but still large) audiences.
With its lack of business firmographic targeting, B2B lead generation is already a tough enough proposition on Meta.
And while Meta has clearly made big strides in reducing costs, if the lead quality issue isn’t seriously addressed, it will continue to lose ad revenue from B2B advertisers in favor of LinkedIn.
Being successful at driving quality B2B leads on Meta requires you to craft a strategy that exploits the platform’s advantages while protecting yourself from the inevitable poor-quality leads you’ll likely get.
Meta’s new Advantage+ targeting is a useful tool to help less experienced and/or lower intensity advertisers drive get better cost pers. But if lead and conversion quality is a big concern, you’ll need to be deliberate and careful with your testing.
Using Advantage+ targeting will likely get you cheaper upfront leads but with a lower likelihood for them to convert. But that doesn’t mean you shouldn’t test it. Instead, you must develop strategies to remove lower-quality leads before they are submitted.
On Meta, the front line of the quality battle needs to be the form itself, not the targeting. If you’re fighting against what makes Meta great, you’ll lose.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
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