Advantage+ Campaigns - What are they and should I be using them?

Paid Social Article

TL;DR

Meta's Advantage+ uses machine learning to boost efficiency and performance. The current App and Shopping campaigns analyse your data to find the right audiences and drive results.
But it's not a silver bullet. Creative fatigue is a risk if you launch it and leave it, or you launch with too few ads without regularly adding more.
The auto-suggestions don't always fit your business. Meticulous management is still key, and we would strongly advise against turning on apply auto-recommendations. STRONGLY.
From our experience, Advantage+ works best for high-frequency B2C conversions. B2B needs more deliberate effort to inform the algorithm. Low-frequency conversions don't provide enough data points to get the best out of the machine.
These aren't one-size-fits-all campaigns. Thoroughly test these features before any full restructuring.

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Intro

Meta's new Advantage+ campaigns are the latest in algorithm-led advertising. These tools take over marketing tasks and automate the heavy lifting.

Specifically, Advantage+ campaigns eliminate manual audience targeting. By inputting up to 150 ads, you inform the machine learning with many data points. This reaches the most valuable audiences while slashing setup time.

The goal is to optimise budget efficiency to boost online sales. It combines AI with Meta’s “proven best practices” to optimise across the user journey.

So in Meta’s words, Advantage+ saves you time while spending your money smarter. But how exactly does it work? How can you capitalise on this powerful new option? And is it the right option for you/your client?

Advantage+ campaign types

There are two Advantage+ options right now: Shopping and App campaigns.

Each consolidates all your ad types into one campaign, in practice. This singular campaign then targets audiences across the entire customer journey - from awareness to consideration to conversion.

With Advantage+, you can say goodbye to splitting campaigns out by funnel stage like brand awareness, consideration, and remarketing. Instead, Meta's advanced algorithms combine your goal with their best practices. This gets the most bang for your buck across Meta's properties.

So the AI handles mapping your assets to each stage for you. One campaign now covers the full journey. Pretty solid, right?

Woman presenting data to a man sitting at a desk.

What is ‘Advantage+’?

Meta's new tool taps into three key sources to optimise your campaigns:

First, it uses Meta's uber-bank of audience data. We're talking demographics, interests, behaviours - the full profile. This helps Advantage+ identify who to target for your products. They hold all of the cards on the audience, so it's a great idea to give them the reigns on that one. Test it.
Next, it looks at product info like category, price, and images. This clues Advantage+ into what you're selling so it can match products to audiences. This is particularly important for ads that use your ‘catalog’, and is influenced by the quality of your commerce manager ‘catalog’ management. If you have warnings telling you about the quality of your ‘catalog’, don’t ignore them.
Finally, it tracks the performance of any ads you import across Meta's platforms. This teaches Advantage+ which creatives work best for different goals and people. By ‘import’, I mean there is a function when setting up these campaigns to simply click import ads that already exist, and it pulls them through. The algorithm also considers how well these have performed to dictate how the new campaign uses them.

With these rich signals, Advantage+ gets smarter over time. It learns who responds to what and how to optimise spending. The more data, the better it gets at convincing your ideal users to convert.

How much time do they save?

So whilst these campaign types save you the time of figuring out how to apply your understanding of your ideal customer to Meta’s targeting, it is not a simple campaign type.

You must regularly analyse how these campaigns compare to ordinary manual sales campaigns to ensure you are using the right strategy, and always challenging that assumption that you “must be using the right set-up because it worked 3 months ago”.

This type of campaign lives and dies on regular input from new ad creative to test what’s working. Regular new creative input is essential - perfect ads don't exist. There's always room to improve, diversify, and capture more people. Alongside Advantage+ driving higher engagement rates and lower CPMs. That means users see these ads more frequently across awareness, consideration, and conversion. Without new assets, it may serve the same favourite ad for all phases. This compromises structure, causing faster creative fatigue.

You can turn on the function to apply all of Meta’s “proven recommendations”, but without knowing the method of exactly what industries were tested with these recommendations, what products, budgets, creative, and more, it’s impossible to know if it suits your ad account without testing. And testing takes time.

So how much time do you save? It’s a debatable question, and there are certainly ways in which you save time. The answer depends on your capacity for regular, diverse creative and solid budget. With those, Advantage+ excels at automating fiddly ad set and budget management, especially with the newly launched Advantage+ budgeting. But prepare to invest stonks in testing, expanding creative, and ensuring tracking is tight. If you don’t know what I mean by stonks, don’t worry about it. I’m young and cool and very nice.

Man sat on the floor working on a laptop.

Our experience with it

We have tested this campaign type with many of our ecommerce clients. The one thing we can say with certainty about it is it’s not for every account.

This is a campaign type built for accounts that can overcome those previously mentioned barriers - budget, creative fatigue, and time to test and manage. If any of those fall to the wayside, your performance will be seriously impacted by it. Stringent budget? You now need to control your activity. Not bringing in new ads? Find one ad now gets all of the budget? Applying automated recommendations? Come back to a super simple account not covering all bases.

But for those clients that it has worked for, you see significantly cheaper CPMs and CPCs. You reach more users for less money spent, and those users engage at higher click through rates. And often you see similar on-site performance in conversion rates and average order values too. Whilst that has only been with high-frequency, lower-AOV conversion ecommerce clients, we are actively challenging this statement and testing it across all clients.

Conclusion

So, test it yourself. Make sure your tracking is on point so your machine-learning is using accurate data points.

Then, if the test looks good, build a bank of 20-50 ads to launch with, and get it out there.

Update your active ads monthly. Test new primary texts, headlines, descriptions, and assets. And if an opportunity arises, double down. These campaigns can be enjoyable to manage, whilst simultaneously supercharging your revenue driven and are dynamic enough to capitalise on these opportunities.

Whilst there are many things to consider with these campaign types, as long as the quality of your activity is high, you will find some success here. If the quality isn’t high, keep scrolling and ‘say hello’.