Advantage+ Shopping: A New Dawn For E-Commerce on Meta Ads?

Bexley Terrell Written on March 22nd, 2023, Last updated on October 10th, 2023

Last week, Meta rolled out the long-awaited Advantage+ Shopping campaigns to the majority of advertisers. 

What sounds like a really boring prescription drug is actually looking like one of the most exciting developments on the Meta ad platform in years.

Using a brand new machine learning developed especially for the new dawn of Meta advertising, Advantage+ Shopping campaigns (ASC) in the early rollout has provided great results for advertisers, and we believe this will continue. 

We’ve created this guide to Advantage plus shopping to help you understand:

  • What Advantage+ Shopping is
  • What makes it different to classic campaigns
  • How to incorporate testing it into your mix

What is Advantage+ Shopping (ASC)

Advantage+ Shopping is a brand new campaign type specifically geared towards e-commerce businesses. It’s a more automated campaign type that gives people less control over audience segmentation in favour of broader audiences.

It uses an all-new machine-learning algorithm for delivery. Meta claim that it is “designed to be the most efficient solution for performance-focused advertisers looking to drive online sales”. Reported results across the industry have been overwhelmingly positive, and indeed internally, we have seen great early indications of great results for our clients. 

That being said, like with all new campaign types in advertising, nothing is perfect. We are seeing indications that the effect of the learning phase is much more severe and causes more instability and inefficiency than with standard campaigns. So if you are looking to test this campaign type, take that into consideration; make fewer changes and wait a week or so for results to stabilise before you decide it hasn’t worked. 

What Makes it Different to Classic Campaigns

The general theme here is simplicity. They have simplified the campaign set-up process to make it easier for advertisers to get started. Meta has introduced a new machine learning algorithm for serving ads and removed a few features such as audience targeting and placement exclusions.

Broader Audiences

The largest difference between ASC and ordinary campaigns is the restriction on audiences. You have no ability to add Lookalikes, Interest targeting or audience exclusions. 

This sounds like a step backwards. We get it. Everyone rolls their eyes and says, “yet another targeting feature was removed from an ad platform just so that the platforms can make more money.” This is the classic argument in our industry whenever something like this happens.

Yes, it would be nice to know that you could refine your targeting. However, in our experience, the majority of advertisers receive a better overall result from leaning into broad in the correct way, and this is especially true with our ecom clients.

So whilst this is a restraint compared to classic campaign types, we see it as an unsurprising evolution, and, if you are getting a better overall result, then that is all that ultimately matters.

Existing Customer Budget Cap

You can now add customer exclusion lists at the account level. You simply just select the audiences that you have previously configured or create new ones. You can then, assign a percentage weighting from 0-100%, which will ensure that only a certain amount of the budget with go to existing customers.

This is great because it used to be that you could only either do all or nothing. You were either excluding all customers or potentially waste budget advertising primarily to existing customers with no way of reporting on it in the platform.

Now by being able to define a split (and report on it too as a breakdown!) you can actually use this as a tool for getting better results. We all know that the more conversions Meta Ads obtains, the smarter its decision-making is. So by portioning a little budget towards existing customers, where conversions actually may be easier to come by, we are effectively giving Meta a signal of what an existing customer looks like. 

So dependent on your individual circumstances, you may want to provide a 0-20% existing customer budget cap.

The downside to this is that you wouldn’t be able to build an upsell campaign for specific groups of customers using ASC, but you can still do this by using manual sales campaigns in tandem.

How to thoughtfully test Advantage+ Shopping

We wouldn’t recommend that you switch all of your campaigns to ASC immediately. In fact, currently, we are seeing the most success running these campaign types along side manual sales campaigns. 

We recommend portioning a small percentage of your budget, dependent solely on your required investment, to reach 50 conversions in a week. So look at your current CPA and multiply that by 7.15. This is the minimum daily budget we recommend using to test this campaign type.

The more you can afford to risk, the better, as this will enable you to exit learning faster, but it’s probably not wise to utilise a high percentage of the budget if this could cause problems to the bottom line of your business should things not work out.

Secondly, you need to give it time. We are finding that the learning phase is a little more unforgiving with this campaign type, and we are finding that the first week can be a little rockier than with manual sales campaigns. Give it a few weeks before assessing its success.

These are general rules, and everyone’s account is different, so please consider your own circumstances before testing this campaign type and feel free to reach out to us for advice around testing advantage+ shopping campaigns.

Bexley Terrell Hey, Bexley here 👋 When I’m not running up that hill, scaling paid media campaigns, I’m often found watching live music or binge-watching How I Met Your Mother for the five hundredth time.

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