Solved: Advantage+ Campaign Audience Targeting Strategy

Hi there,

Thanks for reaching out! Read through your question and it’s a good one – something a lot of advertisers grapple with as they start spending serious money on Meta. You've hit on a common frustration with Advantage+: it works, sometimes freakishly well, but it feels like a black box.

Your idea to sort of 'trick' the campaign into giving you more data is clever, I'll give you that. But my honest opinion? You’d be fighting the algorithm, not helping it, and likely hurting the great performance you're seeing. The real issue here isn't a lack of reporting in one campaign, it's that at your scale, you've outgrown the 'all-in-one' campaign structure. You need to graduate to a more sophisticated setup that gives you both scale *and* the control you want.

I've put together some of my thoughts on how we'd approach this for a client spending $5k/day like you are. It’s a bit of a shift in thinking, but it's how you unlock the next level of growth.

So, you want to outsmart the Meta algorythm...

First off, let's talk about what Advantage+ Shopping Campaigns (ASC) are actually designed to do. Meta built them to have maximum freedom. You give it a pixel, a catalogue, your creative, and a budget, and you tell it "go find me people who will buy my stuff". The algorithm then uses its trillions of data points to do exactly that, without being constrained by narrow audience definitions you've cooked up.

When you start telling it "okay, but my 'existing customers' are actually these non-purchasing email subscribers, and my 'engaged audience' is just these specific engagers", you're putting fences around a racehorse. You're forcing it to focus on pools of users *you think* are valuable, instead of letting it find the users it *knows* are about to convert, wherever they might be. Tbh, the algorithm knows who your next customer is better than you do.

There's a concept I talk about a lot: paying Facebook to find your worst customers. This usually happens when people run 'Reach' or 'Awareness' campaigns and the algorithm just finds the cheapest people to show ads to, who never buy. Your situation is a bit different because you're optimising for conversions, which is good. However, the principle of unnecessarily restricting the algorithm holds true. By mislabeling your audiences, you're introducing noise and confusion. The machine might over-spend on your 'Klaviyo sign ups' because you've told it they are 'existing customers', even if a pocket of completely cold users in a lookalike audience is actually converting at a much better rate. You're essentially blinding it to opportunity.

The desire for control is completely understandable. But the solution isn't to butcher a campaign type that's built for automation. The solution is to use the right tool for the right job.

I'd say your real problem is the blended funnel

The core of the issue is that you're mixing completely different user temperatures in one pot. A new user who has never heard of you needs a very different message than someone who abandoned their cart 3 hours ago. A past customer on your Klaviyo list needs a different message again.

At a small budget, blending can work. But at $5,000 a day, you have more than enough traffic and data to justify a proper, segmented funnel structure. This is how you stop guessing and start knowing exactly what's going on. This means splitting your activity into three distinct stages:

• ToFu (Top of Funnel): Prospecting for brand new customers. People who don't know you exist.
• MoFu (Middle of Funnel): Retargeting warm audiences. People who've shown some interest - visited your site, watched a video, engaged with a post.
• BoFu (Bottom of Funnel): Retargeting hot audiences. People who are on the verge of buying - added to cart, initiated checkout.

By separating them, you can tailor your message, your offer, and your budget to each stage. And, crucially, you get the exact data breakdown you're looking for. You'll know precisely how your FB engagers are performing versus your website visitors because they'll be in different ad sets or even different campaigns.

Here's the campaign structure we'd build for you...

Okay, let's get practical. Forget the single ASC campaign. Here’s a blueprint for a structure that will give you clarity and let you scale effectively. It's built on that ToFu, MoFu, BoFu logic.

Campaign 1: ToFu - The Prospecting Machine (Advantage+ Shopping)

This is where you let ASC shine. Use it for its intended purpose: finding new customers. Set it up, give it your best creative, and let it run broad. The only audience input you should have is uploading your customer list (your Klaviyo list) and telling Meta to use it as an *exclusion* list. This forces the campaign to hunt for new people. You can also exclude recent website visitors (last 30 days) to keep it extra clean. Its one and only job is to fill the top of your funnel with profitable, new traffic.

Campaign 2: MoFu - The Nurture Engine (Standard Conversions Campaign)

This is where you get all the control and data you've been wanting. This is a standard 'Sales' objective campaign, not ASC. Here, you'll build separate ad sets for each of your warm retargeting audiences:

• Ad Set 1: Website Visitors (last 30 days). Exclude anyone who Added to Cart or Purchased.
• Ad Set 2: FB/IG Page Engagers (last 90 days). Exclude website visitors to avoid overlap.
• Ad Set 3: Your Klaviyo list of non-purchasers.

Now you can see exactly how each audience performs. You can allocate budget based on performance and tailor your ad copy. For website visitors, you might show testimonials. For social engagers, you might show user-generated content (UGC). Total control.

Campaign 3: BoFu - The Closer (Standard Conversions or Catalogue Sales)

This is for the hottest leads who are right on the edge. This campaign targets high-intent actions, usually with Dynamic Product Ads (DPA) that show them the exact product they were looking at. Again, separate ad sets are key:

• Ad Set 1: Added to Cart (last 14 days). Exclude Purchasers.
• Ad Set 2: Initiated Checkout (last 7 days). Exclude Purchasers.

The messaging here is about overcoming last-minute objections. Maybe you remind them of your shipping policy, a guarantee, or even a small discount to get them over the line. These audiences are small but incredibly valuable, and you need to treat them separately.

You probably should prioritise your audiences properly

Once you have this structure, the game becomes about testing and optimising within it. Not all audiences are created equal. As a general rule, the closer an audience is to the final conversion action (a purchase), the better it will perform. This applies to both retargeting audiences and the lookalikes you build from them.

Here’s a rough priority list I use when building out accounts. You should be testing audiences in this order, from top to bottom.

For your new MoFu/BoFu campaigns, you'd create ad sets for the audiences in priority 1 and 3. For ToFu, once you want to test beyond broad ASC, you'd use standard campaigns to test lookalikes and interests (priorities 4, 5, and 6).

You'll need to know the maths that actually matters

Spending $5k a day means you're operating at a level where small tweaks have massive financial implications. You mentioned your customer retention is around 30%, which is fantastic. But are you using that information to guide your ad spend? Most advertisers obsess over daily ROAS (Return On Ad Spend), but at your scale, the metric that truly matters is the ratio between your Customer Lifetime Value (LTV) and your Customer Acquisition Cost (CAC).

Your high retention means each customer you acquire is worth far more than just their first purchase. Knowing that number tells you exactly how much you can afford to spend to acquire a new customer and still be wildly profitable. If a customer is worth £1,000 to you over their lifetime, paying £100 to acquire them is a no-brainer, even if their first purchase is only £50 (a 0.5X ROAS on day one). This is the maths that unlocks aggressive, intelligent scaling.

I've built a little calculator for you below to estimate your LTV. Play around with the numbers.

This is the main advice I have for you:

To wrap this all up, here’s a summary table of the strategic shift I'm recommending. This is your actionable plan to move forward.

I know this is a lot to take in, and it represents a significant change from your current setup. Making this transition effectively – choosing the right budgets for each campaign, crafting the right creative for each funnel stage, and interpreting the data correctly – is where having an expert eye on the account can make a massive differance.

It can be the difference between successfully scaling to $10k or $15k a day, or seeing your performance drop because the structure isn't quite right. If you'd like to chat through this in more detail and have us take a look at your account, we offer a completely free, no-obligation strategy session where we can map this out specifically for your business.

Hope this helps give you a new way to think about the problem!

Regards,

Team @ Lukas Holschuh