Solved: Manual vs. Advantage+ Audience on Meta Ads

Hi there,

Thanks for reaching out! Happy to give you some of my initial thoughts on your Meta Ads question. It's a common one, and the platform is pushing Advantage+ so hard it's easy to think you're missing a trick by not using it.

The short answer is that you're asking a good question, but it might be the wrong one. The real difference in performance won't come from just flicking a switch from manual to Advantage+, but from understanding *when* and *why* to use each tool within a proper campaign structure. Let's get into it.

We'll need to look at the real job of targeting...

First off, let's bust a myth. The goal of advertising isn't just to get the lowest possible Cost Per Acquisition (CPA). I've seen plenty of accounts with dirt-cheap CPAs that were burning money because the leads were rubbish and never converted into actual paying customers. The real goal is to acquire a valuable customer profitably.

The debate between manual targeting and Advantage+ is really a debate about control versus scale.

-> Manual Detailed Targeting: You are the pilot. You're telling Meta's algorithm, "Here is a very specific group of people, defined by their interests in X, their behaviour Y, and their demographic Z. Go find conversions within this pond." This is brilliant for testing hypotheses. For example, "I believe people who are interested in HubSpot and follow Jason Lemkin will be good customers for my SaaS product." You can build that audience and test that specific theory. It's controlled, it's specific, and it's how you discover new, profitable pockets of customers.

-> Advantage+ Audience: You are giving the algorithm the keys to the plane. You provide some suggestions, or 'audience signals' (like past purchasers, website visitors), and say, "You know what a conversion looks like for me. Go find more people like that, anywhere on the platform." The algorithm then uses its vast dataset to find patterns and lookalikes you could never manually define. It's built for scale.

The problem is, people often treat them as a straight either/or choice without understanding the context. When you use "Brand Awareness" or "Reach" objectives, or even broad targeting with a weak pixel, you are essentially paying Facebook to find non-customers. The algorithm's job is to fulfill your command as cheaply as possible. The users least likely to click or buy have the cheapest attention, so that's who you get. This is why you must always optimise for a conversion event (lead, purchase, etc.). Advantage+ with a conversion objective avoids this trap, but the quality of its output is entirely dependant on the quality of its input data.

I'd say you need to define your customer by their pain, not their interests...

Before you even worry about which button to click in Ads Manager, the most important work has to be done. Most people build an Ideal Customer Profile (ICP) that's completely useless. They say things like "We target women aged 25-40 who are interested in yoga." That describes millions of people, most of whom will never buy from you.

You need to stop defining your customer by demographics and start defining them by their nightmare. What is the specific, urgent, and expensive problem they are trying to solve? Your ICP isn't a person; it's a problem state.

I remember a B2B SaaS client in the legal tech space. Their old ICP was "Law firms with 10-50 employees." Their ads were generic and their cost per lead was through the roof. We redefined their ICP's nightmare: "A partner at a growing firm who lies awake at night terrified of missing a critical filing deadline and getting hit with a malpractice lawsuit because their document management is a mess of shared drives and emails."

Suddenly, everything changes. Your ad copy isn't "Efficient Document Management for Law Firms." It's "Stop Drowning in Documents. Never Miss a Deadline Again." You're not targeting a demographic; you're targeting a feeling. You're selling a good night's sleep.

Once you know the nightmare, you can figure out where these people hang out online. What niche podcasts do they listen to? What industry newsletters do they *actually* read? What software do they already use? Those become your manual interest targets. They're not just random keywords; they are precise signals that you understand their world. This is the foundation. Without it, both manual and Advantage+ are just shots in the dark.

You probably should structure your account by funnel stage...

Okay, so you've defined the customer's pain. Now you can build a proper funnel structure. This is where the manual vs. Advantage+ question gets a real answer. Most people just lump all their audiences into one campaign, which is a recipe for disaster. You need to segment by temperature.

I usually structure accounts with separate campaigns for each stage of the funnel. It looks something like this for an eCommerce client, but the principle is the same for any business:

-> ToFu (Top of Funnel - Cold Audiences): These are people who have never heard of you. Your only job here is to see if your pain-point message resonates. THIS is where you use manual detailed targeting. You build audiences based on your ICP research (interests in competitor software, industry publications, etc.) and you test them against each other. You are discovering which signals work.

-> MoFu (Middle of Funnel - Warm Audiences): These are people who've shown some interest but haven't taken a key action. They've watched your videos, visited your landing page, but didn't add to cart or start a trial. Here, you retarget them. You can use a custom audience of 'Website Visitors (last 30 days) excluding Purchasers'. You show them different ads, maybe testimonials or case studies, to build trust.

-> BoFu (Bottom of Funnel - Hot Audiences): These are people who are on the verge of converting. They added to cart, initiated checkout, or added their payment info but didn't finish. These are your most valuable audiences. You retarget them with urgency-driven ads: "Forgot something?" or "Your discount expires soon." You also create lookalike audiences from this group. A lookalike of 'Purchasers' will almost always outperform a lookalike of 'Website Visitors'.

So, where does Advantage+ fit in?
You can test it at the ToFu stage, giving it minimal guidance and letting it run wild. Sometimes it works brilliantly, especially for broad appeal products. But where it *really* shines is when you use it with strong BoFu signals. You create an Advantage+ campaign and you feed it your 'Past Purchasers' list as an audience suggestion. The algorithm now has a crystal-clear picture of your perfect customer and can go find thousands more just like them. It's not magic; it's just powerful pattern matching based on high-quality data that you provided.

You'll need a way to calculate what you can afford to pay...

This brings me to the next point. You can't know if a campaign is successful if you don't know what a customer is actually worth to you. The key metric here isn't CPA, it's the ratio of Lifetime Value (LTV) to Customer Acquisition Cost (CAC).

Let's do some quick maths. Say you run a subscription box service.
-> Average Revenue Per Account (ARPA): £50 per month
-> Gross Margin %: 70% (after cost of goods)
-> Monthly Churn Rate: 5% (you lose 5% of customers each month)

The LTV calculation is: (ARPA * Gross Margin %) / Monthly Churn Rate
LTV = (£50 * 0.70) / 0.05
LTV = £35 / 0.05 = £700

So, each customer you acquire is worth £700 in gross margin over their lifetime. A healthy LTV:CAC ratio is about 3:1. This means you can afford to spend up to £233 (£700 / 3) to acquire a single customer.

Now your perspective on that A/B test changes completely. If your manual audience is getting you a CPA of £150 and your Advantage+ audience is getting you a CPA of £120, Advantage+ looks like the winner. But what if the customers from the manual audience have a churn rate of 3%, while the Advantage+ customers churn at 6%? The LTV of the 'more expensive' customer is actually much higher (£1,166 vs £583). Suddenly, the manual audience is the clear winner, even with a higher upfront CPA. You've got to know your numbers.

So, how should you actually run the test?

Alright, with all that context, here is how I would structure the actual A/B test you asked about.

1. Create one new campaign. Use the 'Sales' or 'Leads' objective, whatever your main conversion goal is. Use Campaign Budget Optimisation (CBO) and set a daily budget you're comfortable with for testing, maybe £50 or £100 per day to start. 2. Create two ad sets inside this campaign. * Ad Set 1: Manual Detailed. Re-create your best-performing manual audience here. Layer a few of your top interests that are highly relevant to your ICP's pain point. Keep it reasonably focused. * Ad Set 2: Advantage+. In this ad set, select the Advantage+ audience option. As an 'audience suggestion', provide Meta with your best data source. If you have over 100-200 purchases, use a custom audience of your past customers. If not, use a custom audience of people who initiated checkout or added to cart. This gives the algorithm a strong starting point. Do NOT add any detailed targeting interests here. Let the algorithm do its work. 3. Use the same ads. In both ad sets, use your 2-3 best-performing ads (creatives and copy). It's critical that the only major variable you're testing is the audience. 4. Let it run. Don't touch it for at least 3-4 days. Let it exit the learning phase. After that, monitor the performance.

My general rule for turning off a failing ad set is when it has spent about 2-3 times your target CPA without getting a single conversion. If your target CPA is £50, and an ad set has spent £150 with zero results, it's time to turn it off. It's probably not going to recover.

What should you expect?
Often, you will find that Advantage+ delivers a lower CPA, especially if you have a seasoned pixel with lots of conversion data. Meta is very good at finding people who are likely to convert cheaply. However, you must watch your secondary metrics. Are the leads from Advantage+ booking meetings at the same rate? Are the customers making repeat purchases? As we saw with the LTV calculation, the cheapest acquisition isn't always the best one.

I've detailed my main recommendations for you below:

This is a lot to take in, I know. It's never as simple as one tactic. Effective advertising is about getting the whole system right, from customer definition to offer to testing structure. Here’s a summary of the main advice I have for you.

As you can see, getting this right involves quite a bit more than just selecting an audience type. It requires a strategic approach that connects your customer, your message, and your campaign structure into a coherent system. One of our B2B software clients, for example, saw their CPL drop to just $22 on LinkedIn ads once we implemented this kind of pain-point targeting and funnel structure. Another eCommerce client achieved a 1000% Return On Ad Spend on Meta by focusing on LTV and using their best customers to fuel their Advantage+ campaigns. It's not about the button you press; it's about the thinking you do beforehand.

Navigating this can be tricky, and it's easy to waste a lot of money learning these lessons the hard way. Often, having an expert take a look can reveal opportunities or problems you're too close to see.

If you'd like, we offer a completely free, no-obligation initial consultation where we can review your ad account together on a call. We can look at your current setup, your audiences, and your results, and I can give you some specific, actionable advice on what I'd do next. It’s often incredibly helpful for people to get a second pair of expert eyes on their campaigns.

Let me know if that's something you'd be interested in.

Regards,

Team @ Lukas Holschuh