Speaker 1 (00:00):
In this episode, we're going to speak around meta ads, when to scale and when to switch off, and the mistakes that a lot of founders that I see make mistakes that I've made as well. How to double click into what is the right creative, what is the right CTA, what is the right attribution window versus when to actually switch it off to save budget and to protect that burn rate. So hopefully there's some actionable insight within this. Hey, it's Oliver Bruce and welcome to the Unlock. Previously known as Success is in the Mind. I'm a UK entrepreneur, angel [00:00:30] investor, a neurodivergent founder, and I recently exited my first business, which I scaled from my university halls into a multimillion dollar agency with no backing, no funding, just grit, mistakes and determination. I want to pass on some of the lessons that I've learned, the barriers that I had to overcome and the challenges that I'm still coming up against today. This podcast doesn't grow by itself, it grows with you. If you could possibly share this with friends, family, colleagues, anybody you're in business with, somebody that you think might find this useful would be greatly [00:01:00] appreciative. Anyway, let's get into it.

(01:06):
Alrighty, so we're going to double click here into meta ads. Specifically. We're going to go deep on something that sounds super simple but is actually really done properly, and that is when to actually turn an ad set off for instance, or when to let them breathe, right? A lot of people get impatient. A lot of people will turn them off because they haven't seen the results too early. Equally, there are some people out there that might leave them running for too long simply because they've put a lot of money behind it from an ad creative perspective and they're, [00:01:30] I guess thinking that it's going to perform when actually it really isn't and it's time for them to switch it off. Now, often it's rarely a platforms issue. It's normally a human behavioural issue, and there are sort of two extremes that I can see consistently that I've noticed having founded a few businesses and dealt with entrepreneurs along the way, as I said, one turns 'em off too early, one turns them off essentially too late.

(01:54):
Both the kind of expensive mistakes both you can avoid if you know what you're doing. So let's [00:02:00] maybe start with the impatient part of the process. So individuals that turn things off too quickly because they're just not getting the returns. So an ad launches, it spends for let's say three or five days, and the CPA cost per acquisition is above the target. A couple of leads have come through, but not enough to necessarily feel comfortable. So you guys, you might get cold feet, you turn the ad off, for instance, on paper, that kind of feels responsible. You're protecting the budget, you're looking at your burn rate. You kind of understand that actually if you haven't had the leads that you want coming through in the timeframe [00:02:30] that you feel comfortable with, it's time to turn it off, but actually you're killing something before it's really had a fair chance to actually get moving.

(02:37):
You've only had it on for a couple of days, you've only had a few leads come through. You've only put a minuscule budget behind it, but yet you've got cold feet. Now, meta isn't a static media buying platform. It's sort of probabilistic, if you will, so it runs on probability. It needs data to understand essentially who's converting and why, and if you're turning it off too soon, it's not actually getting that data, it's not [00:03:00] getting fed essentially. Think of it like a growing human. We need food to be able to grow. We start off, we get fed by our parents. If we get switched off too soon, then we're not going to make it past our first birthday, right? It's the same principle with this. It needs feeding, it needs data, it needs budget behind it. It needs people to be clicking through. The first few days can be quite messy.

(03:19):
CPMs can kind of fluctuate. CPAs look volatile. All the stuff that you'd expect during a learning phase. A bit like when a kid's eating food, right? The first couple of years of its life doesn't eat very well, doesn't eat very cleanly, [00:03:30] throws things on the floor, but actually over time it grows, right? Same principle here, the algorithm is testing kind of pockets of audience behaviour, things that work, things that don't work. Eventually, it will get to a point where it is either going to work or it is time to turn off, but if you're interpreting that and you are learning from that, then you know what the right outcome should be. You kind of end up stuck in this permanent testing mode, right? If you're actually doing it correctly, it never actually lets the system mature. You're constantly feeding it with more information. But before you label something [00:04:00] as a winner or a loser, just slow down and interrogate the context a little.

(04:05):
Don't switch it off too early. As I said, don't leave it running for too long, but just look at the data, understand why it's doing what it's doing, and try and get some context from that. Is it working? Because for instance, the ad spend is sufficient. Is it working because the CTA is correct? Is the audience set right? There's lots of little nuances within that. How much is it actually spent relative to your allowable CPA? Have you looked at that data? That's simply looking [00:04:30] at how much you've put in versus what that cost per acquisition is out. If your target CPA is 100 and it's spent for instance 150 without a conversion that that's not conclusive, that's not necessarily going to be the right budget behind it to give you an accurate data point. Hey guys, sorry for interrupting the podcast, but I thought you might find this useful.

(04:49):
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(05:39):
Let's get back to the episode. A conversion events happening at all, even if they're slightly above target, momentum does actually matter. So if they're actually a little inefficient, keep that momentum up, keep that ad running, that's really important to get that data to get that learning window. What is the attribution window actually telling you, right? Are you judging off platform only or [00:06:00] are you cross referencing from CRM through to other areas? So attribution for those that don't understand. If you had a window, let's say 90 days, someone sees your advert, they click on it, but they don't actually fundamentally buy, they then eventually buy from you down the line. That attribution window is really important, but we need to understand what that is in the first place to know whether that a's working, because it's not always that people, individuals, clients, whatever it might be, are buying from your advert the minute that they see it.

(06:27):
So understanding that attribution window, giving it that breathing space [00:06:30] and allowing it to kind of feed into your data set is super important because turning it off within a 30 day window and your attribution window at 90 days, obviously you're shooting yourself in the foot, you haven't got that true aggregate of data. Is the ad actually fundamentally still learning and has it stabilised? Has frequency climbed? Are the click-through rates healthy? But conversion is weak. Suggesting potentially in that case that a landing page issue rather than a creative issue might be the issue or might be the problem, right? You said issue a lot there, but if [00:07:00] you are clicking on the ad for instance, the frequency is cool, it's stabilised, click-through rates are looking positive and they're going through, they're banging through to your landing page, but they're not actually converting, then the issue isn't actually necessarily the advert.

(07:13):
The issue probably is the landing page and the CROs, the conversion rate optimization funnel that you guys might have built. A lot of founders out there don't have landing pages. They think that just banging people through to the main website is the way to go, and actually maybe that's a podcast for another day, but it definitely isn't putting them [00:07:30] through to a bespoke and a niche landing page that talks exactly to the issue or the problem that you're trying to solve is super, super important. So maybe have a look at that, but most, I guess poor decisions in summary come from Shannon analysis. So flipping it on its head, I guess just because the ad is spending and generating conversions does not automatically make it a long-term winner. Meta will push budget specifically towards what it believes is the strongest in the moment. That is fundamentally what Advantage Plus is doing.

(07:58):
It essentially is caching in on [00:08:00] short-term signals, but to I guess truly understand what is simply working, it must have data and it must have volume. You might think it's a short term winner. You might keep it on, it might get good click through rates, it might go through to the landing page, but actually you might drop off there because your landing page isn't right. It might be set up incorrectly. From an audience standpoint, you might not necessarily have the optimization correctly built. There are a number of different areas that unless you run an ad for a specific duration and that specific duration is often longer than most people feel comfortable with, very, [00:08:30] very often you won't have that data to be able to make that educated decision as to if to actually turn it off or to keep it running. If you don't actually structure your account intentionally, your winners can actually end up cannibalising everything else.

(08:42):
So new creatives get starved before they actually get a chance to prove themselves. Now, what I mean by this is if you do have an absolute blinder of an advert that you are running online and that is generating you good returns and you're very happy with it, and then you go and put three or four new creatives out there because of the way that Advantage Plus runs, [00:09:00] it's going to push the majority of the budget towards that winning ad creative because it knows it's fundamentally working, which means that the other creatives, which could be exactly the same in terms of CTA, it could work just as well, won't get a chance to actually breathe properly because the winning ad is taking all that budget essentially. So that's where structure becomes super, super important, and here's the kind of framework that I use or we use specifically to refine that consistently.

(09:28):
So essentially when an ad demonstrates consistent [00:09:30] performance, and I mean multiple conversions, stable CPA over a meaningful window, healthy engagement metrics at that point, move it into a dedicated winners ad set. So not just having it in the same ad set that you currently have all your creatives in, build a completely new one, make sure that you have the winners in their only, and that way you're not going to cannibalise the budget when you try and test and learn with the other creatives, don't essentially leave them competing with fresh tests. Allocate roughly, I would say 70%, sometimes [00:10:00] more depending on confidence of your total budget to that winner's ad set. The remaining 30% or so is a clearly defined learning and test ad set budget, so you're kind of happy to put that out there, hope that it works, hope that it learns, hope that it spends well, but the reality is you're going to get good data from that 30% bang it over into that winner's ad set where the 70% of budget is being put behind, and that's where you'll start to gear essentially.

(10:25):
That's where you'll start to actually get good efficiencies that the creative's going to work [00:10:30] and you're not going to cannibalise the tests with the ads that are already working. This sort of separation does three things. So first, it protects your revenue engine, so winners get fed properly and they're not diluted. Secondly, it kind of creates psychological clarity, exactly which ads are responsible for what performance, and thirdly, it builds clean data so you're not muddying signals by mixing proven creative with early stage experiments. Then you can treat that learning [00:11:00] ad set like a lab, new hooks, new angles, new offers, new formats, have a bit of fun with it, see what happens. That 30% budget is being used specifically to test and learn when something's in that learning phase. It's sort of proving itself with real data, not just having one lucky day where you generate a load of leads, but consistent performance and at that point you graduate it into the winners, right?

(11:22):
And when you do that, you can analyse the data properly and some key kind of points or key metrics that I sort of run through and looking at what good looks like [00:11:30] are as simple as what is the hook? Is it pain led or aspirationally led? What is the CTA A? Is it direct or soft? Is it a founder for piece to camera or is it more of a product focused piece of creative? What is the objection? How do we neutralise that? All those kind of key points that you can take out of the creative if it's working or if it's not working similarly, and either put into, for instance, your new creative if it is a winner or take hours of anything moving forwards. If for instance, it's a loser, you don't need to necessarily scale it, you need to reverse [00:12:00] engineer it. That's how I look at it.

(12:01):
So when you've got an ad that is working great, break it down, compartmentalise everything, understand exactly why it's working, and then build upon that rather than just chucking a load of budget behind it. Similarly, if it's not working, again, break it out, understand why, and don't do that moving forwards, okay? What you do then is you feed the insights back to the next round of testing. It's as simple as that, and people often get stuck at this point, but looking at if it is the CTA, and that is exactly why people are [00:12:30] clicking through and it's because it's an aspirationally led video, right? And people are wanting to solve joint pains, let's say, by taking whatever supplement it is, then that's great. That's the reason it's working. Now, compound that, put that into future add creatives talk in the same style, answer the same pain points, and I pretty much guarantee, although I can't actually guarantee, but near as damn it that the next ad set will work, right?

(12:55):
So scaling on meta is not about doubling budget blindly, it's about increasing spend [00:13:00] on predictable mechanics. Okay? So it's an analytics and data game, not necessarily a broad brush stroke and throwing stuff at the wall. A lot of people think the anter update is just pumping content out there and hoping for the best. The reality of it is there is still an element of elegance to it. You need to make sure that yes, whilst there's diversity with regards to the creative, that actually you are analysing the reasons as to why, and you're not just letting the machine cannibalise what it thinks is good, because otherwise you're only going to have a [00:13:30] handful of ad sets and you're not necessarily going to be able to scale sufficiently. I guess this is the summary of where creative meets science, if you will, or where creative meets data, and it's often where so many brands struggle.

(13:43):
They want to scale before they have clarity, but essentially clarity comes with structured repetition. It's kind of as simple as that. Now, let's talk about when actually to kill an ad. So we've talked a little bit about when to scale an ad, double down on ad, how to actually create new genres, new creative, new ad sets, [00:14:00] et cetera. But let's talk about when to kill an ad because it's fundamentally wasting you money. And again, the data needs to be unambiguous for this. Similarly to the one previously where we spoke about scaling, you need that data to be super, super clear. So meaningful spend relative to CP, a, potentially weak click through rates suggesting poor resonance, possibly low engagement signals, rising frequency with declining performance or strong clicks, but poor conversion rate indicating a broken journey that you're not [00:14:30] prepared to necessarily fix yet, notice the difference.

(14:32):
All of that is not emotion. That's obviously very, very data led, and this is evidence. The biggest unlock for most founders running meta ads is separating the feeling from fact. Often founders sit there and go, shit, I've wasted 5, 6, 7, 8, 9, 10 grand on this ad and it hasn't generated anything, but actually has it been set up correctly? Is the flow correct? Is the creative correct? Are you analysing the data and removing that subjectivity? So it is unambiguous, often not if you feel nervous because [00:15:00] spend is increasing. That is not a performance metric. If you feel excited because one of the ads one day for instance had a huge day, again, that's not scale redness. That's just you being emotional towards an outcome. Meta rewards fundamentally calm operators, people that can analyse data, people can understand exactly what they're putting in and what they're going to get out the other end rather than a sporadic approach.

(15:24):
So what is essentially a calm operator? Well, it's people who let data [00:15:30] accumulate. People who structure accounts intentionally. People who understand the learning phases are actually investments, not inconveniences. If you master that discipline, then you are essentially going to be able to make the decision as to whether to scale or not scale. So in summary, essentially yes, fine, when you're starting out have one ad set, put good budget behind it, look into the analytics, look into the data, look into the attribution window, understand exactly why something is or isn't conversing, [00:16:00] and when you find something is working super well, split it out into a new ad set so you're not cannibalising your test budget 70% into the winning ad set, 30% into the test ad set, right? And then in that test ad set, understand exactly why the winning ad set was working so well and put in new creative to that.

(16:19):
And again, when to switch and add off. Analyse the data, understand the inefficiencies note, have you put enough money behind it? Have you let it run long enough, for instance, and make sure that [00:16:30] it's not a subjective switch off and it's a data led switch off. Remove the emotion and you'll be able to scale anything. This is when you move from guessing to compounding, and I guarantee your business will grow because of it. Appreciate you listening to the podcast. Hopefully you found it useful. For those that want to read up or learn more, head over to my LinkedIn page, Oliver Bruce online where you'll find a weekly newsletter called the Brucey Bonus where we double click into more detail and give you more tips and tricks around how to scale your [00:17:00] business. If you want to share this with friends, family, colleagues, business owners, people that are in your circle then might find it useful.

(17:09):
I would be super appreciative if I said at the beginning of the podcast, this does not grow on its own. This grows with you and we do it for you. So thank you so much for listening and catch you next time. I mentioned earlier, but I do think something that you guys might find super useful if you're running a business and managing multiple transactions across multiple platforms is in card. It's a new [00:17:30] financial platform for modern online businesses, giving you guys multicurrency accounts, connected banking and smart spend managements all in one place. You can open up an account in minutes, attach cards for expenses, and earn up to 2% cash back on everyday spend like ads, SaaS, and travel. Check out incar using the link in the description.