How to Set the Right ROAS Targets in Google Ads

*Apologies in advance for the disrupted audio in this episode, next week will be back to normal.

Setting a random ROAS target and hoping for the best? Not a good strategy. 

In this episode of Google Ads unleashed, host Jeremy breaks down a smarter, data-driven approach to finding the right Return on Ad Spend for your campaigns—one that goes beyond what Google Ads tells you. 

You’ll learn how to use incrementality testing and calibration multipliers to reveal your true ROAS, avoid misleading metrics, and set profitable targets based on real performance.

Google Resource: https://www.thinkwithgoogle.com/_qs/documents/18393/For_pub_on_TwG___External_Playbook_Modern_Measurement.pdf

Get your free 30 minute strategy session with Jeremy here: https://www.younganddigital.marketing/

Scale your store with 1:1 coaching: https://www.younganddigital.marketing/1-2-1-coaching

Transcript

Everyone probably knows that just setting a ROAs target and hoping that Google ads will deliver that return on ad spend is probably not a good idea. That is why you always have to keep testing and keep learning and in this episode, I'll reveal to you a good strategy to find out what the correct Return on Ad Spend target should be for your Google Ads account. Let's dive right in. Hello and welcome back to Google ads. Unleash guys. Hope everyone is doing fabulously this week. This one's pre recorded because I'm in the United States right now enjoying a few cocktails in Miami when this comes out. So so I'm very much looking forward to this, but up until then, I want to tell you about something that happened to me a few weeks back, which has triggered me to do this episode. So I'll be honest, I don't do enough of this, and we've recently done a lot of training ourselves in this department. But nevertheless, I'm going to tell you how important this is today, and I'm also going to tell you how to go about it, and it is how to choose the right ROAs targets for your campaign. So typically, what we do is we don't ever really change ROAs targets too much in the agency. The reason for that is, is that with the volumes that we play with, we don't really want to be change in bid strategies really too often. Because, of course, they should be very often, like kind of set in stone, if you like, and you don't want to play around with them too much, because it's one of the independent variables. If you change that on ongoing basis, you just confuse the algorithm, and you actually make things worse. It's much easier to control sort of performance through the volume of spend that you pop through ad accounts. This is my opinion, and this is just a tried and tested thing that we have found. Nevertheless, setting the right draws target is very important. And recently. Just get back to the anecdote. The following thing happened. So I was in a one to one coaching call with a with a, like, a, how should I say no, it's not a client, but, like, what's the opposite of a mentor? You know what I mean, someone who comes and learns from me, someone who's being coached by me, and this person has a very, very successful brand, which through which they grew, first of all, through meta hats and then organically selling hats. So any kind of hat you can think of, from, you know, an NFL hat or something, from from an NFL team to whatever they sell the right hat for that. So Google is a fabulous, fabulous channel, which they've just never really done anything with up until this year. And I taught them how to do that properly through a nice, sort of bucketed strategy using mainly shopping. And now I think they're happily spending five digits a month easily on the channel. But one thing, I'm just gonna call him Joe. Now, his name's not Joe, but Joe sort of asked me one thing, and it kind of stumped me a little bit. And he said, Jeremy attribution, some nightmare. I know the conversion tracking setup properly, and Google ads is telling me X, Y and Z is my ROAs. But then I look at traceify, and it gives me different ROAs. And then also, although I've got the same campaign set up running in like brand and non brand split in those and those and those in those countries, I'm seeing different levels of revenue, and I'm just totally confused of what the right ROAs target should be across all of those different nations with, you know, there's different competitors, there's different all of the campaigns work differently. And I told him about the air. We don't you should just choose one ROAs target, you know, based on the margins, etc, of the product. All the products have the same margins. It's pretty easy to sort of determine what a good return on ad spend should look like at Five 10% EBITDA. But he said, all of it is working differently, and I don't really know how to optimize that like, Well, how do I choose the right ROAs target. And I said to him, Joe, the answer to that is not very straightforward, because in this instance, what you've done is exactly the right thing. You've gone into your business and you've analyzed, hey, this is the cost of goods sold. This is tax, blah, blah, blah. This is the amount. To spend that, I the return on ad spend that I need in order to be profitable, right? In this case, it was something like 3.3 or something like that. And he set all of his campaigns like three 350% ROAs. And to me, that's actually a pretty good idea, right? And based on that, he can, he can, in fact, sort of do, do his job. But the problem with ROAs, which, as we all know, is revenue divided by ad spend, is that it sounds and looks great, or sounds simple and it looks great on dashboards. And it does right because we can see and that's what we actually work with. And I don't think it's a it's a bad metric, either, like a lot of people always try to sound cool by art and look at ROAs and so on, it is a very helpful metric to discern in platform what is working and whatnot, and to judge performance onto a certain degree, but it ignores two major truths, that, first of all, not all revenue is actually caused by your ads, which is why with Joe, the performance was so different from country to country, and the revenues were so different. And ROAs doesn't actually account for profit, right? For instance, costs may be a little bit different from from country to country consumer behavior, right? Because consumers may be searching completely differently in country to country, or there may be other competitors. And it also doesn't account for costs, other costs that may be implicit from sort of campaign type to campaign type, or from country to country, or between brand and non brand, right? So although his sort of campaigns would deliver in a 350% ROAs in all the various countries, everything was looking good. He was still having quite widely different performance differences after he factored in, you know, product costs, of course, the cost of our consultancy, and so on and so on. And he asked me, How do I fix that, Jeremy, because there's no real easy way to determine maybe I need, actually an artificially higher or lower ROAs, maybe even lower ROAs, because he had the suspicion that whilst the bids that we had now set were good for quite a few countries, right, the 350 which we blanketed, But everywhere, he had sort of the feeling that probably this was not aggressive enough in certain countries, but certainly too aggressive in other countries where we couldn't really hit that return on ad spend, consistently with what We actually seen Shopify, right? What, what, what is in the bank at the end of the day, and at this point, that is where the concept of incrementality comes in. Okay? I've talked about incrementality now in various, in various podcasts, right? I've had muscle small on who trained our team on it. Fantastic podcast. If you haven't listened to it, go back and listen to it. I've talked about it a few other times now, but today I really want to sort of dive into a few resources that I found and been reading on quite a lot. And this is something I want to increasingly start testing more. I've already been doing this now in the past few months, but even more now in the new year, once, once, all the craziness of q4 is gone away. And I want to tell you today about how you can calculate incremental ROAs, or powers, for that matter, for your campaigns and how you can use geo based incrementality tests to adjust ROAs targets to answer the question that I have just put that Joe posed to me, what is actually the right ROAs target for the campaigns that I'm running, maybe a quick reminder of what incrementality is. So incrementality tells you how much of your ads actually generate the real revenue, and how much of that revenue does not come from people who would have bought anyway. Okay, so you may in your platform see this 350% ROAs, but it doesn't actually tell you how many of those people would have bought anyway, because, let's say branded traffic is typically a campaign type which is not very incremental, right? Because people know your brand, search for your brand, they would have clicked anyway on the brand search. Ad or potentially a, let's say,
a an organic search result, right? So traditionally, this type of ad has very low incrementality, whereas, for instance, top of funnel driven advertising measures such as YouTube, demand gen or shopping, which is mid funnel, bottom funnel, have probably more incrementality, right? Because people would have bought because they saw and discovered those ads. That's the sort of reason that they bought. The thing is, with incrementality, it's quite an important concept, because the human mind and psyche is really, really complex, and oftentimes it's really hard to actually identify. Why has someone decided to buy something? Right? Sometimes people buy, let's say, an iPhone, because they like the blue color of the phone, right? That's they could have seen 50 different ads. It didn't. Maybe they saw the ads, but they didn't buy because of the ad. They bought because they liked the color of the phone, right? So it's impossible, or very, very difficult, to sometimes accredit advertising for that, on discredited for that. So how do we find this out, we run incrementality tests and then understand how we can actually adjust our our strategy to sort of to set the right target raw assets. Okay, so first of all, I want to break down incrementality by an example. Let's say, for instance, you want to measure the effectiveness of an ad, okay, you spend 1000 pound a month, and your shop makes, let's say, 10k a month. And you're, you know that this comes from a little bit of Google ads, advertising. This comes from maybe a few other things, such as repeat customers, etc, etc. And on platform, your Return on Ad Spend shows us five because you got a certain number of conversions. And let's say 5000 in conversion value, okay, so you could safely say, if you were to just believe it like this, okay, I got 10k revenue. I spend 1k in in ADS. I got a five extra ass because the conversion value says 5000 so my return on ad spend is five. Now if you suddenly turn those ads off, okay, and your revenue, your overall revenue from 10k would have dropped to, let's say, 7k right? Then you would have realized that, hey, that 1000 that I'm putting in every month is not actually generating 5k or 5000 as the ad platform shows, but rather it must be Driving only 3k in revenue, because clearly, that's what's been missing since I've been running the ads, right, since I've been stopping the ads. So in reality, Google isn't showing a 5x ROAs. The real ROAs is actually three, right? And that is where you can see that this is the actual incremental ROAs that your, that your that your ad account sort of runs. So now you can do hold out tests like that, which are pretty radical, right, in order to determine this. Or you could do a geo test to determine this as well, where I'm not going to go into the details, but essentially what you would do, let's say you target in Britain, you would be splitting up Britain or a good location that you could choose, such as, for instance, a part of England that you would choose as a holdout group. The easiest is probably a 5050, split right. Split it down the middle. There's many factors to consider. Seasonality could always be a factor that you the split that you made is not very good. There could be a million other factors that you need to consider to run a good incrementality test. That's why I go back to the episode and listen to that. But you could be doing that and then also determine the exact same thing. Let's say you split it down the middle, and you have 5k of revenue in Group A, where you spend 500 and then in Group B, you have also 5k in revenue, where you also spend 500 right then you would probably see a drop of 1500, in Group B, where you hold out 500 in ad spend and could make the same deduction that overall revenue must have gone down. So the actual incremental ROAs is only three and not five, as it actually showed the traditional ROAs in the in the ad platform. Okay? So when you do that, that's what I said to Joe, that's what you need to do in all of the countries, right, either through a full on holdout, or through a or through a geo test, you can actually calculate what very likely for all of the ad campaigns that You run in the incremental ROAs is, is what I've just explained. Now, Google actually has now some resources, which I will probably link with this podcast to give you a good understanding of what you should be setting your target ROAs is at at the moment, in this example, I've said multiple times now we've been spending 1k a month, and we've got, apparently, 5x ROAs, that is what our target is set To, okay. But in reality. Through the geo experiment, we found out that the ROAs is actually three. So how we calculate a calibration multiplier now that you need to set to your target ROAs is, is by taking the incremental impact that we've calculated, and that is the ROAs of three, and divide that by the attributed impact, that is the ROAs of five. Okay, so in our experiment here, we will have to now do this calculation, and it's pretty straightforward, three divided by five is naught point six. Now you actually have this correct multiplier that you can now use and set aside. This is now something that you found out, put write that down calibration multiplier and and take that later on. Now Joe was just, let's say Joe has run this experiment and is disappointed. Of course, we're taking out different ROAs targets. Targets here we've been traditionally having five. That's the ROAs he really wanted from his campaigns. That's the way he knows it's profitable, but it turns out it's actually actual, real, incremental ROAs is only three. I'm just keep repeating this, because it's difficult in the podcast to bring this across. Now his real wish, ROAs his goal, would have really been, I really need $5 back for every dollar I put in, because that's otherwise my or pounds. Otherwise, this doesn't really work for me. Okay, so his real incremental ROAs, goal is actually five, right? And there's real life is three. So we can now use those two different features to, in fact, calibrate is real life ROAs that he will now need to set in the ad account, which reflects what the real life incremental ROAs is that he wants. So again, his current ROAs targets would have been at 500 the incremental ROAs is 300 which we found out the calibration multiplier is not point six. And in order to have a goal of caliber of a of five, we would need to do the following exercise. We have to take that incremental raw scale that we found out and divide that by the calibration multiplier that we just calculated, which is no point six. So let's do this experiment. If we really wanted to increment a ROAs of five, we have to divide that by naught point six, which gives us an actual T ROAs that we need to hit of 833% okay. That is the actual ROAs target he needs to set in his ad account in order to achieve the real life increment, a ROAs of five that he needs in order to sustain his business the way he wants it to. And that is the real. ROAs target that he needs to choose for his campaigns.
Okay? So that's what we find out through geo experiments, right? So just to recap, he makes 10k he spends 1k a month. We do a hold out test. We realize that Google is not showing, not actually achieving a 5x ROAs like he set in the ad account in which he is shown in the ad account, but actually only a 3x so what we then do is divide the incremental ROAs by the ROAs shown in platform, which gives us a calibration multiplier, and then we set an actual incremental ROAs goal, which we want, divide that with a calibration multiplier, and that gives us the on platform T ROAs that we need. Okay, so that's what we've done. And this is something that you can do pretty easily in your ad account, in all of your ad accounts right now, which gives you, and the same applies the powers, by the way, right? So, but instead of tracking the revenue in the turnover, you would have to track the profit and the impact it has on that to do the same exercise, right? And this is some really powerful stuff, because what this does is it marries the real life impact of your ads are actually having where the positive or negative, in this case, the incrementality was less than 100% which is, in theory, bad, but nothing is 100% incremental. They are, of course, cases where it's more incremental than we think. This is very often with in poor in platform ROAs, which we very often see with demand gen or YouTube campaigns, but which actually move the needle in your overall baseline revenue right? Very often. This is, of course, not what we wanted, but this is what the reality is, right, and it helps you set the right bids, regardless of what your feel, is, your want is your needs are, etc, etc. There's a few things that you need to think about. Is how to run a proper geo test. For instance, volume is an issue. Sometimes you don't you were trying to test for something that has much too little impact on what you do. Or sometimes it's extremely hard to even measure what you want to do. Or sometimes the seasonality produces in a strange outcome, right? Sometimes you just chosen the wrong areas as geo test. Sometimes freak incidents happen that disrupt your your your geo test, etc, etc, etc. There's also other things that you need to think about when you set in your targets. Typically, I would never just bids more than 20% of the time. So in this instance, we found out we need to actually raise our ROAs targets from 500 to 830 in order to have our incremental ROAs goal of five. Well, the issue with that is, is, if you increase rawest targets this drastically at once, then you could anything could happen. Right? Your ads may stop spending straight away, or the efficiency that you now and achieve is maybe not even possible, or you sacrifice volume because your ads are much too conservative, suddenly, vice versa. If you drop roast targets aggressively, it could even go really bad, right? Like you could be spending crazy amounts of money without without following. So there's other things that happen in the auction competition changes their bids, which may have an impact on how your ads perform, etc, etc. Significant changes can also change who your campaign targets, right? So which also changes or changes results in incrementality. So sometimes, even though this is the best way of going about it, to find the best T RAS on platform for your incremental Return on Ad Spend which you want to achieve, sometimes, you will have to just accept that bid changes can be so unforeseen that they may have a completely different impact as desired, Right? So you have to retest, sometimes your incrementality tests. In order to keep your calibrations accurate, you have to understand that some channels sometimes sponge off each other, right? So this could pollute the outcome of what's going on. So which is why we would recommend in an ideal world, and Google actually recommend this as well, right that you keep your calibration multipliers which you calculate through running those tests fresh by retesting every three to six months. Every six months is probably best for most, most ad accounts, and through that, you can actually set the correct draw style. It. So what did I tell Joe now? What to do? I told Joe, listen in the new year when q4 is over, what you do is you actually split run those incrementality tests in all of your countries. Split it by 50% do geo hold outs? Understand what impact it has on revenue, understand what incremental ROAs very likely is actually happening. Take a calibration multiplier, and from that, you will understand what the best return on ad spend targets are for your campaigns. Wow, that was a lot to chew through, but I hope this has been really valuable for you. If you have any questions about this at all, always feel free to message me at Jeremy, at young and digital dot marketing. You can also send me a message on LinkedIn, Jeremy and Google ads. And if there is anything else, please just simply reach out on that note. I wish you a happy and productive week ahead, and I'll see you in the next episode.