All right, so let’s say you’re doing a Michigan Method or some similar style, you have a ton of ad-sets targeting the same people and they’re all on low budgets. We know that the learning accrues at the ad-set level, like that’s where all of this is happening. If you have 50 ad-sets and you’re getting 50 conversions a day from those ad-sets, that means every single one of those things has only seen one conversion, one positive and a bunch zeros. You can imagine how am I supposed to derive a pattern, or like a prediction, or a solid prediction about who is going to convert next on just one positive.
There’s not enough data. It will work for a while but there’s just not enough data for longevity. This is something the cannabis space has to ingest.
Facebook is conned like all right, well, I got to spend this daily budget tomorrow. I still don’t really have a better idea than I did when I started about who to send this to so we’re just kind of randomly deliver it. When you get to a certain point there, you need to kind of take your learnings and then now let the club do the work.
Okay, so in phase two, we’re going to move to a setup where we’re going to do less ad-sets. Instead of having a number of different ad-sets targeting the same people, we’re actually going to go almost the opposite way and we’re going to combine audiences into one ad-set. The reason we’re going to do this is let’s say you have 10 lookalike audiences, and they’re US look-alike audiences, and it’s all for the same offer, and all that good stuff.
From Facebook’s engineering point of view, the only reason to ever split those out into separate ad-sets would be if you’re going to bid differently for them. Next time when you’re going to want to campaign, you’re going to split out ad-sets. When you’re onto this scaling there, my challenge to you would be to think to yourself why am I splitting these out. Will I bid differently for them? If the answer is no then put them together.
The two things that this is going to do for you here that are going to help you kind of swim with the current related to the auction system and the machine learning is that going from 20 ad-sets to one, if we’re going from 20 ad-sets in stage one where we’re testing to one, we’re going to consolidate all those conversions to one ad-set. We’ll call that the juice. You’re getting all the juice into one ad-set instead of 20. That’s so important, especially for website conversion campaigns where the conversion rates might not be as hot. The difference between one a day and 20 a day is going to make a huge difference.
The other thing is, and this is the part that a lot of people in our industry will miss that’s really key is that if you have an ad-set with a tiny audience and let’s say you break interest up into different ad-sets, like one interest per ad-set, Facebook could be using that learning.
Chances are those answers are going to be somehow related, right? Some people are going to be in one or more of those interest groups because all the learning is happening at the ad-set level and all the reach is controlled at the ad-set level. All these people that would have been great candidates compared to the conversions you’ve gotten from one of your ad-sets, Facebook can’t even see them, unless you’re using expanded interest.
So, what we’re going to do there is we’re going to have better reach and availability in the auction. If I go from 10, 100,000-person ad-sets up to the same group, a million people, your performance should improve drastically because it’s kind of like a compounding benefit. The consolidated juice gives us a better confidence interval and a better idea of expected conversion rate. Therefore, we can predict better who’s going to convert. It’s like Facebook can now see a whole stadium full of people instead of just being in a high-school gymnasium, do you know what I mean? Now they can apply a probability to everybody.
Remember with a daily budget, they have to try to spend that money regardless of whose online especially if you’re auto-bidding. This gives you the best shot of your highest expected value, people being even in the auction, even showing up that day, and us being able to reach them.
Last week someone asked me if I believed that even by audience size, if the audience is too big, if they should split into multiple ad-sets or if Ithought audience size does not matter.
Well, I don’t know the 100% answer to that. I don’t know for whatever reason recently, and it might just be because of the competition in the auction and the competition on Facebook ads, in general, has gotten a lot tougher, that we have seen bigger audiences working.
We’ve done some testing where we had to scale as fast as possible up to $10,000 a day. We did it with no targeting because they already had 500 to 1000 conversions and so they used really big audiences. We’ve seen it in several cases, and then there’s some of the best campaigns that are 30 to 40 million and running for a long time.
That just shows the power of the algorithm I think. We’ve done it plenty of times where we’ve done it sort of by mistake even in testing mode where the interest for whatever reason didn’t catch.The power editor just deleted it for whatever reason, and it’s wide open to 130 million in the US, and it’s the best performing ad-set. Notice I’m saying ad-set here because, I mean, there’s a lot of data that shows that this machine learning happens via ad-set. It is by that 25 conversions in a seven-day period but you want more than that, as many as you can get, which is the reason why level two of scaling here is obviously to larger audiences, larger budgets so you can feed the algorithm positive data and let that machine learning work for you as opposed to you working against it. A lot of times this means not doing a whole lot. It means letting the algorithm do the work while you guys kind of sit back and be patient.
You have to have a good offer. Everything has to be close to perfect. You have to test this stuff upfront first. You can’t go right into this. You’re missing a whole step because you can’t go $500 a day, and you don’t know what’s going to work. You have to test smaller and then get larger. You don’t know what a good message is unless you actually test it to traffic.
It’s kind of like surfing. Let’s say you’re trying to surf and you’re trying to paddle into a wave. If you’re not in the right spot, if you don’t time it right or if you’re just a little bit too far off the shore, you’re just going to be paddling all day long. You’re never going to be catching any waves because there’s so much power into that wave.
What happens is there’s a lot of people are out there focusing all their time and energy in optimizing, and testing, and all this stuff. Instead, what they should be doing is focusing … I spent two days writing an ad and it usually works right out of the gate with zero testing. Now, of course, the more we add to that, the better it does as far as testing, but if you actually put the work in to creating offers that convert, good messaging, then sometimes it’s like are you stepping over a dollar to get to a dime.
If you’re a cannabis entrepreneur, you have to think about where is your best times spent. If you’re a solopreneur or a marketing director for a cannabis brand and you have other departments, sometimes you have to weigh those things.
I think the key is to understand how it works. If Facebook will work better with large audiences, it’s going to work way, way better if you have a great message and a great ad-copy. The fastest way to know which one of your messages works is to test them.
That is the other big key point here is if I can help you simplify your approach and spend a little less time on Ads Manager, which might sound counter intuitive, you can focus that time on things that I think have bigger levers. I think everyone would agree, like working on your follow.
Your copy, your messaging, your creative… everything, your offer, your backend, creating new products to increase customer value. That’s exactly how I look at it. We’ll do testing, and then once our ads are set up and they’re in a good place, I’ll get in there every few days and kind of check on how things are looking and make tweaks.
Facebook is not a day trading platform. It’s built to be easier to use. They want people to spend more money. They want us to spend more money. If they can make the platform better, and easier, and less maintenance, then they’re going to make more money and advertisers are going to be happy too.
This shouldn’t be complete rocket science. It’s so good to know how it works because the better you understand it, the better you’re going to be as an advertiser. But, on the other side of that realizing that this is built to help you. You’re not working against the platform. Once you find something that works, you shouldn’t be making tweaks every 15 minutes because it’s actually going to hurt you. You’re not giving Facebook enough time to do what it’s good at.
I think that a takeaway from this is that once you’ve dialed in that message, if the greatest copywriters can get it right, do it right out of the gate. You have to really know your audience to be able to get it right out of the gate.
In most cases, we don’t get it right, right out of the gate. We fail a lot. We fail 70% of the time or 80% of the time if we’re not having a very good day. The point is that once you have that, then start thinking about how you can do less to get more in the algorithm by leveraging larger audiences, combining those audiences, larger daily budgets, and then even doing some bidding manual optimization.
The point is that inactivity in an ad-set, or in a campaign, and customer clients, and one particular last two weeks, we didn’t actually pause an ad-set that had spent money over a two-day period. I explained to them inactivity in the ad-set and in the campaign does not mean inaction. Inaction means we are looking at it and we’re making a strategic decision to let the algorithms smooth out those inequalities, those ups and downs, because ultimately, we’ll win.
I’ll see our clients and they’ll post. It’s like, “Launched an ad an hour ago. Only 15 people have seen it. What’s wrong?” We don’t even look at our ads for three days at least, sometimes five because you’re going to start making changes off of something that hasn’t had time to do what it’s supposed to do.
It’s emotional, it’s money that’s being spent. If you’re spending thousands of dollars a day, if you see inaction, it might actually mean that your agency or your ads manager, whoever it is, or yourself is asleep at the switch, but that’s not necessarily the case. What we’re doing is we’re trying to let the algorithm do the work here because the algorithm is smarter than all of us.
Simplify and let the algorithm do the work. Just remember that one thing. Every time you go in there and you mess around with the settings and the ad-set or change something, it actually has to recalibrate. It is going to hurt you. It’s not just that you’re wasting time but it is hurting your ad-set performance if you’re doing that. Do less, that would be number one.
Number two, yeah, let the club do the work like we talked about, test it out. I will say that a lot of people who are maybe from the older school of Facebook advertising when they hear this they’ll say, “Well, I’ve tried that. I’ve done that before. It doesn’t work. You can’t do big ad sets, big budgets.”
Well, there’s another phase to this and we’ll probably talk about it on another post but you can use everything we talked about here going with bigger ad sets. That’s what we’re doing right now for some clients with automatic bidding. When you’re starting to get up really high on the daily budgets, there is another step to avoid getting your budget blown, but that’s a whole other story.