Full transcript
0:00One of the brands we took on was doing
0:01about $6000000 a year. A few months
0:03later on the same ad spend, we increased
0:06revenue by 45%. We didn't give them a
0:08bigger budget, we just changed where
0:10every dollar was going. Because right
0:12now, since Meta's Andromeda update,
0:13everyone is telling you the same thing.
0:15Pump out 15, 20 new creatives and let
0:18the AI find your winners. And that's
0:20fine if you have the budget to feed it,
0:21but if you're spending $30 a day or at a
0:23smaller scale than these big companies,
0:25all that does is spread your money so
0:27thin that no single ad ever gets enough
0:29to prove anything. So, in this video,
0:31I'll show you how we actually scale
0:33Facebook ads on a small budget by
0:35forcing every dollar into ads already
0:37working. Instead of spraying it across
0:3920 new ones and hoping one hits.
0:43On my screen, you've probably heard some
0:44version of this advice over the last
0:46year. Create more ads, more concepts,
0:48more hooks. Giving Meta more variety or
0:50different concepts to let the system
0:52decide what actually works, fueling
0:54Andromeda. And the idea behind that is
0:56not completely wrong. They are right. In
0:58simple terms, Meta is using the creative
1:00itself as part of the targeting. It
1:02looks at the image, the video, the copy,
1:04the people engaging with that ad, and it
1:06uses that data to try to match it with
1:08more people who are likely to respond.
1:11So, yes, more creative variety can give
1:13Meta more opportunity to find a similar
1:15buyer. Some buyers engage with the UGC,
1:18others engage with maybe a more
1:19lifestyle infographic image. But the
1:21part that always gets left out is that
1:23every one of those ads needs enough
1:25budget to actually fuel that Andromeda
1:28flywheel. All of these ads need budget
1:30to place out in the market, get the data
1:32signals, and then allow Meta to keep
1:34deploying it to find your ideal
1:37audience. And this strategy works for
1:38those people spending $1000 a day, $5000
1:41a day, or upwards of $50000 a day. And
1:44it's exactly what they should be doing.
1:46But it's just wrong for smaller accounts
1:47who are maybe just getting started and
1:49don't have the capital to actually spend
1:51thousands a day. And if they do try that
1:53strategy, you'll see down here with
1:55smaller budgets, it doesn't really work.
1:57A handful of ads will steal the spend.
1:59This one got $12, $6, $3, and the others
2:02are getting pennies. Never able to prove
2:04themselves in the market and never able
2:06to let the algorithm actually work as
2:08it's intended. And if you look in your
2:10account right now, you can probably see
2:11that something is very similarly
2:13happening in your account. Maybe a
2:15couple of the ads are getting 80, 90% of
2:17the budget, and the rest are only
2:19getting dollars. Not able to actually
2:21fund the growth, not able to actually
2:23fuel performance, and actually weighing
2:25down the account average. And
2:27unfortunately, this structure doesn't
2:28work when you're not able to feed it
2:30enough data. You won't see the results
2:32you're hoping for. And no, the answer
2:34isn't you just need more creatives. With
2:36smaller budgets, you actually have to do
2:37the opposite of that advice. We take
2:40control of where money goes, and that
2:41starts with finding what actually works.
2:43And if we pull up this account here, you
2:45can see it's a brand new client. They
2:47came to us, no history in the ad
2:48account. You can see everything here is
2:50completely empty all the way up until
2:51March 13th, which was our first start
2:54date. And they were a brand new startup,
2:55you know, they had limited budget, under
2:57$100 a day, and they told us, "Hey, we
2:59want to make sure that we can grow, have
3:01a roadmap, actually understand what's
3:04working, understand what's not working,
3:05and more importantly, keep our
3:07profitability in mind." And so, if we
3:09look at the first 30 days of our service
3:11with them, that's exactly what we did.
3:12And we started with something called the
3:14creative test. So, what that means is,
3:17well, before I even talk about targeting
3:19or before I talk about the product page
3:20or before I talk about price incentives
3:22or shipping rates or shipping thresholds
3:24or anything like that, I have to make
3:25sure that the ads we're actually using
3:27and leveraging with this client are top
3:29performers, are ads that the market
3:31actually wants to see. And more
3:33importantly, we're going to make sure
3:34that we cut the ads that the market
3:36doesn't want to see, ensuring that we
3:38remove the fat from the account, and
3:40overall keeping the average return on
3:41investment for this account as high as
3:43it possibly can be. And so, the very
3:45first order of business when working
3:46with any new client or even phasing into
3:48an existing account is making sure that
3:50creative assets are where they should
3:52be. And so, we start with a creative
3:54test. It was the first campaign that we
3:56launched inside of this brand new ad
3:58account. And you can see, fun fact, as
3:59we move up our stairway and go through
4:01our process with every client within the
4:03first 30 days, you can see that results
4:05get better and better and better. And
4:06that's not just because of, you know,
4:07some campaign hack, that's because we're
4:09able to take the learnings from test
4:11number one, apply it in test number two,
4:13take the learnings from both of those
4:14tests, apply it in test number three,
4:16and overall get more and more efficient
4:18because we begin to leverage only
4:20winning assets while cutting the losers
4:22or the fat to make sure, again, that
4:24return stays high. But, you can see
4:26here, we start with a creative test.
4:28This is a very simple structured
4:29campaign. I can go more into how we
4:31build this in another video, but
4:33essentially it's a CBO campaign where
4:35the budget is on the campaign level.
4:36It's broad targeting because we don't
4:38want to add in an audience pool to add
4:39another variable to our testing. Right
4:41now, what I'm concerned about are the
4:42creative media assets. And here is where
4:45you can see, we tested 16 ads with this
4:48client. We wanted to figure out what
4:49were the three to four best ads in here,
4:51so we can cut out the 13 or 12 that were
4:54just weighing the account down. Now,
4:55usually what would happen is you would
4:57take all 16 of these ads and you would
4:59say, "Hey, let's let Andromeda figure it
5:00out. Let's put all of them in the
5:02campaign. Let's put our max budget on
5:04that campaign and over time Facebook
5:06will spend on the winners." But, what
5:08you would see happen is one ad is going
5:10to get out of this total $586 spend, one
5:13ad would probably get $450, another ad
5:15would get $50, another ad here would get
5:18$20, and all of these would get less
5:20than $10 all the way down till they're
5:2120 cents or even lower. And the issue
5:24that I have with that is that those ads
5:26that have 20 cents of spend, I don't
5:27believe that they were ever out in the
5:29market enough or a long enough time to
5:32prove themselves to tell me that they
5:34actually aren't good assets. And the
5:36thing is, when we've done our AB test,
5:38as I'm going to show you here, sometimes
5:40we find that the ads that Andromeda does
5:41not favor are actually the winning ads,
5:44they're the golden nuggets in the
5:45account. And when they're actually able
5:47to get volume behind them, they tend to
5:49be top performers. Now, this doesn't
5:51mean that every underutilized ad is
5:53going to be your top performer. You need
5:54this clear AB test. And how we do that
5:56is, well, I went to my team and I said,
5:58"Okay, if we want to be able to identify
6:00a top performer, what do we have to do?"
6:02Well, we have to get market signals,
6:04right? We have to put these ads out into
6:05the market, get impressions, get data on
6:08what the market says about it. And so we
6:10said, "Okay, well, what's a reliable
6:11amount of data? We don't want to run
6:13this test for thousands of dollars. We
6:14want to find our winners as soon as
6:16possible and for as low cost as
6:18possible. And so we said, well, it
6:19depends on the client's budget, right?
6:21Because if we have about $30 a day, an
6:23average CPM is about $28, $30. It
6:26depends, like if we're going to be
6:28running 16 ads, it'll probably take 16
6:30days. We don't really want to do that.
6:32So if a client has more budget, we can
6:34say, "Okay, let's maybe do 1,000, 2,000,
6:373,000 impressions just to really get
6:39enough data." Now, the reason for this
6:40is I like 1,000 impressions to be the
6:42absolute minimum that we go to. And
6:44because it's essentially a flash in the
6:46pan of what the market believes about
6:48your ad. Now, it's not going to be the
6:49most accurate result, and that's because
6:511,000 impressions is, again, only a
6:53flash in the pan. Imagine if you have a
6:54neighborhood full of 1,000 houses and
6:56you only survey maybe 10 of those
6:58houses, you're not really getting the
7:00average neighborhood sentiment or the
7:02average neighborhood opinion on
7:03something. You have to talk to 100, 500
7:06of those houses. And so it's almost the
7:08same exact thing here. We want to talk
7:09to as many people as we can, get their
7:11inputs on the assets that we deployed to
7:13them, and then from there understand the
7:16metrics and be able to cut the fat from
7:17the account and focus on our winners.
7:19And so for this account here, because
7:21they had about $80 a day in total
7:22budget, we went with anywhere from 2 to
7:243,000 impressions in total to really
7:26give us good market information on what
7:28they think about these ads. And so what
7:30I do here is I let the ads just run as
7:32is, and I keep an eye out for when they
7:34are going to hit about 2 to 3,000
7:36impressions. And then I manually turn
7:38them off before they get over 3,000
7:40impressions, so then other ads will have
7:43the ability to get the spend. This is
7:45basically forcing Andromeda and forcing
7:47meta to now spend on these other ads
7:49that weren't getting the spend in the
7:50first place. And so, now by the end of
7:52all of this test, it may take a week or
7:54so, you're going to be able to have all
7:55of these ads hit 2 to 3,000 impressions
7:57or at least 1,000 impressions. They're
7:59all going to be turned off. And now,
8:00what you're going to have is a really
8:01cool scorecard here. You're going to be
8:03able to look and see, okay, they've all
8:05been out in the market for the same
8:06amount of time. What are the differences
8:08of supporting metrics? And so, what I'm
8:09looking at are CTR all, CTR link
8:12click-through rate, and CPM. Now, if I
8:15sort by all of these metrics, you can
8:16see that we have some with a CTR all of
8:186.5, 6%, which is really, really
8:20healthy. And the important part of this
8:22test is we're also able to identify ads
8:24that are on the lower end of the
8:26spectrum, basically giving us a 2%
8:28click-through rate. Now, the reason why
8:30this is important because if we're
8:31taking 2% versus 6%, that's a difference
8:34of a three-times engagement rate. And
8:36so, we probably want an ad that engages
8:38with our audience at a three-times
8:40higher rate. That means three times more
8:41attention, three times hopefully more
8:43link click-through rates, and three
8:45times more opportunity for purchases,
8:47which is the end goal of this client.
8:48CTR, again, is just the tip of the
8:50iceberg. I'm looking at all of these
8:51different metrics. Some of these other
8:53ads brought us a almost 3% link
8:55click-through rate, while others almost
8:57a 1%. So, again, three times the
8:59opportunity for sales. And I'm also
9:00looking at CPM because different ads
9:03will give us different CPMs. We can
9:05spend the same amount, or actually not
9:07spend the same amount. We can get the
9:08same amount of impressions from two
9:10different ads. This one had to spend $36
9:13to get in front of 2,000 people. This
9:15one had to spend over three times the
9:17amount just because Facebook gave it a
9:19higher CPM. And so, that tells me right
9:22there, it is probably just not a
9:23cost-effective ad for right now, right
9:25for the beginning of an ad account. We
9:26want to make sure that we can get in
9:28front of people at a cost-effective
9:29rate, that it's engaging at a higher
9:31rate, that people are actually link
9:32clicking through, and then they have the
9:34opportunity to be on the site to buy.
9:36Now, these are three supporting metrics
9:38that I look at, but of course, I also
9:39look at supporting metrics in the
9:41funnel. I look at add to cart rate,
9:42checkouts initiated, overall purchases,
9:45what ad drove the highest return on ad
9:47spend. Now again, the reason why this
9:49test is important is because you can see
9:51all of these ads were out in the market
9:52for the equal amount of time or very
9:54close to equal amount of time. You can
9:55see that some of these ads got a 11, 10
9:58times, seven times return on ad spend
10:00when a lot of these, there's hundreds of
10:01dollars spent down here on different
10:03assets that resulted in no sales and
10:05sometimes not even any buying behavior.
10:07And so, this is a very important key
10:09because imagine if we kept leaving it up
10:11to Andromeda and they would maybe favor
10:13one of these ads, who knows, right? And
10:15if they did, how much money would be
10:16bleeding silently from our account? We
10:18want to make sure that every single one
10:20of our dollars, especially at a lower
10:21spend, especially at a starting stage,
10:23goes to effective ads. This is where you
10:26create margin. This is where you create
10:27return on ad spend. This is where you
10:29create profit and you're able to then go
10:31to the next stepping stone because this
10:32fuels maybe a next inventory order.
10:35Maybe this fuels more learning. This
10:36ultimately gives you more time, right?
10:38Because if you're getting revenue in,
10:40you can have more time in the market.
10:41And so, right now, the goal of this test
10:43is to identify what are our winners and
10:45what are our losers and make sure we can
10:47identify and capitalize on the winners
10:50for the next test. And when I say a
10:51winner, I do not mean an ad with a five
10:53times return on ad spend after spending
10:55just $12. You have to let this test run.
10:57I want to find the ads that actually
10:59finish the impression limit and produce
11:01the behavior we care about. I know it's
11:02hard to turn off a 10 times ROAS ad just
11:05because it hits the impression limit,
11:06but this is purely just a test campaign
11:08that we need clear results on. If it's a
11:10winner, then don't worry because we'll
11:12be running it again in the very near
11:13future. So, usually, I'm just trying to
11:15build a short list of two to five real
11:17performers. I still look at the
11:19supporting metrics, the CTR, link click
11:21through rate, CPM, cost per landing page
11:24view, cost per purchase, return on ad
11:25spend, but this is not a full data
11:27breakdown. On a small budget, I need a
11:29reason for every active ad to be there.
11:32And once I know a few real winners, the
11:34next move is the one a lot of brands
11:36with small budgets don't actually want
11:37to make. Now, this sounds obvious, but
11:39it's usually the part brands resist.
11:41They think that reducing the amount of
11:43ads means that they're shrinking their
11:44account. But, on a small budget, every
11:46underperforming or underfunded ad is
11:49competing with a live one for the same
11:51limited dollars. Remember, you don't
11:52have thousands of dollars a day to spend
11:54on this. You are not spending less when
11:56you cut the fat. You're funneling your
11:57dollars to exactly what performs.
11:59Putting it behind fewer, better
12:01creatives. So, the account may look
12:03smaller, but the signal becomes stronger
12:06and the money becomes more concentrated.
12:08Now, what I'm showing you is an account
12:10starting from scratch, but you can also
12:11do this exact process if you're already
12:13spending, generating sales, and just
12:15want to maximize returns, making the
12:17engine more efficient, even with larger
12:19budgets exceeding thousands of dollars a
12:21day. We worked with a brand doing around
12:23$6 million of revenue that had over 100
12:25creatives in the mix, a usual structure
12:27at that kind of scale. There was plenty
12:29of concepts,
12:30styles, hooks. And I remember the
12:31founder told me, "I don't want you to
12:33get better results just by increasing
12:35our ad spend. I want the same exact ad
12:37spend, but reduce our cost per purchase
12:39and improve our return on ad spend."
12:40After a quick audit, I saw the issue
12:42immediately. The budget was being spread
12:45amongst all of those assets, leaving the
12:47top performers with only a small
12:49percentage of the actual daily ad spend.
12:52They had good ads, but also had 70
12:54others weighing down the account. They
12:56thought variety was needed, and at that
12:58stage it is, but there is a very clear
13:00difference between variety and
13:01underperforming assets. We narrowed all
13:04of that variety and all of those
13:05concepts down to our top 30 ads, and we
13:08focused the ads around what was actually
13:10performing that have already proven
13:12itself while cutting the fat. We did our
13:14process, and in the following months,
13:16revenue increased by 45% without
13:18spending a dollar more, and that extra
13:20revenue allowed them to finally scale.
13:22And we worked with them for about 15
13:24more months, getting them up to $35
13:26million in revenue. That's a five times
13:28growth at a seven to eight figure level.
13:31And I'm not saying that the ads were the
13:32only reason for their growth, but
13:34removing the fat and focusing our ad
13:36spend on what was actually performing
13:38gave more breathing room to the account,
13:40allowing the founder and the rest of the
13:41business and the team to now be able to
13:44focus on new initiatives, new products,
13:46expand to new regions, and ultimately
13:47make better decisions for the business
13:49because they weren't just above water
13:51with their ad spend. And this is the
13:53process in our company when we work with
13:55clients. Establish a baseline, remove
13:57what isn't working and pulling overall
13:59average down, and start our next test
14:01from already proven concepts, allowing
14:03us to move down river, making sure that
14:05every dollar goes as far as it can. And
14:07we're able to do this time and time
14:09again with current client accounts, no
14:10matter the size. This business up 33% to
14:132.3 million from last year, same ad
14:16spend. We're just now putting the
14:17dollars towards more efficient assets.
14:19This company here, $500,000 a year, a
14:22little bit smaller of an account, but
14:23almost up 200% same ad spend as well.
14:26And I want to stress that it this isn't
14:28some magic trick or CBO versus This
14:31is actually just taking back control of
14:33where every single one of your dollars
14:34is going. Now, if you're looking at your
14:36own account, thinking you have no idea
14:38what ads are actually giving you the
14:39most leverage, well, that's the exact
14:41thing my team does for brands every
14:42single day. If you're running meta and
14:44the spend just isn't turning to growth
14:45like you want, there's a link below to
14:47work with us. If you'd rather run it
14:48yourself, good, stay with me because
14:51this next part is where small budgets
14:52leak the most money. Once I identify my
14:55winning assets in our CT, I graduate
14:57that into our next campaign, which is
14:59called a LT here. Now, this campaign is
15:02very unique because we have our winning
15:04assets, right? We know what gets a
15:05click, we know what's cost efficient in
15:06the market, we know what leads to click
15:08through. Now, the next variable that
15:10actually makes the most sense is, well,
15:12where do we take that user, right? We
15:14want to be able to control the landing
15:15page. We want to be able to see what
15:17landing page actually influences more
15:19bounce rate, which one has a higher add
15:21to cart rate, which one leads to a
15:23better checkout process and less overall
15:25drop off? So, I move forward into a LT,
15:27which is another very simple campaign.
15:29Now, what this is is one campaign and
15:31now I have multiple ad sets and these ad
15:33sets are different based on the landing
15:35page I want to use. I'm going to use my
15:37winning ad from my creative testing. You
15:39can see all of these have the same image
15:41for winning ad. And so, my media is not
15:44a variable anymore. The variable that I
15:46want to test is the landing page. Now, a
15:48lot of the times it may sound good on
15:50paper to say, "Well, if we're showing an
15:52ad for a t-shirt or a coffee mug, we
15:54need to take people directly to that
15:56coffee mug page. There's no sense in
15:58taking them and having them search
15:59around." Well, in concept and in theory,
16:01that is correct. But, the thing is I've
16:03seen time and time again that sometimes
16:05other pages influence buying behavior.
16:07So, for example, the product page of
16:09that coffee cup might just be a
16:10description, no reviews, add to cart
16:13button. This may work for someone who
16:14has high intent, who's ready to buy.
16:16But, a lot of your traffic, if they're
16:18cold traffic audiences, are not at that
16:20stage yet. They still need a little bit
16:21of credibility. They need social proof.
16:24They need to see why this product is
16:25valuable to them. So, sometimes the home
16:27page actually has assets that the
16:29product page doesn't, which leads to
16:31higher overall conversion rate. So, this
16:33is why we want to AB test everything.
16:34For this client specifically, we tested
16:36our winning ad going to the home page,
16:39to the collections page, to product page
16:41with these smaller variant of the
16:43product, product page now with these
16:45larger variant selected, just to see if
16:47we can influence a higher AOV. But, of
16:49course, as you can see here, this led to
16:50zero sales. Maybe price point and seeing
16:52that high price point from the first
16:54time they visited the website was
16:56actually a deterrent. And so, this is
16:57something that we learned through this
16:58test. We took people to the featured
17:00page, which showed credibility and
17:02featured on and, you know, platforms
17:04that this client has been on. And also a
17:06unique landing page that the client
17:08personally made for their persona,
17:10talking about pain points that they may
17:11have and why this product was valuable
17:13to this specific demographic. And so, it
17:15was very different than the original
17:17product page. Now, what I'm looking at
17:19is I want to make sure each one of these
17:21ad sets has equal amount of budget per
17:23day. Now, this is how we control it,
17:25right? Cuz now we can see that having
17:27these all spend the same amount of
17:29budget, we can see the difference of
17:31buying behavior. And if I sort by return
17:34on ad spend, it looks like the unique
17:36landing page actually resulted in
17:37healthy add to carts, more people moving
17:40through the funnel because I know that
17:41this featured page and smaller variants
17:43of the product page actually had more
17:45add to carts, but there was actually
17:47some resistance in the funnel. The
17:49unique landing page had less overall
17:51resistance and an extra sale. So, this
17:53tells me maybe over a long enough time
17:55horizon that the unique landing page
17:57would probably be the better option for
17:59us to choose. Now, imagine if we just
18:01started taking everyone to the homepage
18:02just off of because we never tested
18:04this. We would likely have overall half
18:07the add to carts, less overall
18:09purchases, and maybe even less than half
18:11the return on ad spend. So, this isn't
18:13again like some CBO versus or O
18:15Andromeda trick. This is controlling
18:18where the budget goes and understanding
18:20that every variable matters even down to
18:22the point of the URL that you use on
18:24your ads. We want to make sure we have a
18:26solid structure and learning around this
18:28for us to be able to move on to the next
18:29stage because once we know what ad to
18:31use and where to take them, now we can
18:34focus on who do we target with these
18:36winning assets. And once I have my
18:38winners, I simplify the structure around
18:40them. That usually means fewer
18:41campaigns, fewer ad sets, and fewer
18:43active ads in most brands want to run.
18:45And I'm not saying that every account in
18:47the world should use one campaign with
18:49one ad set. I'm saying that the
18:50structure has to match the amount of
18:52money available. So, if you're spending
18:54about $30 a day and money is being
18:55divided into four different campaigns,
18:5710 ad sets, and 20 ads, the budget is
19:00already gone before you could even do
19:02anything. And so, the next campaigns
19:03that I launch is an ASC, so an advantage
19:06sales campaign, and also interest. So,
19:08this is basically leveraging we know
19:10what ads, we know where to take them.
19:11Now, let me try some interest targeting
19:13to figure out who I want to target with
19:15these winning assets, but also I'm not
19:16forgetting about Andromeda, right? I
19:18want to leverage the algorithm. I want
19:20to leverage the machine that they built,
19:22the brain that they built, and say,
19:23"Hey, I have the assets I want you guys
19:25to use. I don't want to give you 16
19:27creatives and have you try to figure it
19:29out. I have the top four creatives you
19:31can see here. We chose four creatives
19:33here and not just the one. We wanted to
19:36pick our sample three to four winning
19:38assets from our CT. And we said, "Hey,
19:40we found the assets for you. We even
19:42found the URL that we want to use on
19:43this campaign. Now, we want you to
19:45leverage your algorithm to help us find
19:47buyers." So, we're almost making it less
19:49complex and we're leveraging the part
19:51that's really, really strong about
19:52Andromeda. And so, this campaign here,
19:54and keep in mind guys, this is our first
19:5630 days still, right? This isn't 3
19:58months down the road and learning and
20:00building data and yada, yada, yada, all
20:02this spend. No, like within our first
20:04month, we have campaign spending $500 in
20:06total and getting almost 6.7 times
20:09return on ad spend back. But, I also
20:11want to be able to see, well, can I
20:12target a little bit better? What if we
20:14actually hone in on like who exactly is
20:16our persona? So, the algorithm and the
20:18pixel could actually learn maybe a
20:20little bit on where we want to direct
20:22our attention. So, you can see here I
20:23have climbing, mountaineering, camping.
20:25This is a outdoors kind of brand. When
20:27we were able to target these audiences,
20:29we're able to get in front of our ideal
20:31persona with the unique landing page,
20:33with ads that they actually care about,
20:35and now get a 16 times return, eight
20:36times return. I don't want to boost
20:38these numbers cuz it's still very early
20:39spend, but you can see how within our
20:41first month, we're not at a two times
20:42return and learning. We're actually
20:44moving through the process, we're
20:46understanding what works, we're actually
20:47like having these internal discussions
20:49with the client and saying, "Hey guys,
20:50like this certain photo actually works
20:52for your brand and this video. Can you
20:54maybe make some more like that?" And
20:56these are actually what didn't work.
20:58These assets, maybe this type of photo
20:59didn't work. A product image style ad
21:02didn't really work. So, let's move away
21:04from those and let's work on what
21:06actually your market cares about. And
21:07hey, your unique landing page that you
21:09made was a home run. What if we make
21:11another one for a different audience
21:12persona? How do we build off of this
21:14momentum to actually get better and
21:16better results? And so, this isn't the
21:18end of the road. You're actually
21:19learning instead of just saying, "Okay,
21:21let me set up one campaign. Let me let
21:23Andromeda do everything." And then from
21:25there, what do you learn? You learn
21:27where it spent the most money, and maybe
21:28where you got a two times return. Like,
21:30you need to make sure that you
21:31understand what's happening so you can
21:32grow the brand and be in control of the
21:35return on ad spend, and more
21:36importantly, the profit. Now, I think
21:37it's important to note that I also don't
21:39really crazily raise the budget at this
21:41point. Just because this is getting a 16
21:42times return, if you've ran ads in the
21:44past, you kind of understand that. But,
21:46I don't take an ad that was doing a 16
21:48times return and immediately force it to
21:50carry $150 tomorrow just because one day
21:53looked good. If you've ran ads before,
21:55you understand that performance doesn't
21:56scale one-to-one. So, I want controlled
21:59increases. Maybe at this point, when the
22:01client's getting a five, six times
22:02return, I can say, "Hey, do you want to
22:04add 20 more dollars a day?" With that
22:06budget, I can launch another audience,
22:08find something that gets us close to
22:09that eight, 10 times return that we're
22:11seeing with other audiences. Or, at this
22:13point, if they also have more creatives
22:15that they want to test, maybe a batch of
22:1610 more new creatives, I can say,
22:18"Great, we're going to keep our normal
22:19campaigns running as is to not disturb
22:22the current performance that we've
22:23built, but we're going to just restart
22:25our CT on the side." This is why it's
22:26important to have it on a side campaign
22:29on its own, so you can always go back to
22:30it. And then now, when you launch your
22:32new ad batch, you can compare it to your
22:34original, and you can see did anything
22:36from the new batch outperform our
22:38current assets? And if they did, great,
22:40phase them into your main campaigns and
22:42allow them to also get budget while
22:44cutting the now new fat, which is maybe
22:46that first batch of creative. But, if
22:48those new creatives in your CT that you
22:50relaunched didn't outperform what is
22:52already running, then now you know
22:54better to not spend more money on them.
22:56You know better to turn them off in the
22:58CT, and you know to keep moving forward
23:01with your initial batch because they
23:02just get better results at the end of
23:04the day. And this is how the flywheel
23:06should work on a limited budget. You
23:08graduate into volume as the account
23:10grows. You don't start with volume just
23:12because the account can afford it. And
23:13there's one more lever to make a small
23:15account punch way above its weight and
23:17it has nothing to do with the ads.
23:18Everything we've discussed now is purely
23:20ads, audiences, landing pages,
23:22everything to get people to the website
23:24and convert. But we have to remember to
23:25actually look at the supporting metrics
23:27in the funnel. I look at where the
23:29website is losing people. So I'm going
23:30to sort by what we were running with our
23:32winning assets and be able to look here
23:34and say, "Okay, what are these funnel
23:36metrics? Where are we losing people?"
23:38Are link clicks actually becoming people
23:40who add to cart? Are the add to cart
23:41people moving to checkout? Are they
23:43completing the purchase? If the site
23:45converts more of the traffic already
23:47coming in, Meta needs fewer dollars to
23:49make more sales. And that's why
23:51sometimes the cheapest growth is
23:52actually stuff that happens after the
23:54click, after the ad. So sometimes
23:56instead of asking what new creatives and
23:58you know, what new things we should
23:59launch, sometimes the better question is
24:01how to stop wasting the traffic that
24:02we're already paying for and we're
24:04bringing to the website because scaling
24:05is not only about raising budget, it's
24:07increasing the amount of output the
24:09business gets from every single dollar.
24:11Um so I'm looking at 3,600 content views
24:13to 177 add to carts. We know from our
24:16KPIs inside of ADVT that this is below
24:19our 10% threshold. So that means that
24:21this is constraint number one. People
24:23are getting to the product pages or the
24:25unique landing page, but they're not
24:27adding to cart at a healthy enough rate.
24:29Now, the return on ad spend is still
24:30very healthy at a six times, but that is
24:32mainly because the AOV on this brand is
24:34about $250 and so they don't need that
24:37many sales to get a good return. But
24:39imagine if their AOV was $50, this
24:41return would be much lower. So we would
24:42have to look at this constraint and go,
24:45"How do we make sure we get 10% of
24:46people to add to cart?" And then from
24:48here, I don't like to see more than a
24:4950% drop to checkout initiated. And so
24:52we do have a higher than 50% drop here.
24:54So constraint number one is content view
24:56to add to cart and then constraint
24:58number two can be add to cart to check
24:59out initiated. And again, another 50%
25:02drop I don't really love to see here,
25:04but this is more within our standards,
25:06right? These two are the bigger
25:07opportunities. So, I can go to the brand
25:09and tell them, "Hey, what if we
25:10consolidate some of the bloated product
25:12description? Maybe we can remove some of
25:14the images on the website because
25:15there's so many here that is not helping
25:17with the user flow." And from content
25:19view to add to cart, there are certain
25:20things that we can tell the brand. Maybe
25:22adding a different color to the add to
25:24cart button cuz sometimes brands have it
25:25as just a white background. We want to
25:27make that button pop. There's many
25:28things that we can do to help with
25:30content view to add to cart. And then
25:32from add to cart to checkout, this could
25:34potentially be a shipping rate issue. I
25:35know this brand has shipping costs, and
25:37so maybe people are getting to the
25:38checkout and they're saying, "Well,
25:39$2.50, I agree to that, but maybe not a
25:42$10 additional shipping." What if we did
25:44a shipping discount in our retargeting
25:46funnel? And so, doing all of these
25:48things makes the budget more efficient,
25:50allowing us to hit the end goal of this
25:51brand and fuel them for a even more
25:54profitable second month. None of this
25:56was a campaign hack. Every move was
25:57about taking back control. We found a
25:59few ads that actually earned the spend.
26:01We removed the things stealing money
26:03from them. We simplified the structure
26:05so the budget wasn't being weighed down.
26:07We scaled the winner in measured steps,
26:09one variable at a time. Then we added
26:11new tests, new audiences when the
26:13account could afford them. And we
26:14improved the economics after the click
26:16so every visitor became more valuable
26:18without increasing the ad spend. More
26:20budget does not create efficiency. It
26:22amplifies what's already underneath it.
26:24And if you have a broken foundation,
26:25then more budget only ensures you lose
26:27more money, even if you don't realize
26:29it, like that $6 million a year
26:31business. Budget is fuel. A small brand
26:33may not be able to outspend the biggest
26:35advertiser in the market, but it can
26:36always be more disciplined about where
26:38every dollar goes, giving them the best
26:40chance to reach that second stepping
26:41stone and fund their growth. So, that's
26:44how you scale on a small budget. It was
26:46never about spending more. It's about
26:47deciding where your money goes instead
26:49of handing your budget to Meta and
26:50hoping the algorithm sorts out. If you
26:52get that right, your $30, $100 a day
26:55starts to behave like a lot more. And if
26:57you want to see exactly how I read in
26:58the account to find those top performers
27:00in the first place, that's the one I'd
27:01watch next.