If You Don't Understand Data, You Don't Understand Facebook Ads

0:00If you don't understand your data, you

0:01don't understand Facebook ads. It

0:03doesn't matter how good your creative is

0:05or how big your budget is. We took a

0:07brand from $48,000 a month to $108,000

0:11a month, more than doubling revenue with

0:13essentially the same ad spend. Another

0:15client was doing $500,000 a month before

0:18us and within 90 days was doing $730,000

0:21a month, all with the same ad spend. And

0:23we didn't do that with a secret audience

0:25or fueling Andromeda with creative every

0:27week. We did it by reading the numbers

0:29most people running ads never look at.

0:31Because most brands aren't really

0:33running Facebook ads. They just upload

0:35creatives, they let the algorithm sort

0:37it out, and they hope. And the day it

0:39stops working, they start guessing. They

0:40launch new creatives, new audiences,

0:42more budget, none of it based on a

0:44number they can see. So, in this video,

0:46I'm going to show you the exact numbers

0:48I look at and the exact order I look at

0:49them to find what's actually broken.

0:51Once you can read this, you can stop

0:53guessing. You'll know where every dollar

0:55is going and why.

0:58You probably have seen this happen

0:59before. The account is working, revenue

1:01is coming in, ROAS looks good. Everyone

1:03feels like the ads are finally figured

1:05out. Then, a week later, performance

1:07drops. ROAS falls, cost per purchase

1:10goes up, revenue slows down, and now

1:12everybody wants an answer. Usually, the

1:14first explanation is either the

1:16algorithm changed or we maybe need new

1:18creative. But, that's not analysis,

1:21that's a guess. The biggest mistake I

1:22see is that people watch one final

1:24number and they try to reverse engineer

1:26the whole business from it. They look at

1:29ROAS, the king metric. If ROAS is up,

1:31then the account is healthy. If ROAS is

1:33down, they think the ads are broken. And

1:35the worst part is, these can flip-flop

1:37at any second, making results and your

1:39revenue inconsistent. But, ROAS is an

1:43output. It can tell you that the result

1:44changed, but it does not tell you

1:46whether the ad stopped earning

1:47attention, whether people stopped

1:49clicking, whether the page stopped

1:51converting, whether customers abandoned

1:53checkout, or whether average order value

1:55dropped. And if you don't know which

1:57input broke, you end up changing random

1:59things. Then, even if performance

2:01improves, you still do not know exactly

2:04why. This is the reason after nearly a

2:06decade running ads in over $120 million

2:09in online sales, I created the system we

2:11use inside of my company ADVT called the

2:14stairway to paid ads heaven. This

2:16process is simple and basically in the

2:18name. We don't throw 10 variables into

2:20the account and ask Meta to figure it

2:22out for us. We start at the bottom of

2:25the stairway. We isolate one meaningful

2:27variable, establish a control, define

2:29what success looks like, keep the

2:31winners, and remove what's weighing

2:32performance down. Then, we move up to

2:35the next step. It's very intentional and

2:37we're able to see exactly where we hit

2:39resistance and what needs to be fixed.

2:41The easiest way to picture the account

2:43is like a river. Customers enter

2:45upstream and our job is to make sure

2:47that they flow all the way down to the

2:48purchase without hitting a blockage. So,

2:50instead of standing at the end of the

2:52river wondering where the water went, we

2:53work backwards and find the first place

2:56the flow stopped. Did the creative stop

2:58earning attention? Are people paying

3:00attention but not clicking through? Are

3:02they clicking but not adding the product

3:04to their cart? Are they adding the cart

3:05but not beginning the checkout? Are they

3:07reaching the checkout but not completing

3:09the purchase? Are they purchasing and

3:11buying but the AOV can't sustain all of

3:14the cost on the front end? Those are six

3:16different problems. They should not all

3:18get the same solution. So, let me show

3:20you how I read the account one layer,

3:22one step at a time. The first layer is

3:25the creative. Before I blame the

3:26website, the offer, the landing page, or

3:28the checkout, I need to know whether the

3:30ad is doing its job and getting people

3:32to the website and more importantly

3:34stopping the scroll. At this level, I'm

3:36mainly looking at three numbers. I'm

3:38looking at CTR all, link click-through

3:40rate, and CPM. You can see in this

3:43account that an ad almost getting

3:44$14,000 of spend was also getting a five

3:48return on ad spend. Most people would

3:50leave this because the overall campaign

3:52is at a four times return and to some

3:54people this is a massive win. But when I

3:56took a look at this, I saw a missed

3:58opportunity and winning ads were not

4:00getting the spend they deserved. Once we

4:02were able to identify the top ads using

4:04our system and focus the spend and cut

4:07the fat, we were able to hit a six times

4:09return on ad spend and a $7 lower cost

4:12per purchase basically overnight giving

4:14us margin and more breathing room in the

4:17account. Now, how I chose those ads is

4:19part of our process that earlier. First

4:21I look at CTR, the beginning of the

4:23river and the first engagement point for

4:25your brand to the customer. So if I go

4:27back here, CTR all lets us know if the

4:30ad is doing its job and catching

4:31attention wherever it's placing. People

4:34are scrolling fast. If the visual or the

4:36first hook doesn't catch attention, they

4:38will never stay long enough to

4:39understand the product or the offer. So

4:42you can have the best product in the

4:43world, but if you're not catching

4:44attention, then no one's going to see

4:46it. So when this number is weak, it

4:48usually means the creative itself is

4:51weak. Maybe the opening takes too long.

4:53Maybe the first visual hook is like

4:55every other ad in the feed. Maybe we're

4:57leading with something that the brand

4:59cares about but not the customer. At

5:01that point, I do not need to rebuild the

5:03entire campaign or massively discount

5:05the product. I need to find an ad that

5:07drives stronger first impression. Then I

5:10compare that with link click through

5:11rate. An ad can get attention and still

5:14fail to create buying interest. People

5:16may watch it, react to it, or engage

5:18with it, but if they're not clicking

5:20through to the website, then the

5:21messaging is off. Maybe the product

5:23benefit is unclear. Maybe the offer is

5:25weak. Maybe the ad is entertaining, but

5:28it never creates curiosity around the

5:30product. That is very different from an

5:32ad nobody stopped to watch. If people

5:34are not stopping, I change the hook or

5:36visual. If they're stopping, but they're

5:38not clicking through, I look at the

5:40message, positioning, offer, benefit,

5:43and call to action. Then I look at CPM

5:46because performance does not happen in a

5:48vacuum. CPM tells me what we are paying

5:51to reach a thousand users essentially. I

5:53do not automatically kill an ad because

5:55the CPM is high, and I don't

5:56automatically think a ad is a winner

5:58because the CTR looks great. I want to

6:01understand that there's a trade-off

6:02happening here. An ad can have a

6:04slightly lower CTR, but a much lower

6:07CPM, which may allow us to reach

6:09drastically more people and ultimately

6:12send more qualified traffic to the

6:14website. Or an ad can have a great CTR,

6:17but if it costs twice as much to deliver

6:19and the downstream numbers are weaker,

6:22that CTR is not helping anybody if

6:24nobody's seeing it. The point is to not

6:26judge any metric by itself. It's to

6:28understand how these numbers can work

6:30together. Here's a good example. We had

6:32one ad where the initial attention

6:34numbers looked strong. If I looked at

6:36only CTR all, I could have easily called

6:39this one a winner. But, its link

6:41click-through rate was much weaker than

6:43video three. People were interacting

6:46with this ad, but they were not

6:47interested enough to leave Facebook and

6:49learn more about the product. Then, when

6:51we compared it with a second ad, a

6:53video, its initial CTR all was much

6:56lower, but its link click-through rate

6:58was higher. In this specific account,

7:00it's actually one of our top ads now

7:02driving a lot of revenue. The second ad

7:04was creating more actual interest and

7:06curiosity with the media itself. It was

7:09sending more people to the website for

7:11the opportunity to buy. But, if I left

7:13it up to Meta, they would have likely

7:15kept spending budget here because of the

7:17high CTR and the lower CPM. So, the goal

7:20was not to throw away the entire concept

7:22or blindly make more ads. The data

7:24helped us understand what ad was

7:26producing behavior we actually cared

7:28about and which one deserved more

7:29budget. Doing this properly is a lot of

7:32layers to watch on every account every

7:33[music] week. That's exactly what my

7:35team does all day. We live inside of

7:37this data, so the brand owner does not

7:39have to. We've helped over 500 stores,

7:41so if you're running an e-commerce brand

7:43[music] and you'd rather we find these

7:45leaks and fix them for you, then the

7:47link to talk to my team is right below.

7:48Either way, keep watching because the

7:50next layer is where most of the money

7:52leaks out. Let's say an ad is doing its

7:54job, right? A 4.4% CTR all, a 3.3 link

7:58click-through rate, CPM is pretty

8:00healthy. These are generally pretty

8:02healthy metrics in my experience. Now,

8:03for you guys, I like industry standards

8:06of a 2 to 3% link click-through rate and

8:0850% of that should be clicking through

8:10to the website. And an average CPM is

8:12about 28 to $30. So, everything is

8:14really healthy along the board. People

8:16are seeing the ad, they're clicking it,

8:18and they're being taken to the website,

8:20but the revenue is still not there. This

8:22is where a lot of brands keep asking the

8:24creative team for more ads, even though

8:26the campaign and ads may already be

8:29doing exactly what they're supposed to

8:30be doing. Once the click is healthy and

8:32the best we can make it with the assets

8:34available, I move up the stairway to the

8:36link, offer, and landing page

8:38experience. Now, I want to know what

8:40happened after the person left Facebook,

8:42and I check it in order. First, I look

8:44at landing page views. Did the person

8:46who clicked actually load the page? So,

8:49if we look from 7,300 link clicks to

8:517,000 landing page views, we did lose

8:54about 300 people who never fully loaded

8:56the page. And if there's a big gap

8:58between link clicks and landing page

8:59views, I'm not analyzing the product

9:01page yet. I'm looking at page speed,

9:03tracking, accidental clicks, poor mobile

9:06experience. There is no point trying to

9:08improve add to cart rate or even AOV if

9:11a meaningful percentage never gets the

9:13page to load in the first place. Then, I

9:15look at landing page views to add to

9:17carts. [music]

9:18Of the people who reached the website,

9:19how many cared enough to put the product

9:21in their cart? This is where we find out

9:23whether the interest created by the ad

9:25survives once the customer reached the

9:27site. If clicks are good, but add to

9:29cart rate is weak, there is usually a

9:31disconnect somewhere. Maybe the ad makes

9:33a promise the landing page doesn't

9:35continue. Maybe the offer is not strong

9:37enough. Maybe the price actually creates

9:39friction. Maybe the product benefits are

9:41buried somewhere. Maybe the page doesn't

9:43build enough trust with a lack of review

9:45photos showing the product in use. This

9:47is exactly why I'm against increasing ad

9:49spend until you know every variable. If

9:52you have an issue at this stage,

9:54increasing ad spend won't solve the

9:56problem, it'll just create more

9:58drop-off. Next, I look at the movement

10:00from cart to checkout. If people clearly

10:03want the product are showing intent, but

10:05are not beginning checkout, then

10:07something inside the cart experience is

10:09actually slowing them down. Maybe

10:11shipping costs appear earlier than

10:12expected. Maybe the cart is cluttered

10:14with upsell apps that I've seen a lot.

10:16Maybe the checkout button is not obvious

10:18on mobile and you have to kind of scroll

10:19down to even see that button at the

10:21bottom. Whatever that is, the problem is

10:23not fixed by launching another Facebook

10:25ad. Then, I look at checkout to

10:27purchase. At this point, the customer

10:29has shown real intent. They clicked the

10:31ad, they visited the page, added the

10:33product to their cart, and started the

10:35checkout process. If they still do not

10:37complete the purchase, I'm looking at

10:38payment issues, shipping cost, delivery

10:40expectations, lack of urgency, missing

10:43payment methods, trust, or sometimes a

10:46higher AOV just usually requires a few

10:48more touchpoints. Again, each drop-off

10:50gives us a different direction. I don't

10:52just tell the client that their

10:53conversion rate is down. That doesn't

10:55really help anybody. I want to show them

10:56exactly where it's down, what that tells

10:58us, and what we should work on next.

11:00Because, like we've mentioned, each of

11:01these stages is a specific part of the

11:04consumer journey. And so, there is a

11:06specific answer to each of these

11:08problems. There's always 10 things in an

11:10ad account that could be better. But, we

11:11are not trying to make a list of

11:13everything that's imperfect. We are

11:14trying to find the first constraint, the

11:16single point of leverage currently

11:18costing the business the most money.

11:20Then, we fix that before we touch

11:22anything else. That is essentially the

11:24stairway in practice. If you change the

11:26creative, offer, landing page, audience,

11:29budget at the same time, you may get a

11:31better result by luck, but you've

11:33learned nothing. And if results drop

11:35again, you'll be in the same exact

11:37place. Clarity is what allows you to

11:39compound. For example, we're working

11:41with this apparel brand. In the last 30

11:42days, the ad side numbers were healthy.

11:45I showed you guys and it's the same

11:46exact ad account that I showed you in

11:47the prior screen where the CTR was a

11:494.4, the link click through rate was a

11:513.3%, a healthy CPM. People were

11:54clicking at a reasonable cost, so

11:55traffic wasn't their first constraint

11:57that I wanted to focus on. Is it

11:59possible that we can get the CTR to

12:01maybe like a 6% and increase overall

12:03clicks? Sure, but I wanted to check down

12:06river to see if there's a bigger point

12:08of leverage we can focus on. When we

12:10connected with Shopify, we saw sessions

12:12were going up due to us finding the

12:14right ads, but then the add to cart rate

12:16was only 5% here. For context, I like to

12:19aim [music] for a 10% add to cart rate

12:21for e-commerce businesses. We have a

12:23bunch of internal KPIs at ADVT that we

12:26like to hit throughout this whole entire

12:27process. So, customers were curious.

12:29They were wanting to learn more, but

12:31they were not adding to cart at the rate

12:32we needed. 95% of the visitors were

12:35actually leaving and on top of that,

12:37only one in seven users who actually

12:39added to cart finished their purchase.

12:41That told us that the biggest issue was

12:43buying behavior on the product page as

12:45well as urgency or something in the

12:47funnel like shipping costs not letting

12:49them complete the purchase. So, instead

12:51of spending the next month rebuilding

12:52campaigns or making new creatives, we

12:54focused on improving the funnel here,

12:56improving the product page, adding

12:57social proof, making CTA more bold, and

13:00adjusting our free shipping threshold to

13:01see if we can incentivize a little free

13:04shipping offer with a higher AOV, which

13:06would equal a win-win for the client.

13:08Without the full data, they may have

13:09kept changing the ads and never touched

13:11the thing actually holding revenue back.

13:14But, even when the ads and funnel are

13:15healthy, that does not automatically

13:17mean the business is ready to scale,

13:19which leads me to my next point. This is

13:21where the conversation gets bigger than

13:23Facebook ads. A purchase return on ad

13:25spend by itself doesn't tell me what a

13:27customer is worth or how much gross

13:29profit was created or even how quickly

13:32the business got its cash back. You can

13:34have purchases coming in and still not

13:36have the economics that support more

13:38spend. And before I push the budget,

13:40there are four numbers I need to

13:41understand: AOV, CAC, LTV, and payback

13:45period. First is average order value,

13:47how much an average customer spends when

13:49they place an order. And let's say AOV

13:51is $30. Most people immediately ask,

13:53"How do we get the cost per purchase

13:55lower?" I do too. That's when I look at

13:57those inputs we covered earlier, but I'm

13:59also asking, "How do we get the AOV to

14:0145, 70? Can we create a bundle, add a

14:03quantity upsell, improve the upsell,

14:05build a better free shipping threshold,

14:07position a higher value product more

14:09effectively?" Because if AOV increases,

14:11the ad doesn't even need to perform

14:13better for the business to make more

14:15revenue and potentially more gross

14:16profit. Then I need to know customer

14:18acquisition cost. What does it cost the

14:21business to actually acquire a customer?

14:23And more importantly, what can the

14:24business actually afford to pay? And

14:26that answer does not come from a generic

14:28two times or three times return on ad

14:30spend target. It comes from margins,

14:32customer value, 3PL, operating cost, and

14:35cash flow, which will be unique for

14:37every brand, so I can't give you a magic

14:39number here because two brands can sell

14:41the same product at the same exact price

14:43and have two completely different

14:45allowable CACs. Then we have lifetime

14:48value. What is that customer worth after

14:50the first order? Do they buy once and

14:52disappear or do they come back in 30,

14:5460, 90 days? Is there a replenishment

14:57cycle, a subscription, complementary

14:59product? A brand with a strong repeat

15:01purchase rate may be able to accept a

15:03lower return on the first order, the

15:05front end, because it understands the

15:07value that that customer creates later.

15:09But I don't want to use LTV as an excuse

15:12to lose money today. That is where

15:13payback period matters, which is how

15:15long does it take a business to earn

15:17that acquisition cost back. A customer

15:19may eventually be worth $900, but that

15:22doesn't automatically mean that the

15:23brand can spend $850 to acquire them

15:26today if most of that $900, you know,

15:28arrives over 3 years. Once you know the

15:30payback period, you know how aggressive

15:32you can be, you know how much cash is

15:33going out, when it should return, and

15:35how long the business can afford to

15:37wait. That is how one brand can outspend

15:39another without necessarily taking on

15:41more risk because they're not flying

15:43blind. They understand the economics

15:45behind the spend, and it helps us, the

15:47ad buyers, make strategic decisions for

15:49the growth of the brand, not just the up

15:51and down waves of today. And that's

15:53actually what scale looks like. It's not

15:54raising the budget because yesterday's

15:56ROAS was good. You understand that it

15:58would break, but it's climbing the

15:59stairway with every step underneath it

16:02proven.

16:05At the start of this video, I said most

16:07brands are not really running Facebook

16:08ads. They're letting Facebook ads run

16:10them, and that's the difference. They

16:12see one number, and you'll see the

16:14entire equation with what we covered.

16:16When things go down, you can identify

16:18the constraint, make an informed change.

16:20You're not a slave to the algorithm

16:22anymore. You know where every dollar is

16:24going, and that doesn't mean that every

16:26campaign will work or every test will

16:28work. Performance still goes up and

16:29down. The difference is when something

16:31changes, you have a process for

16:33identifying why because two brands can

16:35have the same product and the same ad

16:37budget, but the one reading the full

16:39equation keeps removing constraints and

16:41compounding the winners. The one

16:43guessing keeps changing random variables

16:45and setting money on fire. So, now you

16:47can see exactly where an account leaks

16:49top to bottom from the first click all

16:51the way down to payback. Reading the

16:53data tells you what's broken, but when

16:54you're working with a small budget,

16:56knowing what's broken and fixing it

16:58without spending crazy amounts of money

17:00are two completely different problems,

17:02and that's what I'm breaking down next,

17:04how to make every dollar count when you

17:05don't have much of it. So, I'll see you

17:07in the next one.