Facebook always wants to make more money off ads. Here’s an insider’s guide on how to advertise on Facebook & drive performance without wasting your budget.
You will hear conflicting reports from different people online about how Facebook ads work (and how to advertise on Facebook).
The truth is it’s tricky. Most account reps and developers don’t know how it works. Plus, Machine Learning and algorithms change all the time.
The best approach is always to:
In January 2018, Facebook announced a new update to its news feed algorithm, which prioritizes posts from friends and family to foster “more meaningful social interactions.”
As a result, it became harder for brands, media publishers, and marketers to organically reach their audience. It also impacted ad prices – as AdStage found, in Q1 2018, Facebook’s CMPs went up 91% year over year.
Back then, the platform’s CEO, Mark Zuckerberg, said that this change would likely mean more users spending less time on the platform, thus higher ad prices.
Fast forward to 2021, and it is still the most popular social media platform out there, with over 2,701M monthly active users.
Moreover, there’s a big update in ad limits coming out this year. As stated by Facebook:
Since each ad’s performance improves the more it is shown, advertisers of different sizes should use different ad volumes to improve ad performance. We will be introducing four limit tiers to encourage advertisers of different sizes to use an ad volume per Page that optimizes their performance.
The advertiser’s size is determined here based on their highest spending month in the last year. And so:
Should you be worried? Not necessarily, but these algorithm changes help us answer a crucial question: What does Facebook want?
The answer: to make more money.
Although Facebook’s algorithm changes often, here’s my simplified calculation of how Facebook ads generally work:
DISCLAIMER: This is my interpretation and oversimplification of how Facebook (and many other ad platforms) work, based off my own personal experience ($25m spent across channels) and countless conversations with account reps and other marketers. With that said, let’s break it down.
If Facebook’s users get pissed off and leave, they can’t show them ads anymore. For that reason, the platform has to strike a delicate balance between providing engaging content from friends and sponsors to avoid overwhelming users with ads.
That’s part of the reason why ad relevance diagnostics exists.
If users hate your ad or don’t engage with it, Facebook’s advertising algorithm will also hate you and will likely either charge you more money or just reject showing your ad to their users.
That’s when Ad Relevance Diagnostics comes in. It scrutinizes your ad in terms of quality and engagement and conversion rate ranking and tells you what to improve.
CPM, or cost per mille, is a cost calculation of how much money it would cost to land 1,000 impressions on your Facebook ad.
If Facebook does a better job finding the right users, advertisers are willing to pay a higher CPM to show ads (impressions). That’s why their team works so hard to expand targeting options and increase their advertising algorithms’ efficiency.
Here’s how the math works here:
$50 Conv. Value * 2% CVR * 2% CTR = $20 CPM
If Facebook matches you to users that click twice as often, they can earn a 2x higher CPM.
$50 Conv. Value * 4% CVR * 1% CTR = $20 CPM
The same goes for the conversion rate. Double the conversions means double the CPM they can charge.
Note: This is only if advertisers are efficiently bidding. Some caveats and inconsistencies allow platforms to game the system, but this holds true over the long run.
To decide what users to match you to, Facebook needs to know what your objective is. That can be anything from website clicks to app installs to video views. There are plenty of options Facebook provides you depending on the type of ad you want to run.
If it’s website clicks, they’ll match you to people who historically show a high clickthrough rate on ads.
If it’s conversions, they’ll look for people likely to convert, based on what they’ve seen on your pixel so far.
The more data they have, the better they can match your ad with the exact type of user that would convert.
But how exactly do they match you to the right users?
Say we only had 10 users in our Facebook audience, each with a different likelihood to convert and some more expensive to reach than others.
Other advertisers are trying to reach these users too, maybe based on different targeting than what you’re using.
So the first thing they’ll do is order these users descending by likelihood to convert (or click, if that’s your objective).
Next, they’ll figure out which are the cheapest to reach. Let’s choose the cheapest 40% of the audience we have.
When Facebook shows your ads to these people, they know they’re giving you the best possible chances of success while still maximizing your budget usage.
The real algorithm is much more complex, but it’s the same basic idea:
You’ll notice that Facebook doesn’t just blindly minimize my CPM: I’m paying $2 for Dave because he has a better propensity to convert than any cheaper options below him.
I altogether skip Sarah and Sally: Facebook can now sell those impressions to other advertisers that they know are more likely to convert and will be willing to pay a much higher CPM.
That’s how Facebook makes more money while also saving their advertisers money.
Of course, they do all this at lightning speed with complex machine learning algorithms based on millions of variables, but you get the idea.
Improving your conversion rate, revenue per conversion, clickthrough rate, or targeting has a direct impact on your bottom line.
That’s why it’s crucial to test new ad creatives (CTR), landing pages/onboarding (to improve your conversion rate), and CRM campaigns (Revenue per user).
You can either take the cost savings and bid down on CPM to be more profitable, or bid on CPM to get more volume (attract more of the Daves and Bills of the world).
You might not know this, but every Facebook audience is a lookalike audience. Even if the example above was “Millenials who like Dogs and buy Pet Food in Manhattan,” Facebook has just taken the top 20% of that audience and shown your ad only to them.
It’s why you rarely reach the full audience and why it hurts performance to increase spend — everyone else is either too expensive or not as interested in you.
Lookalike audiences work the same way, but with the entire population of a country. Ever noticed how a 1% lookalike of any conversion event or email list for any client always equals the same number of people?
It’s because they’re ordering the entire country based on their likelihood to convert on your pixel, then selecting just the top 1% to go into your audience.
This approach is wildly successful and performs amazingly well because Facebook’s algorithm is better than a human at determining the “likelihood to convert.” Further, it finds these cheaper people you wouldn’t usually see.
For example, maybe you know that people who use your product are Entrepreneurs who, like Gary Vaynerchuk, use Mailchimp, are 25-35 years old, and live in New York.
BUT do you know that there are tons of small pockets of entrepreneurs living in places like Texas and North Carolina?
Do you have a list of every single startup influencer or email service provider?
Can you identify the few 45 years old who would also like your product?
Facebook can do all of the above. They have several orders of magnitude more data than you do. More importantly, they can decide what’s more relatively essential to predict whether someone will convert.
That’s why lookalike audiences work so well, why Facebook is one of the best ad platforms ever created, and why we still use them daily.
Facebook needs data to do what it does best. So if you choose a conversion pixel too far down the funnel, it won’t find the right people.
If you choose an objective too high up the funnel, like clicks, it’ll optimize to people likely to take that action, regardless of whether they’re likely to convert further down the funnel.
Unfortunately, clicks do not equal conversions.
Sometimes I’ve seen click campaigns drive much better CTR on the same audience, but at a much worse cost per acquisition because the conversion rate was awful.
And that doesn’t even consider revenue-driving factors like qualified vs. unqualified leads, average order size, lifetime value, etc.
Here’s how each objective works:
$20 CPM * 0.5% CTR * 2% CVR = $50 CPA
$20 CPM * 2% CTR * 0.2% CVR = $125 CPA
Campaign objective affects not only Facebook’s ability to target the right people from your audience but also the bid strategies you will be able to choose from.
The most common propositions are:
If your objective is conversion, go first for the lowest cost with a set budget and once you find the median, change your strategy to cost cap.
As you can imagine, some hours, days, or weeks are more expensive on Facebook than others. If Disney is launching a new movie, you can imagine they’re spending millions buying up all the inventory, increasing the prices for everyone else.
So one way to improve performance is to move to a lifetime budget. This takes away some control in how much you spend per day and some more fiddling around when the campaign ends, but it lets Facebook spend less on expensive days, more on cheap days for you.
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