Cheap leads on the first day, but then the cost skyrockets?

Let’s break it down step by step. First, we’ll go over the basics, then explore classic and unconventional solutions, and finally, I’ll suggest something that might seem insane to some. But do you know what insanity is? 🚬

Why does this happen?

No one knows for sure, but based on observations, here’s what we see:

1️⃣ Facebook initially tests audiences chaotically.
It basically runs your ad to a broad audience without real adjustments. This is when you get those cheap leads. But then, the algorithm starts narrowing down based on initial signals—and that’s when lead costs shoot through the roof. The effectiveness drops drastically, and your excitement quickly turns to frustration.

2️⃣ Pixel learning = Facebook’s algorithm "learning" through your budget.
This leads to huge fluctuations—one day, you get 15 leads, the next day only 2, then 6, and so on. Basically, Facebook is testing different audience segments, and you’re paying for it.

3️⃣ Auction fluctuations also play a role.
Prices can be higher on weekends, during lunch hours—at any random time, really. This naturally affects the cost per lead.

4️⃣ The conspiracy theory:
Some believe Facebook deliberately gives you cheap leads on the first day to keep you running ads longer, making you spend more money on "pixel training" before you realize what's happening. While it sounds plausible, I don’t fully agree with this theory—after all, Facebook makes money when advertisers are happy, not when they rage-quit.

How to fix it?

Let's break it down into proven methods, questionable methods, and finally, a hidden trick that might surprise you.

Simple & Effective Methods:

✔️ Restart or duplicate your campaign – A fresh campaign might hit different audience segments and perform better.
✔️ Run ads from different accounts – Some accounts simply have lower trust and get lower ad priority.
✔️ Duplicate ad sets – This can sometimes help you exit the learning phase faster.
✔️ Set a 7-day conversion window – This gives Facebook a bit more flexibility for optimization.
✔️ Test different budgets – Try $10, $20, $30 and see which one stabilizes better.

Questionable Methods:

➖ Waiting for the pixel to finish learning – This requires around 50 leads, which can be very expensive, but if you’re running white-hat offers, it might be worth it.
➖ Analyzing results over 5-7 days – If your budget allows, long-term data can be more reliable.
➖ Adjusting targeting slightly (+/-2 years age range) – Sometimes, this can help snap the algorithm out of its madness.
➖ Manual bid caps – If you can’t afford to pay more per lead, setting a bid cap can prevent overspending.
➖ Avoiding audience overlap – If you're running multiple campaigns, make sure they don’t compete for the same users.
➖ Frequent creative refreshes – Facebook loves fresh creatives and often prioritizes them in auctions.

The Hidden Trick: No Pixel at All 🚀

This is something I discovered when testing lead campaigns in Europe. The simplest and most interesting solution? Don’t use the pixel at all.

Think about it: if your ads get banned within 3 days, why even bother training the pixel? Who are you "teaching"?

If your budget allows for only 10 leads, why waste money on pixel learning?

If your goal is to blitzscale for 4 days with a black-hat creative on some shady Nutra offer (or worse), and you're cloaking on top of that… why complicate things?

Give it a try. You might be surprised by the results. If a campaign doesn’t work right away, simply restart it. Without a pixel, your ads won’t go through unpredictable audience shifts, so performance will be as stable as the initial audience hit.

However, I must say—in the long run, pixels do pay off. But only if you’re running something that Facebook doesn’t kill immediately.

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