TLDR;
- Your current tracking setup is fundamentally broken. You're telling Meta's algorithm to find people who click a button, not people who become customers. This is the main reason you're seeing a massive discrepancy.
- You absolutely MUST move your `start_trial` event to fire *after* a user successfully enters their credit card details and activates the trial. This is non-negotiable for effective optimisation.
- The huge drop-off (6 out of 7 people) between clicking 'Sign Up' and actually starting a trial points to a serious friction problem in your sign-up process. The surprise credit card requirement is likely the main culprit.
- When you fix your tracking, expect your reported CPA to skyrocket initially. This is normal. You're moving from tracking cheap, meaningless clicks to expensive, valuable actions. You have to be patient through this new learning phase.
- This letter includes several interactive calculators to help you understand your wasted ad spend, your potential Customer Lifetime Value (LTV), and a flowchart visualising your funnel problem.
Hi there,
Thanks for reaching out!
Happy to give you some initial thoughts on the situation with your Meta ads. Read through your notes and I can see the problem straight away. It's a classic one, but the fact you've spotted the discrepancy between Meta's numbers and your actual trial signups means you're already ahead of most people.
The short answer is yes, you absolutely need to change where you track your trial. The current setup isn't just "not ideal"—it's actively harming your campaign's potential and wasting a good chunk of your budget, even at $20/day. Let's get into why that is and what you should do about it.
We'll need to look at what you're telling the algorithm...
Right now, you're in a bit of a tricky situation. You've got an ad that's clearly working on some level—it's getting clicks from people interested enough to hit 'Sign Up', and you're even getting a couple of real trials out of it. The high CTR is a good sign, it means your creative and initial message is resonating. But the core of the problem lies in the instructions you're giving to Meta's algorithm.
You have to think of the algorithm as an incredibly powerful, but very literal, employee. You've given it one job: "Go and find me more people who will perform the 'start_trial' action." Based on your setup, it's doing exactly what you've asked. It's finding you loads of people who are prone to clicking a 'Sign Up' button. The problem is, you don't make money from button clicks. You make money from activated trials.
By placing the event on that initial click, you're optimising for a low-commitment action. The algorithm learns the characteristics of "tyre-kickers" or "the merely curious"—people who are happy to see the next step, but who bail the second you ask for a real commitment (in this case, a credit card). It's actively ignoring the signals from the 1-2 people per day who *do* complete the process because their final, valuable action is invisible to it. You are, in effect, paying Facebook to find you non-customers.
I've seen this play out with clients before. For one B2B software company running ads on Meta, we were able to generate 4,622 registrations at an incredibly low cost of just $2.38 each. This looked amazing on paper. However, for another software client where the goal was to get actual trial users—a much more valuable action similar to your situation—we saw 5,082 trials come in at around $7 per trial. The key difference is that the $7 trials represented users who were genuinely evaluating the product, whereas the cheaper registrations were a mix of high- and low-intent users. By optimising for the more valuable action, even at a higher reported cost, you ensure the algorithm is finding people who will actually become customers. It's the exact same principle you're dealing with here.
You're training the algorithm to hunt for rabbits when you need it to be hunting for deer. They're both animals, but only one of them is the prize you actually want.
I'd say you need to fix your tracking immediately...
So, the first and most important action is to change your conversion tracking. You need to create a new custom conversion event—let's call it `actual_trial_started` or something equally unambiguous—and configure it to fire ONLY on the 'thank you' page or confirmation pop-up that appears *after* the credit card has been successfully submitted and the trial is officially active.
Then, you need to go into your ad campaign and change the optimisation goal from the old `start_trial` event to this new, more accurate one. This tells the algorithm: "Okay, forget all those button-clickers you were finding. I only care about people who complete the *entire* process. Go find me more of *them*."
This is where things will feel a bit scary for a little while. When you make this change, your reported results in Ads Manager will seem to fall off a cliff. You'll go from seeing "7 trials per day" at a cost of roughly $2.85 each, to seeing "1-2 trials per day" at a cost of $10-$20 each. It will look like you've made things worse. You haven't.
What you've done is corrected your data. You're now looking at the *true* cost of acquiring a customer, not a vanity metric. This is the most crucial mindset shift. The algorithm will now go into a new 'Learning Phase'. It has to discard everything it learned about finding button-clickers and start from scratch, learning the patterns of people who are willing to enter credit card details. This phase can take a few days to a week, especially on a smaller budget, and performance will be erratic. You have to resist the urge to panic and make changes. Let it learn.
To illustrate just how much of your budget is being misdirected, I've put together a small calculator. Play around with the sliders to see the financial impact of your current tracking setup.
You probably should analyse your funnel...
Fixing your tracking is only half the battle. The data you've provided reveals another, equally important problem: your sign-up funnel has a massive leak. For every 7 people who express enough interest to click 'Sign Up', between 5 and 6 of them are abandoning the process. That's a drop-off rate of over 70-85% at the final hurdle. That is incredibly high.
This isn't a problem with your ads; it's a problem with your user experience and your offer. The most likely culprit is the surprise request for a credit card. Users clicking a 'Sign Up' button generally expect to create an account with an email and password. When they are immediately met with a demand for payment information, even for a free trial, it creates immense friction. It feels like a bait-and-switch.
You have to ask yourself some hard questions:
- -> Is it made clear on the landing page that a credit card is required for the trial? If not, you're creating a surprise, and people hate surprises in a checkout process.
- -> How long and complicated is the sign-up form? Are you asking for too much information upfront? Every extra field you ask for will cause more people to drop off.
- -> Have you given them a compelling enough reason to hand over their card details? Your value proposition needs to be exceptionally strong to overcome that barrier. The promise of what they'll get must vastly outweigh the perceived risk and hassle of giving you their payment info.
The "Request a Demo" button is the classic B2B version of this problem. It's high friction and low immediate value for the user. Your "Sign Up for a Trial (with a credit card)" is the SaaS equivalent. You are asking for a huge amount of trust before you've delivered any real value.
Here's a visualisation of what your funnel looks like now, and where the tracking should be.
Your Current Funnel
(~85% Drop-off)
The Ideal Funnel
(Friction Point to Optimise)
The best way to fix this? Test a free trial that *doesn't* require a credit card. Let users get into the product, experience that "aha!" moment where they see its value for themselves, and then prompt them to add a card to continue after the trial ends. Yes, you'll get more low-quality signups, but you'll also dramatically lower the barrier to entry for high-quality users who are simply (and rightly) hesitant to share payment details with a product they've never used. Your goal should be to create Product Qualified Leads (PQLs)—users who are already sold on the value because they've experienced it firsthand.
You'll need a new way of thinking about cost...
Once your tracking is accurate and you're working on plugging the leaks in your funnel, you can start thinking like a professional advertiser. The question isn't "how cheap can I get a trial?" but "how much can I afford to *spend* to acquire a new customer?" The answer to that lies in your Customer Lifetime Value (LTV).
If you don't know your numbers, you're flying blind. You can't make intelligent decisions about your ad spend if you don't know what a customer is actually worth to your business. A trial that costs $20 might seem expensive, but if that user converts to a paying customer worth thousands of pounds over their lifetime, then $20 is an absolute bargain.
Here's a simple LTV calculation:
LTV = (Average Revenue Per Account * Gross Margin %) / Monthly Churn Rate
Let's plug in some hypothetical numbers for a SaaS business. Let's say your product costs $150/month, you have an 80% gross margin, and you lose 5% of your customers each month (your churn rate).
LTV = ($150 * 0.80) / 0.05
LTV = $120 / 0.05 = $2,400
In this scenario, each customer is worth $2,400 to you. A healthy rule of thumb is to aim for a 3:1 LTV to Customer Acquisition Cost (CAC) ratio. This means you could comfortably afford to spend up to $800 to acquire a single new customer. If 1 in 4 of your trial users converts to a paying customer, you can afford to pay up to $200 for a *real* trial sign-up.
Suddenly, that $10-$20 CPA you'll see after fixing your tracking doesn't look so bad, does it? It looks like an incredible foundation to scale from. Use the calculator below to get a rough idea of your own LTV.
With this knowledge, you can start building a proper advertising strategy. You can set realistic target CPAs, test different audiences (lookalikes of your actual trial users will be powerful), and make informed decisions about scaling your budget. At $20/day, you're just dipping your toe in. Once this foundation is solid, you can confidently increase your spend, knowing that every dollar is being optimised towards acquiring high-value customers, not just low-value clicks.
I've detailed my main recommendations for you below:
This is a lot to take in, I know. But getting these foundational pieces right is the difference between an ad account that wastes money and one that becomes a predictable engine for growth. It's not about quick hacks; it's about a systematic approach based on accurate data.
| Phase | Action Item | Why It's Important | Expected Outcome |
|---|---|---|---|
| 1. Immediate Fix | Move your conversion pixel to fire *after* credit card submission. | To provide Meta's algorithm with accurate data so it can optimise for real business results (actual trials), not vanity metrics (button clicks). | Reported CPA will increase significantly, but the data will now reflect your true acquisition cost. Algorithm enters a new learning phase. |
| 2. Funnel Analysis | Investigate the huge drop-off between the 'Sign Up' click and trial activation. | A 70-85% drop-off indicates major friction. Fixing this is a higher-leverage activity than just optimising ads. | Increased conversion rate from click to trial, which lowers your *actual* CPA. More trials from the same amount of traffic. |
| 3. Offer Optimisation | Test a version of your trial that does *not* require a credit card upfront. | This is likely the single biggest point of friction. Removing it will dramatically increase the number of people who try your product. | A much higher number of trial signups. You can then focus on in-app conversion to paying customers. |
| 4. Strategic Patience | After fixing tracking, allow the campaign to run for at least 7 days without major changes. | The algorithm needs time and data to exit the learning phase and find the new, more valuable audience. Constant tweaking resets this process. | Performance will stabilise, and you'll have a reliable baseline for your true CPA, which you can then work to improve. |
| 5. Growth Planning | Calculate your LTV and determine your target CAC. | This shifts your mindset from cost-minimisation to investment. It gives you the financial framework to scale your ad spend intelligently. | Clear goals for your advertising and a data-driven basis for increasing your budget when the time is right. |
Navigating this process, especially the 'valley of death' after you correct your tracking where your numbers look worse before they get better, can be really unnerving. It requires a steady hand and a deep understanding of how these platforms work under the hood. It also involves a lot of ongoing testing and analysis, from your ad creative and targeting right through to your website's user experience.
This is where working with an expert can make a massive difference. We've guided dozens of software companies through this exact process. We handle the technical setup, interpret the data, diagnose the funnel leaks, and build a scalable strategy that aligns with your real business goals. It frees you up to focus on what you do best: building a great product.
If you'd like to chat through this in more detail, we offer a free, no-obligation initial consultation where we can take a proper look at your ad account and landing page together. It might be a good next step to get a concrete plan in place.
Hope this helps!
Regards,
Team @ Lukas Holschuh
