Solved: How Long to Test Ads? Data & Cost Analysis

Hi there,

Thanks for reaching out! Happy to give you some initial thoughts on your question. It's one of the most common questions I get, and honestly, the way most people answer it is completely wrong and leads to a lot of wasted ad spend.

The short answer is that you're asking the wrong question. It has almost nothing to do with time. It's all about data and cost. Below, I've outlined the framework we use to make these decisions, moving away from guesswork and towards a predictable system for testing and scaling ads.

We'll need to look at the real question: Data, Not Days...

Let's get this out of the way first. Anyone who tells you to "test an ad for 7 days" is either an amateur or is simplifying things to the point of being unhelpful. It's a completely arbitrary number. Why? Because time tells you nothing without context.

Imagine two scenarios:

Scenario A: You spend £5 per day. After 7 days, you've spent £35. You might have only reached a few hundred people and gotten a handful of clicks. You have virtually no meaningful data to decide if the ad "worked". Making a decision here is pure guesswork.

Scenario B: You spend £500 per day. After 7 days, you've spent £3,500. You've reached tens of thousands of people and have thousands of clicks and potentially hundreds of conversions. You have more than enough data to make a confident decision, probably after just a day or two.

See the issue? Same timeframe, wildly different amounts of data. The clock is irrelevant. The only things that matter are data volume and money spent. The real question isn't "how long do I test?", but rather "how much data do I need to make a reliable decision?".

The goal of testing is to achieve what's called 'statistical significance'. In simple terms, this just means you have enough data to be reasonably sure that the results you're seeing aren't just a random fluke. For that, you need a rule. Our go-to rule is simple and effective: The 3x Target CPA Rule.

It works like this: Once an ad set, audience, or creative has spent three times your target Cost Per Acquisition (CPA) without getting a single conversion, you turn it off. It’s had its chance and failed. For example, if you know a new customer is worth £100 to you and your target CPA is £30, you'd let a new ad test run until it spends £90 (£30 x 3). If it hasn't produced a single sale by then, it gets paused. It's a simple, data-driven kill switch that prevents you from burning cash on duds. We've used this exact principle to slash costs for clients, like one Medical Job Matching SaaS where we took their CPA from a painful £100 all the way down to just £7. That was only possible because we had clear rules for cutting what didn't work, fast.

This approach forces discipline and removes emotion from the decision-making process. But it relies on one massive assumption: that you actually know what your target CPA should be. And for that, we need to talk about the most important metric you probably aren't tracking.

I'd say you need to calculate your Lifetime Value (LTV)...

Before you spend another penny on ads, you need to answer this: "How much is a new customer truly worth to my business over their entire lifetime?". This is your Customer Lifetime Value (LTV). Without this number, you're flying completely blind. You have no idea if your £30 CPA is brilliant or catastrophic.

The LTV tells you the maximum amount you can afford to spend to acquire a customer while remaining profitable. It's the bedrock of any scalable advertising strategy. Many business owners focus obsessively on getting the lowest Cost Per Lead (CPL) or CPA possible, but that can be a trap. I'd rather pay £250 for a lead that turns into a £10,000 customer than £5 for a lead that never converts. The cheaper lead is infinitely more expensive.

Calculating LTV isn't as complicated as it sounds. You just need three numbers:

1. Average Revenue Per Account (ARPA): How much money does a typical customer bring in per month (or year, depending on your model)?
2. Gross Margin %: What's your profit margin on that revenue? (Revenue - Cost of Goods Sold) / Revenue.
3. Monthly Churn Rate %: What percentage of your customers do you lose each month?

The formula is straightforward: LTV = (ARPA * Gross Margin %) / Monthly Churn Rate

Once you have your LTV, a healthy business model typically aims for an LTV to Customer Acquisition Cost (CAC) ratio of at least 3:1. This means for every £3 of value a customer brings in, you spend no more than £1 to acquire them. So, if your LTV is £9,000, you can afford to spend up to £3,000 to acquire a customer. This single calculation changes everything. It transforms your ad spend from an 'expense' into a predictable 'investment' in acquiring assets (customers).

To make this tangible for you, I've built a simple calculator below. Play around with the sliders to see how small changes in revenue, margin, or customer retention can dramatically impact the value of each customer and, consequently, how much you can afford to invest in your ad testing.

You'll need to diagnose your funnel...

So now you have a data-driven rule for testing (3x CPA) and you know how to calculate that target CPA (based on LTV). Sorted, right? Not quite. One of the most common and costly mistakes is to assume the ad is the only thing that matters. You can have the best ad in the world, with perfect targeting and compelling copy, but if it sends people to a broken or unconvincing landing page, you will fail. Every single time.

Your ad is just the front door. You have to look at the entire journey a customer takes, from seeing the ad to making a purchase. This is your funnel, and it's almost certainly leaking. The question is, where? When we onboard a new client, we don't just look at their ad account; we analyse the entire customer journey to find the biggest points of failure. It's a process of diagnosis.

Think of it like this:

• Low Click-Through Rate (CTR)? High Cost Per Click (CPC)? -> The problem is likely your ad creative or targeting. Your message isn't resonating with the audience, or you're showing it to the wrong people. The ad itself isn't compelling enough to earn the click.
• Lots of clicks but very few people staying on your website (high bounce rate)? -> The problem is the 'scent' between your ad and your landing page. The promise you made in the ad isn't immediately fulfilled on the page they land on. There's a mismatch in message, design, or offer that's causing confusion and making people leave instantly.
• Lots of landing page views but no 'Add to Carts' or sign-ups? -> The problem is your offer or landing page copy. The product itself, the pricing, the product photos, the descriptions, or the call-to-action aren't convincing enough. People are interested enough to click, but what they find on the page doesn't persuade them to take the next step.
• Lots of 'Add to Carts' but very few purchases? -> The problem is your checkout process. You're losing people at the final hurdle. This could be due to unexpected shipping costs, a complicated form, a lack of trust signals (like reviews or security badges), or not enough payment options.

You can't fix a landing page problem by changing your ad creative. You have to identify the specific stage where users are dropping off and focus your efforts there. Pouring more money into ads to fix a leaky funnel is like trying to fill a bucket with holes in it. You have to plug the holes first.

To help you visualise this, here is a simplified flowchart of a typical conversion funnel. Use your own analytics to find the percentage of people who drop off at each stage. The biggest drop-off is your biggest opportunity for improvement.

You probably should look at your offer...

This brings us to what is, without a doubt, the single biggest point of failure in advertising: the offer. It's the number one reason campaigns fail. You can have the right numbers, the right testing methodology, and a perfect funnel, but if what you're offering doesn't solve an urgent, expensive problem for a specific group of people, you are pushing water uphill.

I see it constantly. Founders who are in love with their product's features, not their customer's problems. Their ads talk about what the product *is*, not what it *does* for the customer. This is a fatal mistake.

Your ad and landing page must communicate your value proposition through a compelling offer. A great offer does three things:

1. Identifies a specific audience: It calls out to a niche group of people, making them feel understood.
2. Highlights an urgent pain point: It speaks directly to a "nightmare" scenario that keeps them awake at night.
3. Presents a clear solution: It offers a tangible, easy-to-understand way to make that pain go away.

For example, a B2B SaaS company shouldn't just sell "project management software". That's a feature. The pain is a Head of Operations terrified of a critical project deadline slipping, costing the company a major client. The offer isn't the software; it's the 'peace of mind that your most important projects will never be late again'. The ad copy then writes itself: "Tired of chasing your team for updates and praying you'll hit your launch date? Our platform gives you a single source of truth, so you can stop managing tasks and start leading projects. See exactly where every project stands in 30 seconds."

And for the love of god, delete the "Request a Demo" button. It's the most arrogant, high-friction call to action in modern marketing. It screams "I want you to commit 30 minutes of your valuable time to let my salesperson pitch you". It offers zero upfront value to the prospect.

Instead, your offer needs to provide an "aha!" moment for free. It must solve a small piece of their problem instantly, earning you the right to solve the whole thing.

• SaaS company? Offer a free trial with no credit card required. Let the product do the selling. We've seen this work wonders for clients, like one B2B SaaS that got over 1,500 trials by switching from a demo model to a free trial.
• Service business? Offer a free, automated tool or resource. A marketing agency could offer a free SEO audit that finds 3 keyword opportunities. We offer a free ad account audit.
• Consultant? Offer a free 15-minute diagnostic call to solve one specific problem.

You'll need to prioritise your audience testing...

Once your LTV is calculated, your funnel is diagnosed, and your offer is compelling, now you can finally focus on effective ad testing. The mistake most people make here is testing random audiences without any structure. They'll throw a few interests into an ad set and hope for the best. This is inefficient and expensive.

A professional approach involves systematically testing audiences based on their position in the marketing funnel, from coldest to warmest. The warmer the audience (i.e., the more familiar they are with you), the better they will perform. Your testing should therefore be prioritised accordingly.

Here's the hierarchy we use, particularly for platforms like Meta (Facebook/Instagram):

1. Bottom of Funnel (BoFu) - The 'Must-Haves'
These are your warmest audiences. They know who you are and have shown strong buying intent. These should be your first priority and should always be running.

• Cart Abandoners: People who added a product to their cart but didn't purchase.
• Checkout Initiators: People who started the checkout process.
• Previous Customers: Your existing customer list is often your most profitable audience for repeat purchases or new offers.

2. Middle of Funnel (MoFu) - The 'Should-Haves'
These users are aware of you but haven't shown direct purchase intent yet. The goal here is to nurture them and bring them back.

• All Website Visitors: Anyone who has visited your site in the last 30-90 days.
• Video Viewers: People who have watched a significant portion (e.g., 50%+) of your video ads.
• Social Media Engagers: Users who have liked, commented on, or shared your posts.

3. Top of Funnel (ToFu) - The 'Could-Haves'
This is your cold traffic—people who have likely never heard of you. This is where you scale, but it's also the most challenging.

• Lookalike Audiences: Meta can create an audience of users who are similar to your best customers (e.g., a 1% Lookalike of your 'Purchasers' list). This is usually the best place to start with cold traffic. Prioritise lookalikes of high-intent actions (purchases, high-LTV customers) over low-intent ones (website visitors).
• Detailed Targeting (Interests/Behaviours): This is classic audience targeting. The trick is to be specific. If you sell high-end coffee beans, don't target 'coffee'. Target followers of specific roasters, magazines like 'Standart', or owners of specific espresso machines. You have to find the interests that are unique to your ideal customer, not the general public.

When you start testing, you work your way up this list. Ensure your BoFu and MoFu retargeting campaigns are in place first. Then, begin methodically testing ToFu audiences, starting with your highest-quality lookalikes. Apply the 3x CPA rule to each audience you test. The ones that perform get more budget; the ones that don't get cut. This systematic approach, which we've used to help clients drive huge volumes of traffic and leads, like the 18k website visitors for an outdoor brand, ensures you're spending your money in the most effective way possible, moving from guaranteed wins to scalable growth.

This is the main advice I have for you:

To bring this all together, here is the step-by-step process I would recommend you follow. This is the framework that moves you from guessing about 'how long' to test, to a professional and predictable system for growing your business with paid ads.

As you can see, the process is far more involved than simply letting an ad run for 'a few days'. It requires a strategic approach grounded in your business's specific economics. Getting this right is the difference between an ad account that bleeds cash and one that becomes a predictable engine for growth.

Implementing this framework can be a daunting task, especially when you're also trying to run your business. It requires deep expertise not just in ad platforms, but in analytics, conversion rate optimisation, and business strategy. This is where working with a specialist can make a huge difference. We've spent years refining this exact process across dozens of client accounts, helping them avoid costly mistakes and accelerate their path to profitability.

If you'd like to have a chat about how these principles could be applied specifically to your business, we offer a completely free, no-obligation strategy session. We can take a look at your current setup and provide some actionable advice on where your biggest opportunities lie.

Hope this helps!

Regards,

Team @ Lukas Holschuh