Hi there,
Thanks for reaching out!
Happy to give you some initial thoughts and guidance on your Meta ads. It's a really common situation to be in when you're just starting out, so don't worry. The platform can be a bit of a black box at first. It sounds like you've run into a few classic new account issues all at once, mainly around patience, budget, and campaign objectives.
I'll walk you through what's likely happening and give you a proper framework to get things moving. It's not about finding a magic button, but about giving the algorithm what it needs to work for you.
TLDR;
- Your ads aren't delivering because of a combination of impatience, a tiny fragmented budget, and the wrong initial campaign objective for a brand new account.
- You absolutely MUST give the algorithm at least 3-7 days to learn without touching anything. Constantly making changes resets the learning phase and guarantees failure.
- Starting with a 'Purchase' objective on a new pixel is like asking a stranger to find your best friend in a massive city. You need to "season the pixel" by starting with easier goals like 'Add to Cart' or 'Landing Page Views'.
- Consolidate your budget. Spreading $50 across 5 ad sets gives each one just $10, which is not enough to gather data effectively. Start with one campaign and one ad set.
- This letter includes a flowchart explaining the ad learning phase and an interactive calculator to show you the damage budget fragmentation does to your campaign's learning speed.
You'll need a bit more patience... The dreaded 'Learning Phase'
Alright, first things first. The single biggest mistake I see new advertisers make is a lack of patience. You made changes after 30 hours. Tbh, that's like pulling a cake out of the oven after 5 minutes because it hasn't risen yet. You've got to let it bake.
Every time you create or make a significant edit to an ad set, it enters what Meta calls the "Learning Phase". During this period, the algorithm is actively exploring and trying to figure out the best way to deliver your ads. It's testing different types of people within your audience to see who is most likely to take the action you want (in your case, 'Purchase'). This process is messy and unpredictable. You'll see performance swing wildly day to day. That's normal.
This phase typically requires about 50 conversion events within a 7-day period to exit. With a small budget and a high-friction goal like 'Purchase', getting those 50 events can take a long time, or might not even happen at all. Making changes to targeting, creative, or budget during this time resets the learning phase, forcing the algorithm to start all over again. You essentialy trap yourself in a loop of permanent learning, never giving the campaign a chance to stabilise and optimise.
My rule of thumb? Don't touch a new campaign for at least 4 days, ideally a full week, unless it's spending money like crazy with zero results. You need to give it time to gather data. The waiting is the hardest part, but its non-negotiable.
Ad Set Launch
New campaign begins.
Learning Phase
Algorithm explores, performance is unstable.
Significant Edit Made?
(e.g. budget, targeting, creative)
Learning Complete
Performance stabilises. Ready to scale.
We'll need to look at your campaign objective... You can't ask for marriage on the first date
Your second question is spot on, and you've hit on the other major issue. Is it true you can’t start with a 'Purchase' objective on a new account? Pretty much, yes. It's not a hard rule from Meta, but in practice, it's almost always a recipe for failure.
Think of the Meta Pixel like a brand new employee you've just hired. If you tell them on day one, "Go find me my most profitable customers," they'll just stare at you blankly. They have no idea who those people are, what they look like, or where to find them. Your ad account is in the same position. It has zero data. It doesn't know what a "purchaser" for your specific store looks like. So when you tell it to find them, it has to guess from an audience of 100 million people. The odds of it guessing right are incredibly slim, especially with a small budget.
What you need to do is "season the pixel". You give it easier tasks first to help it learn. Instead of asking for a purchase (a very high-commitment action), you start by asking for something easier. This is where the marketing funnel comes in.
You need to build up data on users who show increasing levels of intent. I've run many campaigns for e-commerce stores, from apparel to subscription boxes, and this is always the path. One campaign we worked on for a cleaning products client saw a 633% return, and another for women's apparel achieved a 691% return. Achieving results like these requires a strategic approach; it's not as simple as starting with a 'Purchase' objective on day one and hoping for the best.
You give the pixel a simpler job, like finding people who will simply view your landing page. Once you have a few hundred of those, the pixel starts to get a picture of what an interested person looks like. Then you can ask for a slightly harder task, like finding people who will 'Add to Cart'. Now the pixel has even more data on high-intent users. Finally, once you have hundreds of 'Add to Cart' events, you can create a campaign optimised for 'Purchase', and the algorithm will actually have a clue who to look for.
I'd say you need to rethink your funnel strategy...
So, let's make this practical. You need to stop thinking in terms of one single campaign and start thinking in terms of a funnel. Here's a simple structure I'd recomend for a new store:
- Campaign 1: Top of Funnel (ToFu) - Data Collection.
- Objective: Start with 'Landing Page Views' or even 'Link Clicks'. The goal here isn't to get sales. The goal is to get cheap, relevant traffic to your site to feed the pixel data. You're just trying to find out who is even remotely interested.
- Audience: This is where you test your interest audiences. That massive 70-100m audience is way too broad. You need to narrow it down. I'll get to that in a bit.
- Budget: You could put your whole $50/day here to start.
- Campaign 2: Middle of Funnel (MoFu) - Retargeting.
- Objective: Now you can try 'Add to Cart' or even 'Initiate Checkout'.
- Audience: You'll target people who visited your website in the last 7-30 days (from your ToFu campaign) but haven't purchased. This is a much warmer, higher-intent audience. You'll need at least a few hundred website visitors before you can launch this.
- Budget: Once you have enough traffic, you could split your budget, maybe $35/day on ToFu and $15/day on MoFu.
- Campaign 3: Bottom of Funnel (BoFu) - Closing the deal.
- Objective: 'Purchase'. This is the final step.
- Audience: Target people who added items to their cart or initiated checkout in the last 7 days but didn't buy. This is your hottest audience. They are on the verge of buying.
- Budget: You can start this with a small budget once you're getting consistent 'Add to Carts'.
This tiered approach allows you to systematically build data and guide users from casual browsers to actual customers. It's more work to set up, but it's the only reliable way to build a profitable ad account from scratch.
Top of Funnel (ToFu)
Objective: Landing Page Views
Audience: Cold Interests
Middle of Funnel (MoFu)
Objective: Add to Cart
Audience: Website Visitors (Retargeting)
Bottom of Funnel (BoFu)
Objective: Purchase
Audience: Add to Cart / Initiated Checkout (Retargeting)
You probably should fix your budget and structure...
This brings me to your campaign structure. You started with 5 ad sets at $10 each. This is a classic case of budget fragmentation. With such a small daily spend, each ad set has very little fuel to power the learning phase. It's like trying to run 5 cars on a thimbleful of petrol each – none of them are going to get very far.
When you're starting out with a small budget (and I'd consider anything under $100/day to be small), you need to consolidate. Give the algorithm one job to do and enough money to do it properly.
I would strongly recommend you start with just ONE campaign and ONE ad set with your full $50/day budget. This gives the algorithm the best possible chance of exiting the learning phase quickly. Once that single ad set is performing well and has left learning, then you can think about duplicating it to test a new audience. But dont do it before. You need a stable baseline first.
The calculator below should give you a clearer picture of why this is so important. See how consolidating the budget dramatically increases the number of actions (like an 'Add to Cart') you can get per week, which is the fuel your campaign needs to learn and optimise.
Fragmented Approach
Actions per ad set, per week
Consolidated Approach
Actions in total, per week
You'll need to get your targeting right...
Finally, let's talk about that audience of 70-100 million. That's what we call 'broad targeting'. It can work exceptionally well for accounts with a lot of pixel data, because you're essentially trusting Meta's algorithm to find the buyers for you. But for a new account, it's just too vast. You need to give the algorithm some guardrails.
This is where detailed targeting (interests, behaviours, demographics) comes in. Your job isn't to find every possible customer, but to build a profile of your absolute *ideal* customer. Who are they? What do they like? What brands do they follow? What magazines do they read? What tools do they use?
For example, if you're selling handcrafted jewelry, targeting a broad interest like "Jewelry" is a mistake. You'll get millions of people who like big high street brands. Instead, you could try layering interests. For instance:
- People who like 'Etsy' AND
- People who like 'Handmade' or 'Artisan' products AND
- People who have shown interest in specific, smaller, independent jewelry brands.
This creates a much smaller, more qualified audience. Specificity is your friend. Start with one well-researched audience in your single ad set and let it run.
I've detailed my main recommendations for you below:
Okay, that was a lot of information. To make it simple, here's an actionable plan you can follow. This is the exact process we'd use for a new e-commerce client in your position.
| Problem Area | My Recommendation | Why This Works |
|---|---|---|
| Patience | Pause all current campaigns. Launch a new one and commit to not touching it for at least 4-7 days. | This allows the campaign to exit the Learning Phase, leading to stable performance and effective optimisation. |
| Campaign Objective | Start a new campaign with the 'Landing Page Views' or 'Add to Cart' objective. Do NOT use 'Purchase' yet. | This "seasons" your pixel by giving it an easier goal, gathering crucial data on who your potential customers are before asking for the sale. |
| Budget & Structure | Use only ONE campaign and ONE ad set. Allocate your entire daily budget (e.g., $50) to this single ad set. | This consolidates your spend, providing enough data and budget for the algorithm to learn quickly and efficiently. It avoids budget fragmentation. |
| Audience Targeting | Instead of a broad 70m+ audience, build a specific audience using layered, relevant interests that your ideal customer would have. Aim for an audience size of 1-5 million to start. | This provides the algorithm with clear guardrails, ensuring your budget is spent on a much more qualified and relevant group of people. |
| Next Steps | Once you have 500+ website visitors, launch a second retargeting campaign (MoFu/BoFu) targeting those visitors with a 'Purchase' objective. | This targets your warmest audience—people who already know your brand—dramatically increasing your chances of getting those first few crucial sales. |
What kind of results can you expect?
This is always the big question. It's impossible to give you exact numbers, but I can give you some realistic ballpark figures. For e-commerce stores in developed countries (like the UK, US, etc.), a typical conversion rate is around 2-5%. The Cost Per Click (CPC) can range from £0.50 to £1.50.
If we do the maths, your Cost Per Purchase could be anywhere from £10 (£0.50 CPC / 5% conversion rate) to £75 (£1.50 CPC / 2% conversion rate). Your job, through constant testing and optimisation of ads and your website, is to push your numbers towards the better end of that spectrum.
I remember one campaign for an e-commerce client selling subscription boxes, where we achieved a 1000% Return On Ad Spend (ROAS). This means for every £1 they spent on ads, they got £10 back in revenue. This is a fantastic result, but it wasn't achieved overnight. It came from applying a methodical, funnel-based approach like the one I've outlined.
It's not just about setting up an ad and hoping for the best. It's a process of understanding your audience, optimising your targeting, creating compelling ads, and fine-tuning your landing page. Getting professional advice can make a huge difference, as we can often spot opportunities you might miss and implement strategies to drive down your costs and increase your returns much faster.
This stuff can feel overwhelming, especially when you're also trying to run a business. This is where having an expert partner can be invaluable. We've navigated these challenges for dozens of businesses, from startups to established brands, and can apply that experience to get your campaigns on the right track from day one.
I hope this detailed breakdown has been helpful and gives you a much clearer path forward. Follow the steps, be patient, and focus on gathering data before you ask for the sale.
If you'd like to chat through this in more detail and have us take a direct look at your account, we offer a completely free, no-obligation strategy session. We can audit your setup and provide a tailored plan to get you moving in the right direction.
Regards,
Team @ Lukas Holschuh