Solved: eCommerce Stores Need Server-Side Tracking

Hi there,

Thanks for reaching out!

Happy to give you some initial thoughts on what you're seeing with those eCommerce accounts. Your observations are spot on and tbh, pretty common for stores at that level. They hit a ceiling and can't figure out why, and it's usually because the foundations are a bit shaky. I'll walk you through why this is happening and what a proper setup looks like.

We'll need to look at why their tracking is broken...

So, the first thing you've noticed is that these stores are all relying on client-side tracking. A signal score of 40/100 is, frankly, awful. It's not suprising though. Setting up server-side tracking properly can be a real headache, and most business owners don't see the immediate link between that technical task and their monthly revenue. They see it as a "tech problem" not a "marketing problem", so it gets pushed down the to-do list forever.

But here's the thing they're missing: since the iOS 14 update and the rise of ad blockers, client-side tracking is fundamentally broken. It relies on the user's browser (the 'client') sending data directly to platforms like Facebook and Google. This connection is incredibly fragile. If a user has an ad blocker, uses a privacy-focused browser like Brave, or simply opts out of tracking on their iPhone, that data is just gone. Poof. The ad platform never even knows a conversion happened.

Server-side tracking fixes this. Instead of the browser sending the data, your website's server sends it directly to the ad platform's server. This is a much more reliable and secure connection that bypasses most of the things that break client-side tracking. It means your ad platforms get more, and better, data. You get a truer picture of what's actually working.

I've put together a little diagram to show you what I mean. It's a bit simplified but it gets the point across. You can see how many ways the client-side path can fail compared to the server-side one.

I'd say you need to understand the real cost of bad data...

So what does this data loss actually *do* to an ad account? A score of 40/100 means they're potentially missing 60% of their conversion data. This is catastrophic for three reasons:

1. Optimization Goes Blind: The ad algorithms (especially Meta's) are incredibly powerful, but they need data to learn. If they can only see 4 out of every 10 sales, they'll struggle to find more people like those 4 buyers. They end up optimising based on an incomplete picture, which means higher costs and worse results.
2. Retargeting Audiences Shrink: Their 'Add to Cart' or 'Viewed Product' audiences are smaller than they should be. That means they can't effectively retarget people who showed interest but didn't buy. This is leaving a huge amount of money on the table.
3. Lookalike Audiences are Weak: Lookalike audiences are built from a source audience (e.g., 'all purchasers'). If the source audience is missing 60% of its members, the lookalikes created from it will be less accurate and less effective.

In short, bad tracking doesn't just mess up your reporting. It actively makes your ads perform worse. The store owner thinks their ads "aren't working", but the real problem is the algorithm is flying with one eye closed. The amount of wasted ad spend and lost revenue this causes is massive.

To give you an idea of the financial impact, I've built a small calculator. You can adjust the sliders to see how much potential revenue a business might be losing based on their ad spend and how much data they're missing.

You probably should question their channel strategy...

The second thing you've pointed out is the reliance on just Google Ads. This is another classic sign of a business that's hit a growth plateau. They're only capturing existing demand, not creating new demand.

Think about it like this: Google Ads is brilliant for catching people who are already looking for a solution. They go to Google and type "buy handmade leather wallet" or "best cleaning products for wooden floors". This is high-intent traffic, and it's essential. But it's also limited. You can only capture the people who are *already* searching.

Meta Ads (Facebook and Instagram) are different. They are a demand *creation* engine. Nobody goes on Instagram to search for a new brand of cleaning product. But if they're scrolling through their feed and see a really satisfying video of your product making a dirty floor sparkle, you've just created a new customer who didn't even know they needed your product a minute ago. For eCommerce, especially for products that are visually appealing, new, or solve a problem people don't actively search for, Meta is an absolute goldmine.

I’ve seen this time and time again. One campaign we worked on for a women's apparel brand drove a 691% return using Meta and Pinterest. For a client selling cleaning products, we hit a 633% return just on Meta. Another one selling maps and navigation products got an 8x return. These are results you simply can't get by sticking to Google Ads alone. Relying on one channel is like trying to build a house with only a hammer. You need a full toolkit.

You'll need to build a proper full-funnel system...

So, how do you put this all together? You stop thinking in terms of single channels and start thinking in terms of a full-funnel system. Once the tracking is fixed, you can build a machine that moves customers from awareness to purchase, using each platform for what it's best at.

Here’s what that looks like in practice:

• Top of Funnel (ToFu) - Awareness: This is where you find new customers. You use Meta Ads to target broad audiences and lookalikes built from your (now accurate) purchase data. You show them engaging video ads, carousels, and beautiful images to introduce them to your brand and create that initial spark of interest.
• Middle of Funnel (MoFu) - Consideration: These are people who've shown some interest but haven't bought yet. They've visited your website, watched your videos, or engaged with your ads. Now you retarget them on both Meta and the Google Display Network. You can show them testimonials, user-generated content, or highlight specific product benefits to pull them back in.
• Bottom of Funnel (BoFu) - Conversion: This is for the hot leads. People who've added to cart, or are actively searching for your product type on Google. You hit them with Google Shopping ads and Google Search ads for specific keywords. On Meta, you use Dynamic Product Ads (DPA) to show them the exact product they left in their cart. This is where you close the sale.

This system works because it's integrated. The reliable data from your server-side tracking feeds every stage of the funnel, making your targeting smarter and your budget more efficient. You're not just throwing ads at a wall; you're guiding customers through a journey. I've mapped it out below.

This is the main advice I have for you:

Putting it all together, the path forward for these stores is clear, but it requires them to fix the foundations first. It's not about finding one magic ad campaign; it's about building a robust system. Here are the main recommendations I'd make.

As you can see, the work is pretty cut-and-dry. But the execution is where it gets tricky. Implementing server-side tracking correctly requires technical expertise. Structuring multi-channel campaigns, managing budgets, and creating ads that actually work takes a lot of time and experience.

This is often the point where businesses decide they need expert help. Getting this stuff wrong can be incredibly expensive, not just in wasted ad spend but in missed growth opportunities. Getting it right is what allows a store to break through that $50k/mo ceiling and scale profitably.

If you or any of the businesses you're looking at want to have a chat about their specific situation, we offer a completely free, no-obligation strategy consultation. We can take a look at their ad accounts and website and give them a tailored plan of action.

Hope this detailed breakdown helps you make sense of what you're seeing out there.

Regards,

Team @ Lukas Holschuh