$36K/Month To $1.24M/Month In Under 6 Months

This is the entire blueprint detailing how I scaled a fitness eCommerce brand from:

$36K/month to $1.24M/month in under 6 months.

Making Google Ads their #1 growth channel.

Today I share the 3 core strategies that unlocked serious growth:

Product Data Optimisation

This is exactly how we optimised their product data to create performance segmentation.

Please note we used DataFeedWatch (DFW) to achieve this.

Mapping Internal Fields

We first mapped their shop’s data fields to that of DFW.

It does wonders for:

Ensuring data accuracy
Giving us the control we needed
Creating and optimising data feeds

Here’s an overview of how it looks:

Standard Fields

Then we had to make sure all standard fields were correctly entered, for example:

id
title
link
price
condition

Adding Product Descriptions

We did this to fill in descriptions which they had missed in their backend.

Here’s how we implemented it:

Custom Shipping

They also had a range of shipping costs based on item weight.

Using the shipping_label, we added static values based on the weight of each product:

Once we completed this, we then setup custom shipping policies using these static values within their Google Merchant Center account:

Setting Up Shipping Within Google Merchant Center

Include/Exclude Products

This is an excellent way to make sure you aren’t trying to show products that:

Are out of stock or
Don’t have an image link

The impact?

A cleaner data feed and most importantly:

Saving wasted spend by ensuring your budget is only going to products that are in stock.

This is exactly what we did for our client:

Categorising Products

This is where we mapped their products to Google friendly categories.

By simply selecting the product_type field and mapping them to the respective category:

Merge Product Variants Control

This is where you determine:

If you want to merge variants
Assign variant selection to custom fields of weight and shipping_label

We also ensured this was completed, allowing us to focus budget and maximise performance.

Using Product Type To Label Product Performance

Here we leveraged the product type field to label products based on performance, for example:

Top performers
Mid performers
Poor performers

We created a Google Sheet to map and create the labels.

Here’s how this rule looks within DFW:

Using Product Type To Label Product Performance

With this strategy, instead of optimising the products within Google Ads, you’re doing so on a data feed level.

You need to be highly organised and structured to ensure you make no mistakes during setup alongside ongoing management.

Creating Product Hubs

This is great if you have product hubs that perform really well and you want to:

Single them out
Create a campaign focusing on them directly and
Assign additional budget increasing their exposure within Google

And this is exactly what we did for our client.

You do this by using the product_type field, here’s an example:

Creating Custom Categories

What if you wanted to create custom categories to have the same impact as product hubs but on a larger scale?

You’d want to use the custom_label field for this.

Again, we leveraged this strategy for our client.

Here’s an example for football boots:

Performance Max Transition

With the data optimisation completed, it was now time to…

Transition them away from PMax to improve ROI.

First of all, here’s why PMax campaigns shouldn’t be used:

It increases wasted spend across:

Low converting keywords
Underperforming products
Low converting placements

And restricts account performance.

Why?

Because:

It has a broad targeting range
Starts to cannibalise other campaigns
Can neglect parts of your product range
It targets all Google Ads inventory in one
It starts scaling into unprofitable placements
It’s a black box with limited reporting and performance visibility
There’s minimal segmentation between branded vs non-branded traffic

Leaving you with:

Limited performance visibility
Campaigns that overlap, increasing costs
Neglected products with untapped potential
Uncertainty to where you should increase spend
An inability to prevent unprofitable placement targeting
No understanding to truly know what’s moving the needle
Restricted ability to segment budget between branded and non-branded users

In summary, you have minimal visibility and control.

And in the world of Google Ads optimisation:

Increased control and visibility = Increased performance.

The Performance Max Segmentation Strategy

We essentially wanted to segment all Google Ads campaign types:

Whilst also considering their product/category performance.

The first step is campaign segmentation.

It’s critical, as it gives you the ability to target:

Shopping
Search
Display
Video

Individually.

Here’s a visual of how this looks:

The Recommend Segmentation Of Google Ads Inventory By Campaign

Why is this approach ideal?

Because it appreciates the entire funnel.

This allows you to:

Nurture potential customers
Keeps them highly engaged
Maximising conversions

In other words:

Activating both demand generation and capture…

Across Google’s best placements…

At the right time…

Boosts sales.

Here’s an overview of how these campaign should be used to target the entire funnel:

Google Ads eCommerce Full Funnel Approach

The Transition Timeline & Requirements For Each Stage

When making the switch, here’s the performance considerations.

Performance:

Decreases (weeks 1-2)
Stabilises (weeks 2-3)
Increases (weeks 3-4)

Here’s a visual of how this looks within an account across 3 weeks:

The best way to achieve this sequence is through performance based campaigns (explained below).

Here’s the requirements of each step within the sequence:

Step 1: Build Shopping campaigns and exclude PMax listing groups
Step 2: Build Display/Remarketing campaigns and remove all but 2 PMax image assets
Step 3: Build Search campaigns and pause all PMax campaigns

This gradual building, activation of new campaigns and pausing flow allows for a smooth transition into your new campaign architecture.

In terms of timeline, it should occur over a 3-4 week period.

Step 1: Weeks 1-2
Step 2: Weeks 2-3
Step 3: Weeks 3-4

Our Recommendation

DTC brands, don’t sleep on this.

Make these changes now and get ahead of your competition who are still using PMax campaigns.

Campaign Architecture And Building

At a bird’s-eye view here’s how the campaign architecture initially looked:

$0 To $5,770,000 In 6 Months - 3-Step System Blueprint

Campaign Building

I’ve detailed the entire building process in a separate post.

Loaded with a bunch of golden nuggets that’ll seriously boost your ROI.

You can get direct access to it all here:

The $18.8M Google Ads eCommerce Guide.

Bonus: Get Started Today

All of this can be a lot of work, it also requires time and expertise to get it right.

If you need a hand with your Google Ads management, reach out we’d be happy to help.

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