How We Generated $6M+ in 30 Days With Google Ads

How We Generated $6M+ in 30 Days With Google Ads (Full eCommerce Breakdown)

🎯 If Google Ads is a major growth channel for your eCommerce brand—but results feel capped, inconsistent, or inefficient—this breakdown will show you what actually drives scale.

Below, we’re walking through how we helped one of our clients generate over $6.5M in a single month, using a structured, full-funnel Google Ads system across Performance Max, Search, and YouTube.

No hacks. No viral moments. Just clean execution, tight structure, and profit-driven decision making.

Real Shopify Results: What the Growth Looked Like

Let’s start with the source of truth: Shopify.

In May, this brand generated just over $6.5M in sales, representing a 144% month-over-month increase.

Here’s why these numbers matter:

• 🧠 8,247 total orders (+138% MoM)

• 📈 Traffic increased only ~7%, meaning growth wasn’t traffic inflation

• 🛒 AOV held steady at $755 (no heavy discounts or bundles)

• 🔁 Just 19% returning customers → over 80% new-customer revenue

This tells us something critical:
👉 Growth came from better traffic quality and structure, not more promos or brand demand.

Where the Revenue Came From Inside Google Ads

Now let’s jump into Google Ads.

From Google Ads alone, this account generated $2.6M+ in tracked revenue.

Top Revenue Drivers

• 🔍 Search + Performance Max → $2.1M+ combined

• Display & Demand Gen → low-budget support / remarketing

Search Campaigns

• $1.55M revenue

• <$100K spend

• 15.7 ROAS

Performance Max

• $620K revenue

• 3.27 ROAS

• Scaled cold traffic profitably

These two channels did the heavy lifting. Everything else supported them.

Performance Max: How We Actually Scaled It

Performance Max drove $620K in revenue last month—but the structure is what made it profitable.

The Key Difference: Profit Margin Groups (PMGs)

Most brands group PMax by:

• Product type

• AOV

Instead, we grouped products by profit margin:

• 60–70% margin

• 50–60% margin

• 40–50% margin

Why this works:

• Google optimizes for revenue, not profit

• Margin-based segmentation lets us set different Target ROAS goals

• High-margin products = more scale flexibility

• Low-margin products = stricter efficiency targets

This setup isn’t always necessary—but when margin variance is real, it’s one of the cleanest ways to scale profitably.

Deep Dive: One $212K Performance Max Campaign

One standout PMax campaign delivered:

• $212K revenue

• 4.04 ROAS

• ~$52K spend

• 100% cold traffic

Why It Worked

• Asset groups built per top-selling SKU

• Only 4 best-selling products included

• Clean 1:1 mapping between asset groups and listing groups

• Poor-performing SKU paused mid-month

Cleaner signals → better learning → stable performance.

Search Terms: Protecting Cold Traffic in PMax

A critical checkpoint in Performance Max is search terms.

None of the traffic here was branded—and that’s intentional.

Letting PMax spend on branded queries:

• Artificially inflates ROAS

• Masks weak prospecting

• Doesn’t grow new-customer revenue

👉 Always exclude brand terms in cold PMax campaigns.

How:
Campaigns → Settings → Add Exclusions

Product-Level Performance Reviews

At the product level, we review performance line by line:

• Sort by Clicks

• Check CPC, CTR, and conversion trends

• Identify SKUs that:

  • Consistently drive revenue

  • Drain spend without scale

  • Spike early then flatten

This is how we decide:

• What to pause

• What to double down on

• How to restructure listing groups over time

Large catalogs demand active management, not set-and-forget setups.

Performance Max Settings That Matter

⚙️ A few settings that make or break learning:

• Conversion Goals → Purchase only

• New Customer Acquisition → Off during early learning

• Merchant Center Feed → Clean, accurate, synced

• Location Targeting → Presence only

• Automatically Created Assets → Off (full creative control)

Simple. Controlled. Predictable.

Bidding Strategy: Aggressive vs Conservative

For established accounts, we use Conversion Value + Target ROAS.

For newer or ramping accounts, there are two solid options:

Option 1: No Target ROAS (Aggressive)

• Faster learning

• Higher volatility

• Requires close monitoring

Option 2: Break-Even ROAS (Conservative)

• Controlled efficiency

• Slower learning

• Cleaner early data

Both work—the choice depends on risk tolerance and cash flow.

Search Campaigns: The Profit Engine

Search delivered:

• $1.5M revenue

• ~$98K spend

• 15 ROAS

Non-Branded Search

• DSA, competitor, product-specific queries

• $74K spend → $219K revenue

• 2.96 ROAS

• Pure demand capture

This revenue would not exist without intentional cold-intent targeting.

Branded Search: Defending Revenue

Branded search alone drove $1.3M+ in revenue.

Why it matters:

In auction insights, Amazon appeared in 42% of branded auctions, often ranking at the top.

Because we ran branded search:

• 97% top-of-page rate

• 81% absolute top position

Without it, that traffic—and revenue—would leak.

YouTube Ads: From Awareness to Conversions

We normally use YouTube for prospecting—but this brand showed direct purchase behavior.

Campaign 1: High-Intent Remarketing

Audiences included:

• Purchasers (30–540 days)

• All visitors

• Cart abandoners

• Customer Match lists

Result: YouTube functioned as a conversion channel, not just awareness.

Campaign 2: Cold Prospecting

Built around intent and lifestyle:

• Affinity (Cooking Enthusiasts)

• In-Market (BBQs, Outdoor Equipment)

• Custom Intent (fire pits, competitors)

Separate ad groups = better testing and scaling control.

Final Takeaway

🧠 This is how we helped generate $6M+ in 30 days:

• Clean account structure

• Margin-based Performance Max

• Defensive + offensive Search

• YouTube tied into real intent

• Zero shortcuts

If your Google Ads performance feels capped, it’s rarely a spend issue—it’s almost always a structure issue.

If this breakdown helped, keep an eye on future content where we’ll continue unpacking what actually drives profitable scale.