Case Study: Scaling E-commerce Revenue with Google Ads
Client Type: E-commerce Brand
Platform: Google Ads
Campaign Start: August 23, 2022
Objective
Improve revenue performance from Google Ads by:
a. Increasing purchases
b. Reducing cost per purchase
c. Improving purchase (conversion) rate
d. Scaling profitably without increasing waste spend
Problem Statement: In September, the account showed high activity but inefficient outcomes:
1: Decent traffic volume
2: Low purchase efficiency
3: Higher cost per purchase
4: Low purchase rate
This indicates the campaign was driving traffic, but not training the algorithm strongly enough for buyers.
September 2022 Performance:
Purchases: 53
Conversion Value: $4,043.85
Cost per Purchase: $71.56
Purchase Rate: 1.10%
Avg CPC: $0.79
The issue wasn’t traffic — it was signal quality and conversion efficiency.
Strategic Thinking (What Changed)
Instead of chasing more clicks, the focus shifted to conversion-led optimization, ensuring Google’s algorithm received stronger purchase signals.
Key strategic principles applied:
Optimize for purchase behavior, not just clicks, Improve conversion rate before scaling volume, Reduce cost per purchase by improving traffic quality, and Allow learning through consistent optimization, not constant resets
Execution & Optimization Approach
Over the next 3 months, continuous optimization was applied:
1. Campaigns refined to favor high-intent traffic
2. Conversion tracking aligned properly to purchases
3. Waste reduced through better keyword and traffic filtering
4. Algorithm trained consistently with clean purchase signals
5. Budget efficiency prioritized over raw spend increase
No aggressive scaling — only controlled, data-driven optimization
Results (After Optimization – December 2022)
Purchases: 115
Clicks: 4.38K
Impressions: 538K
Avg CPC: $1.00
Conversion Value: $9,835.85
Cost per Purchase: $38.16
Purchase Rate: 2.61%
