From 80 to 240 Orders
in 4 Months
in 4 Months
An e-shop with a limited budget, focused on orders and loyal customers.
Even we weren’t sure if we could improve the results – but we gave it a try.
Find out what happened and what made the difference in this case study.
Even we weren’t sure if we could improve the results – but we gave it a try.
Find out what happened and what made the difference in this case study.
About the E-Shop
This e-shop sells printer cartridges (Czech Republic)
- Category:Printer Cartridges / Toners
- Growth:from 30–50 to 50–400 monthly orders
- Product Range:400 SKUs
This case was unique for us – we don’t usually take on projects like this.
For this client, acquiring orders is critical, and they already had a solid customer retention process in place. That’s why we tailored our algorithms to focus specifically on that primary goal.
For this client, acquiring orders is critical, and they already had a solid customer retention process in place. That’s why we tailored our algorithms to focus specifically on that primary goal.
The Beginning – and Analytics Challenges
Initially, the campaign structure was extremely basic — just one ad campaign — and analytics were poorly configured.
They were using a paid plugin for analytics, but it provided inaccurate data. The discrepancy in reported order values sometimes reached up to 40 times the real amount.
Using our algorithm, we categorized the product range and discovered that some products significantly outperformed others. So we grouped them into separate segments.
They were using a paid plugin for analytics, but it provided inaccurate data. The discrepancy in reported order values sometimes reached up to 40 times the real amount.
Using our algorithm, we categorized the product range and discovered that some products significantly outperformed others. So we grouped them into separate segments.
Results and Growth
After several rounds of adjustments, we managed to stabilize the cost per conversion while increasing the number of monthly conversions from 80 to 400 during the high season.
Post-Christmas, order volume settled at around 200–250 orders per month.
Post-Christmas, order volume settled at around 200–250 orders per month.
Key Steps:
- Analytics Setup
- Product Analysis & Segmentation
- Ad Campaign Structure
- Optimization
Analytics Setup
This is one of the most critical steps in working with Google Ads.
If you’re sending data from GA4, we recommend replacing it with Google Ads conversion tags — GA4 data loss can reach up to 20%.
If you’re sending data from GA4, we recommend replacing it with Google Ads conversion tags — GA4 data loss can reach up to 20%.
In this particular case, things were trickier. The client used a paid plugin and believed everything was working fine.
Our audit revealed major inconsistencies — the reported average order value was up to 40 times higher than the actual numbers.
We decided to implement two additional conversions to identify the issue. After a week of testing, we compared the results and kept only the conversion with realistic data.
This is a vital step — working with Google requires accurate and trustworthy data.
In general, analytics issues are rare on platforms like Shoptet, but with smaller providers or open-source solutions, thorough verification is essential.
Our audit revealed major inconsistencies — the reported average order value was up to 40 times higher than the actual numbers.
We decided to implement two additional conversions to identify the issue. After a week of testing, we compared the results and kept only the conversion with realistic data.
This is a vital step — working with Google requires accurate and trustworthy data.
In general, analytics issues are rare on platforms like Shoptet, but with smaller providers or open-source solutions, thorough verification is essential.
Product Analysis & Segmentation
Using our algorithm, we evaluated each product in the ads and sorted them into five categories:
- Bestseller
- Potential Bestseller
- Zombie
- Loser
- New
This step is essential for allocating the budget based on individual product performance.
We aimed to boost visibility, clicks, and conversions for products with strong performance metrics.
Conversely, products that consumed budget without delivering results were given lower priority and restricted budgets.
We aimed to boost visibility, clicks, and conversions for products with strong performance metrics.
Conversely, products that consumed budget without delivering results were given lower priority and restricted budgets.
Ad Campaign Structure
Based on this segmentation, we divided
the range into two campaigns:
-
Campaign #1Goal: Maximize conversions and revenue at the target ROAS
Segments: Bestsellers, Potential Bestsellers, New
This campaign included products with proven sales and new items we wanted to test for bestseller potential. -
Campaign #2Goal: Minimize costs for Zombie and Loser segments while maintaining profitability
Segments: Loser, Zombie
We set a target ROAS — costs would only increase if that ROAS was achieved.
This approach helped us allocate budget more effectively, uncover new bestsellers, increase revenue, and improve campaign efficiency.
Once we surpassed 120 conversions per month, we slightly expanded the structure and added two more campaigns.
We found that one segment was generating the majority of orders and performing best. So we assigned it a dedicated budget and reallocated the remaining budget across other segments.
Once we surpassed 120 conversions per month, we slightly expanded the structure and added two more campaigns.
We found that one segment was generating the majority of orders and performing best. So we assigned it a dedicated budget and reallocated the remaining budget across other segments.
Optimization
We tested several optimization methods beyond product segmentation.
We also developed an algorithm to maintain stable performance:
• Make changes no more than once every 3–4 days
• Adjust CPA targets by no more than 10%
• Adjust budget by no more than 30%
• Limit the number of assets in each asset group
Why? Because Google Ads is a combination of:
• Demand
• Statistics
• Data
• A self-learning algorithm
Any drastic change can cause performance fluctuations:
• Increasing budget raises impressions and clicks, altering data flow
• Changing ROAS/CPA changes how the budget is applied
• Modifying product count in campaigns affects search queries
Major changes can trigger algorithm retraining.
We also developed an algorithm to maintain stable performance:
• Make changes no more than once every 3–4 days
• Adjust CPA targets by no more than 10%
• Adjust budget by no more than 30%
• Limit the number of assets in each asset group
Why? Because Google Ads is a combination of:
• Demand
• Statistics
• Data
• A self-learning algorithm
Any drastic change can cause performance fluctuations:
• Increasing budget raises impressions and clicks, altering data flow
• Changing ROAS/CPA changes how the budget is applied
• Modifying product count in campaigns affects search queries
Major changes can trigger algorithm retraining.
The most important thing is that most of the optimization and product segmentation processes run automatically.
Final Results:
Orders:
From 78 to 240 (+208%)
Budget:
From CZK 15,000 to 28,000 (+86%)
Cost per Order:
From CZK 192 to 134 (–32%)
Orders:
From 78 to 240 (+208%)
Budget:
From CZK 15,000 to 28,000 (+86%)
Cost per Order:
From CZK 192 to 134 (–32%)
Conclusion & Next Steps
Online success doesn’t come by chance. The key is understanding your e-shop’s economics — knowing which products bring profit, which drain the budget, and what truly drives results. That requires precise data, regular analysis, and informed decision-making.
Just launching campaigns isn’t enough. You need to monitor the performance of each product and segment, set up analytics correctly, and direct budget where it has the greatest impact.
In upcoming chapters, we’ll explore examples from shops of various sizes and segmentations, along with real metrics and strategies that match their specific needs.
Online success doesn’t come by chance. The key is understanding your e-shop’s economics — knowing which products bring profit, which drain the budget, and what truly drives results. That requires precise data, regular analysis, and informed decision-making.
Just launching campaigns isn’t enough. You need to monitor the performance of each product and segment, set up analytics correctly, and direct budget where it has the greatest impact.
In upcoming chapters, we’ll explore examples from shops of various sizes and segmentations, along with real metrics and strategies that match their specific needs.
What You Can Do Right Now:?
Use our step-by-step guides to evaluate your shop and gradually improve your product offering, average order value, and ad campaigns.
Guides:
Use our step-by-step guides to evaluate your shop and gradually improve your product offering, average order value, and ad campaigns.
Guides:
- How to Set Up and Validate Your Analytics
- How to Increase Average Order Value — (Key Principles + Examples)
- How to Manage Product Range in Your E-Shop
- Competitor Comparison for Your Products
- Campaign Performance Analysis
What You’ll Get with GETPROFIT in 30 Days:
- Analysis of Your Product Range & Google Ads AccountWe’ll show you your bestsellers and how much you’ve already invested in them. You’ll find out which products deserve more budget — and which ones are just burning through it needlessly.
- Campaign Structure CreationWe’ll segment your products by performance to increase revenue and ROAS.
- Product ReportsWe’ll create clear, easy-to-understand product reports that will help you manage your e-shop’s product range effectively based on real data.
Analysis of Other E-Shops
1.5M+
100+
14+
$1M+
Products in the System
Active Clients
Managed Monthly Budget
Countries We Operate In
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