Client
An e-commerce store for appliance parts and consumables
We previously highlighted how the project took off from day one, doubling Google Ads conversions. Below, we outline how the results evolved over time during our ongoing collaboration — and which changes helped drive even more growth.
Initial Objective
Reduce the average cost per conversion
Project Timeline
May 2024 – October 2025
Types of conversions in the project
- Website purchase;
- Binotel chat;
- Binotel phone call.
Right from the start, we cut the average cost per conversion by 48% and doubled conversions. But the real challenge came right after — operating in an environment where demand is volatile, competition is getting tougher and auction conditions are constantly changing. That’s why we responded quickly to changes and continuously optimized the campaigns to maintain consistent performance.
Updated objective
Average monthly conversions: 1,580
Campaign Performance Metrics After the First 6 Months
Within the first six months we managed to achieve a consistent performance: an average of 1,680 conversions per month at a cost of UAH 41.91 per conversion . Performance remained consistent with only minor fluctuations over time.
Client’s Challenge
The company encountered operational overload. During peak periods, order volume reached up to 90 orders a day, making same-day shipping impossible for all orders. On top of that, the average order value was relatively low, ranging from UAH 200 to 230, as low-cost replacement parts dominated and were typically ordered in small quantities.
Hiring additional staff could have helped process the orders faster, but it would have pushed operating costs up. On top of that, external risks emerged — the war and declining purchasing power raised concerns about whether the company should expand the team.
The business was looking for a way to improve efficiency without expanding the staff.
Our solution
To address the client’s needs without expanding the team, we took a different approach: shifting the focus from conversion volume to conversion value.
This change allowed us to focus not only on the number of orders coming in, but also on the return of each order for the business — thus, increasing the average order value. We immediately assessed the risks: the number of conversions might drop, but the overall value of each purchase should increase.
The client approved the strategy, and we launched a test in one product category, using the “Maximize Conversion Value” bidding model, to test the new strategy.
Testing a new strategy
Performance Max campaign metrics with the “Maximize Conversion Value” strategy for the first 7 weeks of the campaign (January 16 – March 8):
During the first 7 weeks of the test campaign, we reached a ROAS* of 6.3 — compared to an average ROAS of 3.19 for the account. This outcome confirmed the effectiveness of the new approach and served as a solid rationale for applying the strategy to the whole Google Ads account.
*ROAS (Return on Ad Spend) is a marketing metric measuring the efficiency of advertising budget usage: how much revenue was generated.
Campaign Performance Metrics for the Period from January 16 to March 8:
Initial results
In the first two months of implementing the new strategy, the total conversion value increased by 56.25%, and the ROAS by 60.73% respectively. Following the transition to a new approach the average purchase value increased from 255 UAH to 431 UAH. Meanwhile, the overall number of conversions decreased by 13.27%, which, in turn, reduced the workload on the store’s logistics department.
Key Campaign Performance Metrics for the Period from March 9 to May 8
Following the transition to the value-maximizing strategy, we observed the following changes:
- The average cost per click increased by 25.72%
- The average cost per conversion increased by 12.09%.
These changes are to be expected: the algorithms started attracting users who are more likely to buy more expensive items. This is expected, as the algorithms shifted toward users with higher purchase value, whose acquisition is more expensive.
Campaign Performance Metrics Compared to the Previous Period from March 9 to May 8
Conversion structure
Along with changes in key metrics, the conversion structure has also transformed. The share of purchases in the total number of conversions increased by 5.7% during the first two periods.
This change is due to a technical restriction – we couldn’t track the value of calls and chats. As a result, the algorithms focused optimization on users who regularly make purchases as they were recognized as the most valuable for Google Ads.
The structure of the conversions obtained:
Summary
- Continuous optimization is the key to consistent results.
Effective advertising isn’t just about a good launch. It requires regular monitoring, analysis, and quick adaptation to market changes, competition, and updates to Google tools - A clearly set goal is the cornerstone of an effective strategy.
The client has to understand which metric is the priority for their business — the number of conversions, their value, cost, profitability, or other KPIs. This allows the team to align the strategy correctly and deliver the best possible outcome. - One strategy — one key KPI.
It’s impossible to both increase the number of conversions and their value or to raise the number while simultaneously reducing the cost. Each strategy has its own priority KPI, so it inevitably affects other metrics. In our case, the transition to the “Maximize Conversion Value” strategy increased the ROAS by 60.73%, adding 290,000 UAH in revenue from Google Ads, although the total number of conversions decreased by 13.27%. - New strategy is equal to new audience behavior.
Following the change in the optimization model, the conversion structure may also be subject to change — e.g., the percentage of purchases may increase in comparison to calls or chats. That’s a natural shift that should be factored in when choosing a strategy.
Project participants:
- Project manager: Anna Losenko
- PPC specialist: Vadym Sirman
