Client
An online store selling parts and consumables for home appliances.
Our Task
To reduce the average cost per conversion.
Work Period
From May 10, 2024, to July 8, 2024.
Project Challenges
The project presented several niche-specific difficulties:
- A large volume of SKUs.
- Extremely low product prices.
- Product names and descriptions included coded parts that were difficult for search engine bots to recognize.
Initial Optimization Results
Given the broad range of spare parts across various categories, brands, and models, our team decided to work simultaneously on two fronts: Search Campaigns and Performance Max, based on a product feed.
The division in the ad account was somewhat artificial but essential for a comprehensive evaluation of results, as the time spent optimizing Search campaigns and Performance Max campaigns varied significantly.
Results from the Second Period
Campaign results after the first two periods of collaboration:
- Conversions increased by 2.2 times
- Cost per conversion decreased by 48%
- Conversion rate improved by 3.8%
Search Campaigns
Considering the store’s specific nature, our specialists decided to set up search campaigns based on dynamic ads. This approach helped manage the large volume of products, simplify account management, and maintain relevant traffic.
First Period Results
Our hypothesis that dynamic search ads would better suit the store’s specificity proved only partially correct. Although the cost per conversion decreased by UAH 249 compared to the previous period, it still seemed high.
To further reduce costs, we set up separate search campaigns for the client’s priority categories with a unified budget, which allowed for more efficient resource allocation between campaigns.
At first glance, it would have made more sense to pause the search campaigns and reallocate the budget to Performance Max. However, this would have negatively impacted Performance Max campaigns because the absence of data from the search campaigns would disrupt the automated bidding strategies, leading to less efficient and more expensive customer acquisition.
Second Period Results
Search campaign results from the second period:
- Campaign expenses decreased by 12.5%
- Conversions increased by 86.9%
- Cost per conversion dropped by 53.2%
- Conversion rate decreased by 0.43%
Launching additional campaigns with a unified budget helped allocate resources more effectively, resulting in increased conversions and lower conversion costs.
Performance Max Campaigns
We set up and launched Performance Max campaigns using the product feed.
First Period Results
Results from the first period of Performance Max campaigns:
- Conversions increased by 90%
- Cost per conversion decreased by 26.9%
- Conversion rate increased by 3.78%
The cost reduction and improved conversion rate were achieved through audience signal optimization. We implemented the following optimization measures:
- Set up search topics
- Added users who interacted with our site and interest-based audiences
- Created custom audience segments, including user interests and behaviors
Second Period Results
In the second period, conversions increased by 7.5%, driven by an increased budget and improved audience quality.
Conclusion
Initial hypotheses and experiences from other projects don’t always hold up 100%, so it’s crucial to monitor campaign dynamics and always have a backup plan to achieve the set goals.
Google’s advertising tools work best in combination. Even with significant differences in cost per conversion, it’s not advisable to disable search campaigns, as this could negatively impact the optimization and effectiveness of other campaign types.
When developing a strategy for contextual advertising, it’s important to consider not only financial aspects but also scalability options and the ability to respond quickly to changes without involving additional resources.
Project Participants:
- Project Manager: Anna Losenko
- PPC Specialist: Vadim Sirman
- Head of Contextual Advertising: Galina Lyman
