A 142% increase in orders at a used computer equipment store

Optimization and scaling of advertising campaigns for an online store specializing in the sale of used laptops for the corporate sector and gaming models.

CTR
9
ROAS
55
Conversions
142
Impressions
113

Initial data

Website age
5 years
Promotion region
Ukraine
Ad type
Shopping, PMax, Search

Whole works

  • /01 Increase in the steady volume of transactions
  • /02 Increasing sales through low-frequency queries
  • /03 Reducing the cost per acquisition (CPA)
  • /04 Ensuring the accurate transmission of data on the current status of products in Google Merchant Center
  • /05 Increase return on advertising spend (ROAS)

Issues and general strategy

The main challenge in the used electronics niche is fierce competition from classifieds sites and buyers’ distrust regarding the condition of the products. At launch, the ads were performing inconsistently: some products failed moderation in Google Merchant Center due to the lack of unique identifiers (GTINs), and the cost per click for general search terms was too high to maintain profitability.

Project status before work began

  • Many products had a “rejected” status in Merchant Center due to the specific nature of their used condition.
  • Lack of segmentation by device purpose (for education, for gaming, for work).
  • Untapped potential of low-frequency queries based on specific characteristics (SSD capacity, processor model).

Proposed strategy

We focused on automation and maximizing the detail level of the product feed. The strategy was based on allocating budgets across product categories with varying levels of demand and using Performance Max to reach the audience during the feature comparison phase.

What has been done

Technical Setup of the Feed on Khoroshop

We used Khoroshop’s standard features to generate the feed, but added manual conversion rules in Google Merchant Center:

  • We explicitly set the “used” value for all items to avoid being blocked.
  • We automatically added key technical parameters (processor, RAM, SSD, screen resolution) to the Title, which allowed us to capture targeted traffic based on specific user queries.
  • We categorized products by profit margin and price ranges.

Performance Max Campaign Segmentation

Instead of a single general campaign, we created separate ad groups:

  1. Separate groups for devices in perfect condition and those with minor defects (discounted).
  2. Campaigns targeting queries like “laptop for the office” or “used gaming laptop.”
  3. A separate strategy for used Apple devices with higher bids due to high demand and average order value.

Working with the Search Network (DSA)

To cover thousands of unique product listings, we launched Dynamic Search Ads (DSA). This allowed the system to automatically generate headlines for specific laptop models appearing on the site, without the need to manually curate keywords for each listing.

Setting up dynamic remarketing

Users in this niche often spend a long time comparing options. We set up remarketing that targeted visitors with the exact product they had viewed, offering an additional incentive in the form of a store warranty.

Conversion Optimization

We set up tracking not only for purchases via the shopping cart but also for transitions to messaging apps and clicks on the phone number, since used electronics often require additional consultation before purchase.

Results

Thanks to the automation of the product feed and the use of dynamic search ads, we were able to ensure steady growth in orders even amid high product range volatility.

The main driver of growth was the accurate inclusion of technical specifications in ad headlines, which allowed the system to find buyers with clearly defined search queries. Segmentation by usage scenarios (office/gaming) helped us allocate the budget effectively, directing more resources toward categories with higher average order values and faster turnover.

Options At the start of the project In 5 months The difference
Impressions
Impressions 420000 895000 +113%
Clicks
Clicks 8500 19800 +132%
CTR
CTR 2,02% 2,21% +9%
CPC
CPC 4,80 UAH 4,10 UAH -15%
Conversions (sales)
Conversions (sales) 115 278 +142%
Average bill
Average bill 8400 UAH 10200 UAH +21%
ROAS
ROAS 420% 650% +55%
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