BULBASHKA
Initial Data
Objectives
- /01 Attract customers for specific services: Generate leads for cleaning down jackets, coats, wedding dresses, and shoes.
- /02 Ensure visibility for local queries: Show ads to users searching for "dry cleaning near me."
- /03 Improve traffic quality: Filter out non-target queries ("self-service laundry," "clothing repair," "home stain removal").
- /04 Set up analytics: Track phone number clicks, messenger transitions, and website form submissions.
- /05 Establish a customer retention system: Remarket to users who have already visited the site.
Implementation Strategy
The strategy relied on building a segmented structure based on item types. We created separate campaigns for outerwear, footwear, and home textiles (curtains, blankets). The primary focus was placed on convenience (courier delivery), delicate care for items, and the use of safe cleaning technologies.
Work Performed
Semantic Core Segmentation
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Queries were collected by category: “down jacket dry cleaning,” “suede shoe cleaning,” “on-site curtain cleaning.”
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Separate clusters were created for branded queries and general queries (“dry cleaning prices,” “dry cleaning nearby”).
Structuring Ad Campaigns
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An ad group structure was developed where each group leads to the corresponding service page on the website.
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Precise geotargeting was set up for service areas to ensure maximum relevance.
Creation of Responsive Search Ads
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Ad copies were prepared with clear benefits: “Stubborn stain removal,” “24-hour express cleaning,” “Free delivery for orders over a certain amount.”
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Dynamic Keyword Insertion (DKI) was used so that the user sees the specific item they want cleaned in the headline.
Ad Extension Setup
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Call Extensions: Added for quick contact.
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Callout Extensions: Added regarding professional equipment and eco-friendly products.
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Location Extensions: Configured for drop-off points so customers could easily find the nearest office.
Optimization and Traffic Filtering
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A detailed negative keyword list was formed to exclude queries like “washing machine,” “repair,” “DIY,” or household chemical products.
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Regular search term report analysis was conducted to identify and block irrelevant phrases.
Analytics and Remarketing
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Goals were configured in Google Analytics 4 to track all touchpoints: call requests, Viber/Telegram messages, and online orders.
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Remarketing audiences were connected to bring back users interested in seasonal services (e.g., cleaning winter clothes in the spring).
Results
| Stable Lead Flow: Launched an effective advertising campaign that ensures regular orders for dry cleaning services. |
| Reduced Cost Per Conversion: By filtering out non-target queries, we optimized expenses and acquired customers at a lower price point. |
| Performance Control: The owner now sees clear statistics: the cost per call and which source generates the most orders. |
| Improved CTR: Relevant ads and the use of all available extensions made Bulbashka’s offer more prominent than competitors in search results. |
| Season Readiness: A flexible system was created that is easy to scale during peak seasonal demand. |
Analysis and confirmation of results
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