Details
Project: LORI – Furniture Factory
Website: https://www.lori.com.ua
Industry: Solid Oak Furniture
Region: Ukraine
Promotion Period: May 2020 – Present Time
Platforms: Google Ads
Initial Client’s Request: In May 2020, the LORI project was taken on with a primary goal: to increase product sales through various digital marketing channels, primarily focusing on Google Ads.
The main difficulty lay in analytics. There were no resources available to implement full-funnel tracking and associate purchases made via phone, messengers or offline stores with website traffic sources. Essentially, only direct eCommerce transactions via the google/cpc channel were taken into account (purchases made directly on the website without any interaction with managers, calls or chat inquiries).
Solution: To achieve the main goal of increasing sales, it was decided to focus effort on comprehensive optimization of the Google Ads channel and implementing a full-fledged analytics system.
Goals:
✅ Improve and optimize existing search ads
✅ Optimize display/banner advertising
✅ Launch product listing ads
✅ Launch dynamic remarketing campaigns
Tasks:
✅ Set up the eCommerce module in Google Analytics
✅ Verify correct linking between Google Ads and Google Analytics accounts
✅ Develop a keyword list, match types and bidding strategy
✅ Compile a negative keyword list
✅ Structure the advertising account
✅ Set up search campaigns in Google Ads
✅ Set up shopping campaigns in Google Ads
✅ Set up Performance Max campaigns
✅ Set up dynamic remarketing campaign
Більше
Implementation:
Analytics Integration for Efficacy Measurement:
To enable full conversion tracking and accurately measure campaign results, the eCommerce module was implemented in Google Analytics. This allowed detailed tracking of user behavior on the website, including product views, add-to-cart actions, transactions and other key funnel activities.
Call tracking was also implemented, providing a complete picture of lead sources. This was crucial for more precise campaign optimization and smarter budget allocation.
Search Advertising:
In the initial stage, the efforts were focused on search campaign optimization. A thorough keyword analysis was conducted, identifying and excluding irrelevant queries. Highly relevant ad copy was created for each ad group to align with user intent. Additionally, observation audiences were configured, allowing bid adjustments based on the retrieved data.
Product Listing Ads:
The launch of shopping ads became the second stage. Its major advantage is that users see product image, major characteristics, pricing and shopping terms right within the ad. This helps generate the initial interest even before a user accesses the website. Thus, traffic acquires quality, while the conversion potential becomes more possible.
Performance Max Campaigns:
A comprehensive creative and setup approach was used when launching Performance Max campaigns. These campaigns included versatile visual elements:
- Product photos in interior settings to create emotional engagement with users
- Promotional banners to stimulate demand
- Product feed integration for ad relevancy
- Product videos (e.g. tables and chairs) for dynamic audience engagement
Throughout the campaign, various combinations of creatives, audience segments and display strategies were tested to achieve optimal results. This adaptive approach helped tailor the ads to evolving user behavior and ensured peak efficiency of each campaign.
Results (2020 vs 2024 comparison):
✔ Ad expenses decreased by -7.11%
✔ Conversions increased by +119.07%
✔ Conversion Rate (CR) increased by +322.66%
✔ Cost per Conversion (CPA) decreased by -57.56%
✔ Return on Ad Spend (ROAS) increased by +75.89%
Key Performance Dynamics:
↗️ Growth in conversions (purchases, phone calls, lead form submissions)
↗️ CPA (Cost Per Action) – Conversion Cost
↗️ CR (Conversion Rate) – Correlation between the number of conversions and clicks
↗️ CPC (Cost Per Click) – Cost of Click
Performance Max campaigns currently demonstrate the highest effectiveness. These campaigns cover a wide range of Google properties, including Search Network, Display Network, YouTube, Gmail, Google Maps etc.
According to statistics, over 50% of purchases are made after in-person visits to physical stores, around 30% come from phone calls and live chat consultations. The remaining 10–15% are completed directly via the online shopping cart.
Conclusion:
Throughout the campaign’s lifespan, ongoing testing of various campaign types – search, shopping and Performance Max – has enabled a deep understanding of the target audience behavior and evolving market conditions. Based on the data collected, Performance Max campaigns currently deliver the best results, allowing for the most efficient use of the advertising budget and consistent growth across key performance metrics.