How a Strategic PPC Approach Boosted Online Sales and Improved ROAS for a Fashion Brand

We launched a set of Google Shopping Ads to showcase the client’s products with high-quality images, compelling ad copies, and optimized product feeds. Special attention was given to product titles, descriptions, and custom labels to improve the relevance and quality score of the ads, resulting in better placement and a higher clickthrough rate (CTR).

Two separate campaigns were created for A/B testing, each with different targeting settings, bidding strategies, and ad creatives. Campaign 1 focused on a target return on ad spend (tROAS) bidding strategy, while Campaign 2 used a maximize clicks strategy to capture more traffic. We monitored both campaigns closely for a period of one month, analyzing key performance indicators (KPIs) such as CTR, conversion rate, and CPA. Campaign 1 outperformed Campaign 2, delivering a higher conversion rate and a lower CPA, prompting us to scale up Campaign 1 and allocate more budget toward it.

Using insights from Google Analytics, we identified key audience segments, such as returning visitors, high-intent users, and those who abandoned their carts. This data was used to refine audience targeting, enabling us to create more personalized ad experiences tailored to these groups, increasing the chances of conversion.

We set up a dynamic retargeting campaign to specifically target users who visited thewebsite, added products to their carts, but did not complete their purchases. Custom audiences were created to retarget these users with ads featuring exclusive offers, discounts , or free shipping to incentivize conversions. This strategy resulted in an increase in recovered abandoned carts and boosted overall conversion rates.

In collaboration with the client, we conducted an analysis of the checkout process to identify potential friction points. We streamlined the checkout process by reducing the number of steps, offering multiple payment options, and providing clearer communication around shipping costs and return policies. These changes were implemented to reduce cart abandonment and improve the overall user experience.

To further improve cost efficiency, we utilized advanced bidding strategies, including smart bidding with machine learning, to automatically adjust bids in real-time based on the likelihood of conversion. This approach ensured that the ads were shown to the most relevant users at the optimal bid, significantly reducing wasted ad spend.

Throughout the campaign, we regularly monitored performance metrics and conducted weekly optimization sessions. This included refining negative keyword lists, adjusting bids for high-performing products, and continuously testing new ad creatives and messaging to maintain freshness and engagement.