Our client, a well-known retailer with a vast range of products, was struggling to effectively manage their paid search and social advertising campaigns. So we at Beet, a digital marketing agency, took on this challenge to get our client great results.
Problem
The main challenge of our client at Beet was the unpredictable nature of product trends, with sales spiking and dipping within days or weeks. Their goal was to make sure their products got maximum visibility during these peak times to get the best return on investment (ROI) from their ads.
Solution
We teamed up with the client and used real-time data analysis combined with DataFeedWatch's powerful features to create a winning strategy.
Here’s how we did it.
-
Real-time data analysis
Dynamic data integration
We connected with Google Analytics 4 (GA4) and the client's ERP to pull sales data at various intervals. This gave us up-to-the-minute insights into which products were selling well.
Performance monitoring
By keeping a constant eye on product performance, we could quickly spot top sellers and adjust our ad strategies on the fly to take advantage of emerging trends.
-
Custom labeling and bidding optimization
Creating custom labels
Using DataFeedWatch, we labeled products based on factors like price, margin, seasonality, and special deals. These labels helped us target ads more effectively.
Optimizing bids
With these custom labels, we set up sophisticated bidding strategies. This meant we could allocate the ad budget more wisely, focusing on products with the best potential for high returns.
-
Product segmentation
Segmenting campaigns
We created dedicated campaigns for the top-performing products to give them the attention they deserved. This allowed for more focused advertising efforts.
Aggressive advertising
These segmented campaigns had a lower ROAS threshold, letting us adopt a more aggressive ad strategy for products with high potential, ensuring they got the visibility they needed during peak times.
-
Multi-channel integration
Consistency across channels
We applied our strategies consistently across various platforms, including Google Ads, Microsoft Ads, Facebook, and Instagram. This multi-channel approach kept the messaging cohesive and maximized the impact of our ads.
Flexible budget allocation
By continuously analyzing performance data, we could shift our budget in real-time to the most effective channels and campaigns, quickly seizing new opportunities.
Results
Our efforts, fueled by real-time data analysis and smart use of DataFeedWatch, delivered great results.
Higher ROAS
We consistently achieved a ROAS that was approximately 25% above our goal, demonstrating the effectiveness of our targeted ad strategies.
Increased conversion rate
The conversion rate saw an impressive increase of 126%.
Improved shopping impression share
Our client's shopping impression share for these products rose from 52% to 70%.
Quick adaptation
With continuous data monitoring and flexible campaign adjustments, we stayed agile and responsive to market changes.
Staying ahead
By quickly capitalizing on trending products, we helped the client stay ahead of competitors, leading to sustained success and growth.
Conclusion
This case study shows how combining real-time data analysis with DataFeedWatch can transform ad campaigns. Our approach not only maximized ROI but also ensured smart budget allocation across different channels, driving ongoing success.
With careful planning, dynamic adjustments, and strategic execution, we delivered outstanding results that took the client's advertising performance to new levels.