DataFeedWatch Blog | Data feed optimization tips

[Case Study] Maximizing ROI with Real-Time Data Analysis and DataFeedWatch

Written by Kevin Wahlström | May 24, 2024 7:58:48 AM Z

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.

  1. 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.


  1. 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.


  1. 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.


  1. 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.