Due to the economic downturn, many e-commerce businesses have chosen to cut their advertising spend with hopes to save budget. Since Fashion Days also cut their budget, their goal was to improve their Facebook dynamic product ads (DPAs) performance at a lower cost.
As Fashion Days was one of the early adopters of ROI Hunter, they were already connected with the Product Performance Management (PPM) platform.
To accomplish their goal, ROI Hunter introduced Fashion Days to the platform’s new Segments solution for Facebook.
With Segments, you can view different product segments based on product data from Facebook and Google.
Product Segments are data-driven clusters of items with similar performance, such as bestsellers, deadstock, poor-performers, new arrivals, fragmented stock, and more.
For their goal, Fashion Days chose to analyse how much they were wasting on their poor-performers through Segments.
One of the best benefits of ‘Poor Performers’ is that you can define the metrics needed to meet your goals, and if your goals change over time, the filters can easily change too.
In this case, Fashion Days defined the Poor Performer segment as per the image below.
Upon defining this rule (pictured above), Fashion Days discovered that over 14% of their DPA budget was being wasted on poor-performing products.
To save budget, ROI Hunter used the Product Insights tool to create a new product set that excluded Fashion Days’ Poor Performers from Facebook promotion.
By using ROI Hunter’s Segments, Fashion Days was able to reduce wasted spend and reallocate their budget to other products with better performance.
After creating a product set that excluded Poor Performers from promotion, Fashion Days’ return on ad spend (ROAS) in Google Analytics spiked by 47% month-on-month, despite having a 30% lower spend.
This new product set also contributed to a 33% decrease in cost per sale (CPS) and a 32% drop in cost per acquisition (CPA) month-on-month.