Case study

Bodystore: increasing yearly revenue growth by 100%

We rebuilt the Search setup around machine learning to increase sales without hurting ROAS. As a result revenue grew fast, and Bodystore.dk regained its market position.

Result

100%

Revenue increased

100%

Revenue increased

0%

ROI decreased YoY

0%

ROI decreased YoY

Overview

Bodystore.dk was experiencing declining growth on Search, despite the fact that Shopping was doing extremely well. Instead of accepting this as an overall trend in Search behavior, we decided together with the client to try out a new approach to search campaigns and overall strategy.

Our Approach
Success factors

Data aggregation based on value per click

By grouping keywords in ad groups based on their value per click, it meant that even though smart bidding tries to cluster similar performing queries we could hold a strategic advantage by easing this process, especially in low data situations like the always highly valuable long-tail keywords.

Automated adgroup and campaign level search query analysis

Themed grouping of search query data allowed for intelligent use of N-gram logic by turning big data into actionable data. By having different themed levels to apply the automated negative keyword set up on, we were able to limit wasteful spend, while retaining as much revenue production as possible in an automated manner.

Tailored campaign specific audiences

Smarter segmentation and grouping of campaigns opened up the ability to tailor audience lists towards certain segments specific to the given campaigns. This allowed us to feed the smart-bidding algorithm, with extremely high-value audience signals.

The future of search is clearly in working together and not against algorithms. It's about finding ways to give platforms a better foundation for thier decisions as well as tailoring accounts towards a client's business goals.

Christoffer Lötebo

Group CEO

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