Public Desire was growing rapidly across offsite digital channels, such as Google Shopping and Facebook. It became difficult keeping on top of their product data in-house; they needed the right expertise and tools to help them keep on top of their digital scalability. By integrating with Intelligent Reach, Public Desire was able to take control of their product data to optimise ads and take their performance to the next level.
Having successfully launched on offsite channels such as Google Shopping and Facebook in-house, their growth on these digital channels were becoming difficult to keep up with. With limited resources and expertise, they were searching for a solution that gave them the ability to easily get control over their product data, access valuable performance insights, and optimise their data feeds at scale.
Public Desire found it difficult to keep on top of their product data themselves. They were looking for a solution that gave them better control and insight into their product ads, at scale.
They had access to limited resources and knowledge on optimising the core of their product ads. It prevented them from going further to enhance campaign performance on Google and Facebook.
As Public Desire were growing digitally, their ad spend was also increasing. With limited capabilities and insight, it was difficult to adjust bidding strategies accordingly.
Our platforms ability to give Public Desire valuable insight into a product-by-product level, helped them to manage product data efficiently. Their insight into the product data health and performance metrics, made it easier to fix data and adjust their bidding.
After getting control over their product data, Public Desire were on route to take their campaigns further. They could now quickly launch content experiments themselves, to easily optimise product titles, categories and images effectively.
With our intuitive platform and experts on hand, we helped support Public Desire in becoming confident Intelligent Reach platform users. They were able to flawlessly get control over their multiple feeds and use Content Experimentation to optimise data and achieve great results.
Laurence Taylor,