Hush Blankets is on a mission to help people reclaim their rest. Around the world insomnia and anxiety are only getting worse. Hush provides products like weighted blankets, cooling sheets, and mattresses to help people get the sleep they need.
Hush Blankets came to us looking for help scaling their PPC profitably. A key aspect of this scaling was properly establishing attribution across all marketing channels. Although they were experiencing growth, determining which channel (email, organic, google ads, social ads) was primarily responsible for the growth wasn’t known.
Our goal was to establish a reliable attribution system in which we could clearly see which marketing channels were performing and which channels weren’t. Performance across the board was profitable, but previous paid advertising scaling efforts had lead to significant drops in ROAs. Additionally, we noticed that there was a significant lack of attention given to the email marketing. Our team identified key automations and broad casts to focus on to improve performance.
In order to get the ad campaign up and running we built out a custom landing page structure around CRO best practices. With the checkout process including custom features, we suggested a simplified checkout process. We tested 2 checkout button variations, 2 different checkout variations and 2 thank you page variations. Based on out A/B test, we determined that variation 1 yielded 23% increase in revenue when compared to the control. This was an increase of $6k in revenue in the first month.
The next few months we ran a series of desktop and mobile landing page A/B tests including header navigation changes, product layout changes, font sizes, product reviews. As a result of these tests we saw an increase of 51% in revenue in comparison to the control. This resulted in $14k of additional revenue in the first few months of being deployed.
When we started working, email wasn’t going to be a focus of our team. However when we started digging into the attribution numbers we realized that email accounted for less than 10% of the total revenue generated. Since we typically like to see this number be close to 30% – 40% we started investigating what was happening. What we found is there were very few automations setup to capture potential customers. Our team deployed these campaigns and continued to expand on them to increase the LTV of the customers. We spent most of our time working post-purchase campaigns as well as front end pre purchase workflows and integrating them with the paid campaigns.
Additionally, we noticed very few emails being sent regularly to the existing purchasing list. There was the assumption that very few customers would re order, based on the type of product. Our team tested this philosophy by deploying a content calendar with promotional sales and new product offerings. Based on our recommendations and efforts the average revenue per email jumped from $6k to over $23k.
The goal through the paid ad campaigns was to scale the existing results without seeing a significant pull back in performance. At the current spend levels the ROAs was around 2x and any attempt to scale was met with significant decrease in ROAs. We also learned that proper attribution was never setup and FB was reporting significantly more revenue than it was actually generating, meaning the 2x ROAs was not accurate at all.
Once we address the attribution and could reliably analyze the data behind our effort, we began scaling the advertising campaigns. Through new and engaging creative as well as the enhancements to the website and checkout process, we saw an immediate lift in ROAs. We were able to increase spend from $150k/month to $450k/month while maintaining a 2.5 ROAs on the front end. We were also able to see, at a granular level, which campaign and specific creative were performing best.
When we started this project, we were simply brought on to scale the Paid ad campaigns, but what we ended up doing was much more than that. As with all good marketing campaigns, it is important to look beyond one singular aspect in order to see the big picture. Being able to identify improper attribution, allowed us to quickly and efficiently address the biggest marketing gaps and add generate the most revenue for the client.
