How Prescient AI enabled Coterie to fuel Q4 acquisition by reallocating network-level spend on Linear TV and across the marketing mix.
ABOUT
From its signature Diaper to its newest Soft Wipe, Coterie creates premium-quality, high-performing diapering essentials made from clean materials to make the journey into parenthood a little easier. The brand, loved by young parents and endorsed by a growing lineup of celebrities, uses a diverse mix of online and offline marketing channels to find new customers and drive sales through its online stores and retail partners.
CHALLENGE
Scaling spend while maintaining performance across the mix
As Coterie continued to grow, SVP of Growth Ankur Goyal wanted to find more sophisticated tools to complement the brand’s in-house attribution solution, which was manually stitched together using multiple data streams. Inconsistent attribution signals left the team unsure about the ideal channel mix as customer acquisition continued to scale.
Ankur views his marketing tech stack as a way to enhance and confirm the deep knowledge and experience of his marketing team. He wanted to enhance his attribution system to provide more detailed insights, so his team could make ongoing, data-driven decisions with confidence.
As top performing channels, where Coterie invests the most budget, getting spend right on Meta and Linear TV was critical to drive demand. Because Linear TV does not provide great clickstream data and is difficult and expensive to geo-test, multi-touch attribution (MTA) or incrementality testing could not meet their needs.
SOLUTION
Using Prescient AI to reveal ideal spend and opportunities to scale
Ankur began looking into marketing mix modeling (MMM) providers and Prescient AI stood out due to its ability to analyze spend data, platform data, and sales data from multiple revenue sources, while also taking into account all the external factors that can impact marketing performance. While Coterie’s existing attribution methods did provide some valuable but siloed insights, Prescient AI would provide another level of detail and triangulate the data to attribute revenue and find opportunities for optimization.
When Coterie first engaged with Prescient AI, the team had noticed a decline in paid media efficiency and needed to pinpoint the contributing factors. Just one day after connecting Coterie’s channels to the platform, Prescient AI confirmed that linear TV was behind the drop in performance. Prescient’s MMM also showed that results being provided by Google and Meta were skewed due to the limitations of last-click reporting.
With the new cross-channel insights and recommendations from Prescient AI, Coterie was able to fine-tune its TV strategy at the network-level and make quick, confident decisions about spend allocation across the mix.
RESULTS
Linear TV CAC goes down 22%, leading to a 7% overall CAC reduction in the business. ROAS gets a boost across the board.
With new insight into how platforms and campaigns influence each other and a deeper understanding of performance within and across channels, Coterie took action to correct the performance erosion of their linear TV investments and make spend adjustments on other channels to exceed CAC goals and increase revenue generated by paid media.
Encouraged by the initial results using Prescient AI, Ankur and team now trust the platform as a valuable resource for ongoing insights on campaign performance and to test into new channels as the brand continues to grow.
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