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The sustainable apparel brand ran a pilot of Angler’s Predictive CAPI, improving purchase ROAS by 35%. They rolled out Angler AI across 100% of media spend on Meta to optimize campaigns towards new customer ROAS.
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Christy Dawn is proud to forge mutually beneficial relationships with all of the people and ecosystems they work with, from the regenerative farm and weavers in India to dressmakers and photographers in Los Angeles. They strongly believe in the power of reciprocity and view themselves as part of a larger web that we all rely on. Every member of the community making their garments is essential, and they honor their contribution through long-term commitments.
Christy Dawn has cultivated a strong relationship with their customers, with nearly 50% of their orders coming from returning shoppers—a testament to their excellent product-market fit and a well-executed CRM strategy. When it came to their Meta acquisition marketing budget, the focus was on bringing in new customers exclusively. Prior to partnering with Angler AI, Christy Dawn relied on syncing their existing customer lists from Shopify and Klaviyo (CRM) and using these lists to exclude current customers from all prospecting campaigns. However, in recent years, particularly after the iOS 14.5 privacy changes, they noticed that these audience exclusion strategies became less effective. Meta began attributing significantly more purchases than the actual number of new customer orders reflected in Shopify.
In May 2024, Christy Dawn embarked on a 30-day free pilot with Angler AI, setting clear objectives to enhance their marketing efforts. Their primary goal was to drive new customer acquisition by optimizing their paid campaigns on Meta, with a particular focus on improving the return on ad spend (ROAS) from first-time orders. Additionally, they aimed to implement advanced measurement techniques to gain deeper insights into their campaigns. This included tracking the cost to acquire new customers (CAC) and the purchase ROAS, analyzing what percentage of attributed orders came from new customers, and predicting the 90-day lifetime value (LTV) of these newly acquired customers.
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Christy Dawn installed Angler's app through the Shopify app store, enabling Angler to access their historical backend data, including order headers, line items, products, and customer information. This connection also allowed Angler to subscribe to both standard and custom events directly from Shopify. Additionally, Christy Dawn linked their Meta ads manager and datasets to Angler via Angler’s intuitive web interface.
With this setup, Angler was able to implement predictive CAPI, focusing on optimizing new customer acquisition based on their 90-day lifetime value (LTV). Alongside tracking high-value standard events, Angler also sent custom events to Meta, including events on new customer purchases and the predictive 90-day LTV for each order and new customer.
Christy Dawn conducted a two-week A/B test on Meta, where they compared two campaign strategies. The challenger campaign optimized for the purchase event using the new dataset powered by Angler AI, while the control campaign continued to optimize using their legacy dataset. The results were impressive: the challenger campaign achieved a 23% reduction in cost per order (with 89% statistical significance) and a 35% improvement in purchase ROAS.
Following the success of this pilot, Christy Dawn decided to subscribe to Angler and transitioned all their campaigns to optimize using Angler’s predictive CAPI. This included campaigns specifically targeting new customer purchase events. When comparing the results from June to August 2024 (post-implementation) with March to May 2024 (pre-implementation), Christy Dawn saw a 33% increase in new customer marketing efficiency ratio (nMER) and a 21% decrease in blended customer acquisition cost (blended CAC), all while maintaining a 12% higher daily spend in the post period.
Partnering with Angler AI has been transformative for our marketing strategy. Their predictive CAPI and advanced measurement tools significantly improved our new customer acquisition efforts, leading to a 33% increase in new customer marketing efficiency ratio and a 21% reduction in blended customer acquisition costs, all while maintaining higher spend levels.
Director of E-commerce
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