U Beauty Case Study
Finding Net-New Customers Using AMC and 1P Data.
U Beauty knows DTC but aimed for rapid growth in Amazon's premium beauty category.
Their concern was not understanding how Amazon interacted with the .com (DTC) or if upper funnel display investment might ultimately cause cannibalization.
They focused their limited Amazon budget on lower funnel conversion campaigns that they could measure.
AMC allowed us to find “net-new” customers by incorporating U Beauty’s 1P data.
We created a data pipeline ingesting data from 1P data sources like Shopify into Snowflake. Snowflake’s ease of use and straightforward billing meant we were able to implement our framework quickly. We then synced the client’s ongoing DTC customer and order data and augmenting that customer data with additional 3P household data creating customer cohorts. Through Snowflake allowing us to find key customer behavior insights we could use in our Amazon strategy. We pushed the data into AMC via API to unify DTC shoppers with Amazon shoppers.
We now better understand LTV and CAC for customers that shop both on DTC and Amazon, Amazon’s role in acquisition to produce true incrementality beyond their current DTC performance, and the most effective DSP audiences to reach net new customers across both Amazon and DTC.
Did close-up shots of plated food perform better, or were customers more drawn to at-home scenarios? Was copy about convenience, restaurant experience or value more impactful? Did pro photos perform better or was UGC more compelling?
More efficient. DSP orders achieved a lower eCPM (only $1.52) while ensuring that upper funnel campaigns targeted only net new customers.
More effective. Total account traffic increased 294% when comparing account traffic with the same time period in the month prior. Total “new to brand” users increased 60%.
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In New to Brand Customers
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