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How Paula’s Choice achieved 6x ROI and boosted brand reputation
Technology Category
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Consumer Goods
- Retail
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Fraud Detection
- Predictive Quality Analytics
Services
- Data Science Services
- System Integration
The Challenge
Paula’s Choice, a multinational skincare company, was facing persistent fraud patterns on their platform, resulting in an influx of chargebacks. Fraudsters were ordering products in bulk at a discount and then shipping them to other countries to resell through eBay or Amazon for profit. To combat this, Paula’s Choice initially kept a spreadsheet and manually blocked suspicious orders, but soon discovered how challenging it was to manage and stay accurate. They turned to Sift as a solution. However, when they adopted a new payment processor, they switched from Sift Payment Protection to the payment processor’s revenue protection product, which was offered for free. This switch resulted in an immediate inundation with fraud, receiving hundreds of chargebacks—6x their normal volume.
About The Customer
Paula’s Choice is a pioneer in the skincare industry, offering cruelty-free, effective, and safe products for more than 25 years. The multinational skincare company is dedicated to science-backed research, using ingredients that are gentle for skin and non-irritating. Paula’s Choice strives to empower and enable people around the world with in-depth knowledge about skincare ingredients to help them understand how products impact their skin and how to make educated decisions. The company has a strong commitment to its customers and aims to maintain a secure, safe e-commerce platform.
The Solution
Paula’s Choice realized that a rules-based system was significantly less effective than Sift’s machine-learning models, and that turning off Sift had left their business vulnerable to fraudsters. With the competitor's product, the Client Services department would have needed a dedicated team to monitor orders and constantly make adjustments to rules in order to stay ahead of fraud—resources they didn’t have. The team decided to reverse course and re-implement Sift Payment Protection. Among the many things that Paula’s Choice missed while using the competitor product, was the predictive power of the Sift Score. The wealth of data and ability for automation would have been too difficult to replicate on their own. Paula’s Choice also came to rely on Sift Workflows, specifically their ease of use and the ability to quickly adapt to new fraud trends.
Operational Impact
Quantitative Benefit
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