Get your fraud questions answered and connect with product experts in our brand new Sifters community

How Paula’s Choice achieved 6x ROI and boosted brand reputation

Talk to an expert
Overview

Authentic skincare brand and pioneer

Paula’s Choice has triumphed as 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.

Challenge
  • Fraud patterns resulted in chargebacks and reselling
  • Manual review was faulty and difficult to manage
  • Switching to a competitor’s revenue protection product caused more problems
Solution
  • Opting for real-time machine learning over a rules-based system
  • Re-implementing Sift Payment Protection
  • Using Sift Workflows to adapt to new fraud trends
Results
  • Reduced chargeback rate to 0.2%
  • Uncovered new types of fraud
  • Boosted brand loyalty
Joshua Hamman

Fraudulent activity is, unfortunately, nearly impossible to prevent when doing business online. I believe that the best way to keep customer data secure is with the use of modern technology like Sift. Having Sift is like a security blanket. It uses an incredibly large number of data points to make smart decisions on all orders. In turn, this helps keep customer information private and secure because we’re proactively catching fraudulent orders.

Joshua Hamman, Director of Client Services at Paula's Choice

Challenge

Persistent fraud patterns, faulty manual review, and limited rules-based solutions

Like many e-commerce businesses, Paula’s Choice experienced fraud patterns on their platform that resulted in an influx of chargebacks. They were also faced with a reselling issue—fraudsters were ordering products in bulk at a discount and then shipped them to other countries to resell through eBay or Amazon for profit. 

To combat this influx of fraud, Paula’s Choice initially kept a spreadsheet and manually blocked suspicious orders from a single source of truth—but soon discovered how challenging it was to manage and stay accurate. The Client Services team saw the need for an unbiased system that could take human error out of the equation, and turned to Sift as a solution.

However, when Paula’s Choice adopted a new payment processor, they switched from Sift Payment Protection to the payment processor’s revenue protection product, which was offered for free. Paula’s Choice quickly discovered the limitations of the rules-based product and was immediately inundated with fraud. Within the first 11 days of using the competitor’s product, Paula’s Choice received hundreds of chargebacks—6x their normal volume. This surge of fraud left their warehouse and Client Services team overwhelmed and under-resourced.

Solution

Making the switch back to Sift

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 this 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.

We had to hit the red button and go back to Sift. It made us realize how much Sift does behind the scenes. There’s so much more data to see with Sift.

Joshua Hamman, Director of Client Services at Paula's Choice

Results

Reducing losses and safeguarding brand reputation

As soon as Paula’s Choice switched back to Sift, their chargeback levels immediately went down to 0.2%. Paula’s Choice also discovered a shift in block rates, with the rules-based product blocking 3.1% of orders and Sift blocking 2.2%—indicating that Sift more accurately identifies fraudulent orders. With these factors combined, Paula’s Choice saved $100,000 worth of fraud orders from being placed within the first three days of re-implementing Sift. And longer-term, Paula’s Choice saw a 6x return on investment with Sift Payment Protection. 

By having access to Sift’s global data network, Paula’s Choice was even able to uncover new kinds of fraud they were unaware existed on their platform, such as fake accounts that would later result in suspicious orders. Paula’s Choice also discovered that having the right fraud checks in place with Sift Payment Protection has had a sizable impact on their customer experience and brand loyalty. Even just one negative post on social media about a fraudulent order could lead to a bruised brand reputation—but Sift has helped Paula’s Choice maintain the trust of their customers as a secure, safe e-commerce platform.

Joshua Hamman

What you’re getting with Sift is absolutely worth it. One of the biggest benefits is being able to use a network of large amounts of anonymous data to help monitor your company’s orders. You’re also getting a self-learning tool that’s true AI. Once you get started, the benefits are exponential.

Joshua Hamman, Director of Client Services at Paula's Choice

Download this case study

Download now

Secure your business from login to chargeback

Stop fraud, break down data silos, and lower friction with Sift.

  • Achieve up to 285% ROI
  • Increase user acceptance rates up to 99%
  • Drop time spent on manual review up to 80%
Your information will be used to contact you about our service and subscribe you to our direct marketing communications. You can, of course, unsubscribe at any time. Please see our Website Privacy Notice.