Wayfair

Case Study: Wayfair

With Signifyd, Wayfair spends less time and money investigating legitimate transactions yet still manages to reduce fraud and chargebacks. Signifyd’s accurate detection and ease of investigation make Wayfair.com more efficient than ever.

78%

Reduction in Chargebacks

29%

Increase in Detection Accuracy

2%

Reduction in Cases Flagged for Review

Wayfair, with more than seven million home items across thousands of brands, styles, and price points, is truly the online destination for all things home. With an unparalleled selection of home goods, Wayfair promises to make it easy for every customer to find perfect home furnishings and décor at a price that they can afford.

Dedication to its customers has helped Wayfair grow to nearly $1 billion in annual sales, but it is its dedication to improving operational efficiencies to keep costs and prices low that has brought Wayfair to Signifyd.

Before working with Signifyd, Wayfair already had impressively low chargeback rates for such a large online retailer, and its order review process was one of the most streamlined in the industry.

Since deploying Signifyd, however, Wayfair has been able to cut 20% from its average order review time. Fraud analysts have access to all transaction data on one screen, and can quickly and easily see connections between those data elements to make well informed decisions.

What’s more is that Signifyd’s advanced risk scoring has reduced Wayfair’s chargeback rate by an additional 78% from previous levels while actually reducing the number of orders that Wayfair reviews by 2% - no small amount, given the high volume of transactions that Wayfair processes every day.

Signifyd utilizes cutting edge machine learning and sophisticated graph traversal techniques to quickly identify both good and bad actors in a transaction, allowing Wayfair to focus analysts’ efforts on only those transactions that need additional review.

Before Scenario
  • Low catch rate for bad transactions
  • Acceptable chargeback rates for online retailer
  • Analysts spending excessive time reviewing good cases
Goals
  • Reduce chargebacks
  • Reduce number of good transactions flagged
  • Reduce time spent investigating cases
Signifyd Proposal
  • Wayfair uses Signifyd to review orders, taking Signifyd’s suggestion for accepting and declining orders
  • Use Signifyd’s console in manual review process to streamline case investigation
After Scenario
  • 78% reduction in chargebacks
  • 2% fewer overall transactions flagged for review
  • 29% increase in detection of bad transactions
Eliminate fraud and accept more orders with Signifyd
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