Streamlined fraud workflow, delightful user experience
Customer Company Size
Mid-size Company
Region
- America
Country
- United States
Product
- Sift
Tech Stack
- Machine Learning
- Webhooks
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Machine Learning
Applicable Industries
- Retail
Applicable Functions
- Sales & Marketing
Use Cases
- Fraud Detection
Services
- Data Science Services
About The Customer
Everything But the House (EBTH) is an online platform that brings the thrill of estate sale shopping to the digital world. It operates a global marketplace and community of buyers and sellers, transforming the traditional estate sale model while preserving its fundamental charm. EBTH conducts 150 sales a month and ships to anywhere in the world. Its full-service model, which includes photography, cataloging, payment, and delivery, makes downsizing easy for sellers. For buyers, the reach of an e-commerce platform and the starting bid of $1 for all items means there's always something new to discover.
The Challenge
Everything But the House (EBTH) was facing a challenge with fraudulent bids on their online estate sale platform. Fraudulent activities included users bidding with stolen credit card information or without any real intention to complete their purchase. This not only delayed profits for the sellers but also potentially lowered the selling price of the items when they had to be relisted. The continuous occurrence of fraud could lead to customers questioning the integrity of the site. EBTH was using a tool that sent identifiable information about bidders to its servers, but it was reactionary and didn't offer any proactive notifications. Therefore, the company started looking for solutions that could detect and prevent fraud proactively.
The Solution
EBTH decided to integrate Sift, a machine learning-based fraud detection tool, into their system. Sift's transparent, pay-as-you-go pricing and easy setup were the main selling points. Sift's webhooks feature proactively notified the customer service team when it detected someone suspicious, allowing them to decide whether to investigate further. The Developer tab in the Sift Console allowed developers to understand the data and decide what tweaks to make. Additionally, the ability to set up a deep link between the Sift Console and their internal dashboard made the review process smooth and efficient.
Operational Impact
Quantitative Benefit
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