Sift Case Studies Streamlined fraud workflow, delightful user experience

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	Streamlined fraud workflow, delightful user experience Sift

Streamlined fraud workflow, delightful user experience

Sift

Technology Category	Analytics & Modeling - Machine Learning
Applicable Industries	Retail
Applicable Functions	Sales & Marketing
Use Cases	Fraud Detection
Services	Data Science Services
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Applicable Industries

Retail

Applicable Functions

Sales & Marketing

Use Cases

Fraud Detection

Services

Data Science Services

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.

About 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.

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.

Impact #1	EBTH has been able to streamline their fraud prevention workflow and dedicate the time they formerly spent reviewing false positives to other initiatives.
Impact #2	Since Sift provides the customer service team with such useful, actionable data, EBTH hasn’t needed to add any employees who focus solely on fraud prevention.
Impact #3	Sift provides such high accuracy that EBTH has been able to tackle fraud without introducing steps that could potentially deter good bidders.

Impact #1

EBTH has been able to streamline their fraud prevention workflow and dedicate the time they formerly spent reviewing false positives to other initiatives.

Impact #2

Since Sift provides the customer service team with such useful, actionable data, EBTH hasn’t needed to add any employees who focus solely on fraud prevention.

Impact #3

Sift provides such high accuracy that EBTH has been able to tackle fraud without introducing steps that could potentially deter good bidders.

Benefit #1	0 Fraud analysts on-site
Benefit #2	0 Extra security checks

Benefit #1

0 Fraud analysts on-site

Benefit #2

0 Extra security checks

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Overview

Streamlined fraud workflow, delightful user experience

Operational Impact

Quantitative Benefit