Sift Case Studies How Universe proactively stops abusive user-generated content
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How Universe proactively stops abusive user-generated content

Sift
Analytics & Modeling - Machine Learning
E-Commerce
Business Operation
Fraud Detection
Data Science Services
Universe.com, a global events marketplace, was experiencing an increase in fraudulent listings and spambot attacks as it expanded to over 3 million active users worldwide. The volume of event listings, hosts, and users was increasing rapidly, escalating the risks and potential impact of spam, scams, and other fraudulent activity. The attacks were becoming more sophisticated and harder to address. A major client's event was attacked, which was a pivotal moment for Universe. They didn't want customers to hesitate to host major events for fear of attacks. The fraud team was constantly playing catch up. If a fraudulent event was posted or a spambot started messaging thousands of users, the team would only find out about it once it was too late. Each attack meant multiple developers would have to drop what they were working on to address the issue in time.
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Universe.com is one of the biggest marketplaces in the world, hosting a wide range of events. The platform has experienced rapid growth, expanding to over 3 million active users across the globe. However, with this growth came an increase in fraudulent listings and spambot attacks, threatening the integrity of their platform. The company's goal is to maintain platform integrity and customer trust while continuing to grow and expand into new markets. They aim to provide an abuse-free user experience and ensure that their hosts and users are happy and engaged. Universe.com is also looking to explore new opportunities globally while remaining a leader in the events marketplace.
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Universe decided to partner with Sift to provide a holistic fraud and abuse solution. They chose Sift over other vendors due to the compelling testimonials from Sift’s customers and its global network of 6,000+ customers. Sift's Content Abuse Prevention and Digital Trust Platform were implemented to evaluate host and user behavior and posted content to ensure an abuse-free user experience. Sift's solution also helps Universe to detect bad users, stopping them before they can even post content. The onboarding process took only a week to get the model set up so most review could be automated. Sift's machine learning model allows Universe to be proactive in fighting spam, keeping up with the ever-evolving types of spam.
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Universe can now proactively prevent fraud before malicious content is posted.
Universe was able to reduce their reliance on the engineering team for abuse and fraud management by almost 100%.
Universe has greater confidence in entering new markets. Sift’s machine learning technology is language agnostic, which means language patterns associated with content abuse can be easily detected across dialects.
10x Faster at resolving attacks
100% Elimination of reliance on engineering team for review
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