Download PDF
StubHub's Battle Against Bots: Protecting Content, Preventing Account Takeover, and Ensuring Accurate Conversion Rates
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Robotic Process Automation (RPA)
Applicable Industries
- Education
- Equipment & Machinery
Applicable Functions
- Procurement
- Warehouse & Inventory Management
Use Cases
- Chatbots
- Traffic Monitoring
Services
- Cybersecurity Services
- Data Science Services
The Challenge
StubHub, a leading ticket marketplace, was facing a series of challenges due to the activities of malicious bots. These bots were scraping pricing and inventory data from StubHub's website, selling this proprietary information to competitors, and reposting it on other platforms. This not only led to StubHub's pricing being undercut but also resulted in the theft and misuse of customer accounts. The problem was further exacerbated by the availability of stolen login information and password reuse, which facilitated account takeovers leading to buyer and seller fraud. Additionally, StubHub's site was under constant attack from Advanced Persistent Bots (APBs) that could imitate human-like interactions and blend in with human traffic. These bots were causing a significant increase in site traffic, leading to skewed analytics and artificially low conversion rates.
About The Customer
StubHub, an eBay company, is one of the world's largest ticket marketplaces. Founded in 2000 and headquartered in San Francisco, California, StubHub's mission is to help fans find fun. The platform enables fans to buy and sell tens of thousands of tickets whenever they want, through both desktop and mobile experiences, including apps for iPhone, iPad, Apple Watch, and Android. StubHub's accounts hold significant value due to the ease and speed of purchasing and selling tickets on its platform, making it a prime target for cyber thieves.
The Solution
To combat these challenges, StubHub partnered with Imperva, a cybersecurity company. Imperva implemented a series of measures to protect StubHub's proprietary information and customer accounts. They proactively blocked persistent web scraping campaigns, thereby protecting pricing and inventory information and maintaining StubHub's competitive pricing advantage. To prevent account takeovers, Imperva prevented credential stuffing bots from accessing the site, which significantly lowered fraud and improved StubHub's brand reputation among customers. To tackle the issue of APBs, Imperva used advanced fingerprinting technology, behavioral analysis, and machine learning to distinguish between bot and human traffic. They also implemented dynamic access controls to further secure the site. To correct skewed conversion tracking, Imperva blocked 99.9% of bad bots, which lowered page view traffic by 50% and resulted in higher conversion rates and improved sales funnel reporting.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Smart Water Filtration Systems
Before working with Ayla Networks, Ozner was already using cloud connectivity to identify and solve water-filtration system malfunctions as well as to monitor filter cartridges for replacements.But, in June 2015, Ozner executives talked with Ayla about how the company might further improve its water systems with IoT technology. They liked what they heard from Ayla, but the executives needed to be sure that Ayla’s Agile IoT Platform provided the security and reliability Ozner required.
Case Study
IoT enabled Fleet Management with MindSphere
In view of growing competition, Gämmerler had a strong need to remain competitive via process optimization, reliability and gentle handling of printed products, even at highest press speeds. In addition, a digitalization initiative also included developing a key differentiation via data-driven services offers.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Premium Appliance Producer Innovates with Internet of Everything
Sub-Zero faced the largest product launch in the company’s history:It wanted to launch 60 new products as scheduled while simultaneously opening a new “greenfield” production facility, yet still adhering to stringent quality requirements and manage issues from new supply-chain partners. A the same time, it wanted to increase staff productivity time and collaboration while reducing travel and costs.
Case Study
Integration of PLC with IoT for Bosch Rexroth
The application arises from the need to monitor and anticipate the problems of one or more machines managed by a PLC. These problems, often resulting from the accumulation over time of small discrepancies, require, when they occur, ex post technical operations maintenance.
Case Study
Robot Saves Money and Time for US Custom Molding Company
Injection Technology (Itech) is a custom molder for a variety of clients that require precision plastic parts for such products as electric meter covers, dental appliance cases and spools. With 95 employees operating 23 molding machines in a 30,000 square foot plant, Itech wanted to reduce man hours and increase efficiency.
