Upwork needed a faster way to diagnose the performance of their global jobs marketplace
公司规模
1,000+
国家
- United States
产品
- Sisu
技术栈
- Machine Learning
- Operational Analytics
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
- Revenue Growth
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
- 分析与建模 - 实时分析
适用行业
- Professional Service
- Software
适用功能
- 商业运营
- 销售与市场营销
服务
- 数据科学服务
- 系统集成
关于客户
Upwork is a global online marketplace that connects freelancers with clients. With a mission to increase economic opportunity for freelancers and organizations alike, Upwork serves tens of millions of people worldwide, offering them freedom and flexibility in their work. The platform supports over 5 million companies posting jobs and a community of 12 million freelancers. Upwork's Finance and Strategic Planning team faced challenges in forecasting due to the complexity and diversity of the marketplace, which required a more efficient way to diagnose performance and understand key metrics.
挑战
Despite their global reach, the Upwork team runs lean. But with over 5 million companies posting jobs and a community of 12 million freelancers, the team struggled to diagnose changing conditions, quantify the impact to the business, and quickly recommend a clear course of action. The team had a rich set of dashboards that showed when key metrics like revenue and job fill rates changed, but understanding why those KPIs fluctuated required hours or weeks of manual investigation in spreadsheets and BI tools.
解决方案
The Upwork team implemented Sisu, an operational analytics platform powered by machine learning, to diagnose why their critical metrics were changing. Sisu's approach allowed the team to get answers to their toughest business questions quickly and made complex analysis easy and accessible. By continuously monitoring all organizational information, Sisu automatically recommended meaningful facts in seconds and tracked changes to the data over time. This enabled the Upwork team to respond to new inquiries in minutes instead of days and make more data-informed decisions in partnership with the business. Additionally, the team used Sisu to analyze what makes a successful job posting for freelancers and enterprises, sharing these insights with product and client support teams to grow the marketplace.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Factor-y S.r.l. – Establishes a cost-effective, security-rich development environment with SoftLayer technology
Factor-y S.r.l., a web portal developer, was faced with the challenge of migrating its development infrastructure to a reliable cloud services provider with highly responsive technical support. The company needed a solution that would not only provide a secure and reliable environment but also support its expansion by providing resources to create and deliver innovative offerings.
Case Study
UBM plc: Taking the pulse of the business and engaging employees with a far-reaching strategic transformation
UBM, a leading global events business, was undergoing a significant strategic transformation named 'Events First'. As part of this transformation, the company was preparing to complete the largest acquisition in its history - Advanstar, a US-based events and marketing services business valued at more than USD970m. The company faced the risk of human capital flight if it was unable to effectively engage top talent with the new strategic direction. UBM needed to make significant structural, process and systems changes, uniting its previously autonomous regional businesses. The challenge was to ensure all of its employees were engaged and aligned with the new future vision.
Case Study
Darwin Ecosystem: Accelerating discovery and insight through cutting-edge big data and cognitive technologies
Darwin Ecosystem was founded with a unique vision of harnessing chaos theory mathematics to uncover previously hidden connections in unstructured data. The company’s algorithms can look at all the data generated by any source (such as news, RSS feeds and Twitter), and analyze how a specific set of concepts within that data are evolving over time. This is particularly valuable in situations such as business and competitive intelligence, social research, brand monitoring, legal discovery, risk mitigation and even law enforcement. A common problem in these areas is that a regular web search will only turn up the all-time most popular answers to a given question – but what the expert researcher is actually interested in is the moment-tomoment evolution of the data available on that topic. Darwin’s algorithm is computationally intensive, and the sources of data it correlates can be vast. To bring its benefits to a larger commercial audience, Darwin needed to find a way to make it scale.
Case Study
Wittmann EDV-Systeme launches IT monitoring services
Small and medium-sized businesses often lack the know-how and resources required for thorough IT system monitoring. Wittmann EDV-Systeme wanted to launch a solution to plug the gap – enabling it to improve its own competitiveness and that of its customers. IT landscapes are becoming ever more complex and outsourcing is gaining popularity, IT systems must nonetheless remain easy-to-use and extremely reliable at all times. Automated, round-the-clock system monitoring therefore represents an immensely valuable proposition for companies: downtime for business-critical applications can be avoided, and IT systems remain available at all times.
Case Study
Zend accelerates, simplifies PHP development
Zend Technologies, a major contributor to the PHP open source community, needed to keep pace with emerging trends such as mobility, agile development, application lifecycle management and continuous delivery. The company needed to provide the right tools to the worldwide community of PHP developers. The challenge was to support enterprise-class capabilities from end to end, including mobile, compliance and security. The pace of business required developers to show results fast across a variety of devices without compromising quality or security.
Case Study
Delivering modern data protection with cloud scale backup from Cobalt Iron and IBM
Organizations are struggling to modernize their legacy data protection environments in the face of growing demands around new infrastructure, new applications, and budget consolidation. Virtualization and modern application development processes have significantly outgrown legacy backup architectures. In response, infrastructure teams have created multiple backup solution types to handle the varying SLAs (performance, scale, cost) required by their business sponsors. However, the sheer number and variety of solutions in this uncontrolled expansion creates huge amounts of work, threatening to overwhelm the IT team in many organizations. Today, developers may add new applications and virtual server instances by the hundreds per day without accounting for the restrictions of the existing backup infrastructure. They leverage the cloud for immediate compute and storage resources, yet rarely communicate succinctly with corporate IT to ensure that the appropriate data protection services are in place.
