实例探究 > Pipeline Insight Case Study: YARCDATA

Pipeline Insight Case Study: YARCDATA

公司规模
1,000+
地区
  • America
国家
  • United States
产品
  • Pipeline Insight
  • Salesforce.com
技术栈
  • Salesforce
  • Spreadsheets
实施规模
  • Enterprise-wide Deployment
影响指标
  • Cost Savings
  • Customer Satisfaction
  • Productivity Improvements
技术
  • 分析与建模 - 预测分析
  • 应用基础设施与中间件 - 数据可视化
  • 功能应用 - 企业资源规划系统 (ERP)
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
  • 软件设计与工程服务
  • 系统集成
关于客户
YarcData LLC, a subsidiary of Cray Inc., is based in the San Francisco Bay Area. The company specializes in enabling enterprises to gain better business insights by discovering unknown relationships in Big Data. Cray, the parent company, is renowned for its advanced supercomputers used by scientists, engineers, and various industries, including academia and government sectors worldwide. YarcData's mission is to help clients uncover high-value relationships within their data, leveraging the power of Big Data analytics to drive business decisions and strategies.
挑战
YarcData faced challenges in determining the conversion rates of prospects into customers through various marketing efforts and identifying the source of its leads. They wanted to know the percentage of opportunities in the sales pipeline that came from different marketing events, web downloads, or self-sourced sales opportunities. Additionally, they needed the ability to drill down into the data to guide where to allocate more marketing dollars based on the success of previous efforts. Previously, YarcData relied heavily on spreadsheets and Salesforce.com reports, which made it difficult to extract the exact information they needed. This reliance on spreadsheets represented about 70% of their data presentation.
解决方案
When Todd Quinn joined YarcData in January 2013 in product marketing, he encountered the initial implementation of Marseli's Pipeline Insight Marketing Analytics. This tool provided YarcData with end-to-end analytics for every nurture and sales stage, linking each campaign and tactic-based inquiry to revenue reporting. With Pipeline Insight, YarcData could identify which marketing-generated leads were successfully converted into sales, view full funnel and pipeline conversion, and analyze velocity and usage metrics for both historical and forecasted periods. The data for each report was extracted from Salesforce, but the value of Pipeline Insight lay in its ability to present multilayered and dynamic insights in a single dashboard. Users could change views and reveal specific information through drop-down options. Beyond saving time, Pipeline Insight increased user adoption with its simple and concise screen views, showing key metrics that could be filtered to identify active opportunities by vertical or sales rep, velocity charts for marketing-related opportunities, conversion rates, and other key factors. This deeper dive into the data and the uniform, centralized view significantly improved over spreadsheet interpretations, giving management greater confidence in the numbers.
运营影响
  • Pipeline Insight provided YarcData with end-to-end analytics for every nurture and sales stage, linking each campaign and tactic-based inquiry to revenue reporting.
  • The tool allowed YarcData to identify which marketing-generated leads were successfully converted into sales and view full funnel and pipeline conversion.
  • Users could quickly see multilayered and dynamic insights in a single dashboard, with drop-down options to change views and reveal specific information.
  • The simple and concise screen views increased user adoption, showing key metrics that could be filtered to identify active opportunities by vertical or sales rep, velocity charts for marketing-related opportunities, conversion rates, and other key factors.
  • The uniform, centralized view provided by Pipeline Insight gave management greater confidence in the numbers, enabling better business decisions and more intelligent allocation of resources based on sales performance.
数量效益
  • 70% reduction in reliance on spreadsheets for data presentation.
  • Increased user adoption of the analytics tool.
  • Improved allocation of marketing resources based on sales performance.

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