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How Revenue.io Transformed Salesforce Data Into Actionable GTM Insights
技术
- 分析与建模 - 预测分析
- 应用基础设施与中间件 - 数据交换与集成
- 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
- 系统集成
挑战
Analyzing a Rapidly Expanding Product Line\nIt’s easier than ever for businesses to diversify their product lines through software as a service (SaaS) subscriptions. The results can be great—but they need to be measured. This is especially true for teams like Revenue.io that have aggressive product expansion strategies.\nAs Revenue.io expanded from a single-point solution to a platform over the course of two years, they laid out a clear roadmap to optimize new customer acquisition. They onboarded new customers to their primary RingDNA product while methodically cross-selling other emerging product lines. Quickly analyzing new business pipelines while assessing opportunities to attach existing cohorts to other products became increasingly complex.\nFinance leaders could pull customer and deal information from Salesforce to run the necessary analyses. But, given their SaaS model, it often required up to 12 separate reports just to get a trended view of ARR. Collecting this financial information was too time-consuming, forcing the team to eventually revert to Excel to calculate the 30+ business-critical metrics they needed.\nFor Revenue.io to fulfill its acquire and expand strategy, it needed a reliable system to do two things: first, centralize Salesforce data for financial analysis. Second, turn all that data into actionable, SaaS-optimized insights for sales and product leaders.
关于客户
Revenue.io powers high-performing teams with real-time guidance. By surfacing and recommending what works best, Revenue.io enables hundreds of customers like HPE, Nutanix, and AWS to deliver predictable results and optimize their entire revenue operation. Much like the company’s focus on accelerating meaningful conversations among sales leaders, the finance team at Revenue.io wanted a system that powered strategic growth conversations based on a rapidly expanding product line.
解决方案
Transforming Salesforce Data into Strategic Insights\nRevenue.io needed a dedicated financial analysis tool to replace manual workflows for pulling data from Salesforce and digging into the numbers. They were looking to implement a more flexible platform to help take its product expansion strategy to the next level and they were drawn for Mosaic for two main reasons:\n• The ability to seamlessly connect to Salesforce\n• The platform’s ability to turn static CRM data into actionable, real-time insights for driving strategic decision-making\nAfter implementing Mosaic, the team quickly created 12 powerful self-serve dashboards, saving them 32 hours per month from manual efforts.\nThe dashboards now enable them to pull through pipeline metrics to help sales leaders forecast revenue more accurately with deep insight into new customer deal stages, account names, ACV, and renewal bookings. Trended reports help the team better predict the likelihood of net new ARR and carefully manage renewals.\nTracking sales rep productivity was also a critical part of Revenue.io’s expansion efforts. The finance team wanted visibility into how quickly sales reps could close deals—specifically for its Moments and Guided Selling products. By connecting Mosaic and Salesforce, Revenue.io was able to benchmark its own sales cycle and test how changes to their own product could improve the products they offered to others.\nFinally, to better understand upsell and cross-sell opportunities, the team now relies on a series of pre-loaded metrics that give them visibility into hard-to-come-by cohort data. Being able to easily analyze distinct audiences by product line, attach rates, and customer lifetime value in just a few clicks improves their decision-making, further accelerating their expansion strategy. The finance team can analyze the performance of individual products, understand the most common combinations of products, and effectively engage sales to help grow average customer value.
运营影响
数量效益
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