Real estate technology platform implements SaaS Intelligence

Client background

The client is a real estate information and technology platform that provides commercial, geographical, spatial and environment building data. Their customers include commercial and government agencies requiring definitive real estate data and powerful workflow solutions including brokers, developers, investors, lenders, insurers, technology providers, environmental consultants and valuation professionals.

The business challenge

Like so many other SaaS companies, this business’s finance department was reliant on manual, time consuming processes to record and analyze their customer subscription activity data in Excel on a monthly basis. Subscription data was pulled from their CRM system, which often contained unreliable subscription details and categorizations input by their sales organization. This required them to then extract contract details and revenue activity from their Sage Intacct ERP system to reconcile, decode and rectify the subscription data in an attempt to maintain the trustworthiness of their Excel model. At their scale, it necessitated a team of specialized analysts to manage and maintain a litany of spreadsheets just to produce a consolidated, high-level Annual Recurring Revenue (ARR) analysis.

When it came to reporting their recurring revenue (MRR/ARR) activity and SaaS metrics to executive leadership, the process required dozens of hours each month and the result was merely a historical view and a broad, directional analysis of their subscription business. The finance team still couldn’t pinpoint the underlying drivers of recurring revenue growth or analyze trends by critical subscription segmentation variables such as customer, segment, industry and product.

The client knew they needed to upgrade from Excel spreadsheets to a business intelligence tool that could shift their team’s focus from data management to advanced data analytics. However, the tool had to be a purpose-built SaaS industry solution that integrated with their Sage Intacct ERP system and provided configurability to adeptly manage the complexities of their subscription business now and into the future (e.g., distinct add-on, cross-sell, upsell, and uplift tracking; direct customer and channel sales; multi-entity and multi-currency consolidations; self-service reporting; etc.). Most importantly, the business intelligence tool had to deliver in-depth, reliable and real-time metrics to empower the business with insights to support rapid, data-driven decisions in response to evolving market signals.

Strategy and solution

After reviewing various business intelligence solution alternatives, they enthusiastically moved forward with SaaS Intelligence by Baker Tilly. The client was impressed by the power of application’s intelligence engine, and its ability to automatically parse customer’s subscription activity in real-time, and contextualize the impact into discrete, detailed categories that revealed specific drivers of recurring revenue growth. It was an easy decision to make once they learned the business intelligence tool’s breadth and depth of functionality, configurability, out-of-the-box dashboards and self-service reporting on top of having been built directly on the Sage Intacct ERP system.

With the guidance of Baker Tilly’s application and industry experts, SaaS Intelligence was installed and configured to meet their business processes and reporting needs. As the application consumed and processed the existing subscription data in their Sage Intacct ERP Order Entry and Contracts subledgers, they were able to immediately see the unique, hidden insights that the intelligence engine was uncovering – their dashboards displaying a new vantage of their customer subscription activity and SaaS metrics trends.

The client utilizes SaaS Intelligence to automate their reporting process and empower stakeholders with on-going visibility into their subscription contracts and key performance indicators (KPIs). Unburdening the finance team from these manual efforts and providing them with more detailed MRR/ARR activity data and crucial SaaS metrics (e.g., Net & Gross Revenue Retention [NRR / GRR], Renewal Rates, Churn Rates, Customer Acquisition Cost [CAC], Customer Lifetime Value [CLTV], etc.) has allowed their analysts to concentrate their efforts on advanced data analytics instead of data management and ad-hoc reporting requests. Analysts can now segment and explore their customer subscription data and metrics to identify, monitor and escalate emerging trends – equipping business leaders with the information necessary to respond to discovered market opportunities and risks.