To tackle the complexity of customer data, ConstructConnect facilitated a collaborative approach to data analysis that made insights accessible—and actionable—to stakeholders throughout the organization.
Big Data and the Subscription Business Model are twin engines that have transformed how business gets done over the past two decades. Digitalization and the power of the cloud have enabled high tech companies to transition from selling products and licenses to Software-as-a-Service (SaaS) offerings available through subscriptions. And these subscriptions are continuously gathering massive amounts of data about their customers. Big Data, and more specifically, Big Data Analysis, gives subscription companies the means to process that data more quickly than ever before.
But how much of that customer information is being translated into actionable insights that actually improve a company’s business? In other words, how much of it is just data for data’s sake?
The question is top of mind for the leaders of many subscription-based businesses. A Forrester study found that 60% of executives are not very confident in their data and analytics insights. Many of these companies are struggling because their legacy systems weren’t built to generate subscription insights. Having actionable insights is critical to driving business performance.
Executives looking for a data analysis blueprint would do well to study ConstructConnect, an SaaS platform for the construction industry. The company is a leading provider of construction information and technology solutions in North America. Their subscription service helps their customers, who are primarily trade contractors, general contractors, and building product manufacturers, identify new projects to bid on or opportunities to sell their products or services, collaborate and share that information with their teams, and estimate their job costs to successfully bid on those projects.
As their subscription offerings began generating huge amounts of data, ConstructConnect realized they could apply lessons learned from preconstruction to data analysis. The mistake many subscription companies make is to silo customer data within one part of the organization. All too often, IT and a small team of overworked data engineers become responsible for managing this hugely important asset. ConstructConnect wanted to develop a data analysis solution that allowed the entire organization to access the data and provide input.
To facilitate a collaborative data analysis model, ConstructConnect built a tech stack based around using an Extract, Load, and Transform (ELT) methodology executed through a cloud data warehouse. ELT allows a wide range of data types to be processed very quickly and to scale up with very little lead time.
The company has two core upstream systems of record, which are tightly integrated: Salesforce for customer relationship management (CRM); and Zuora for invoicing subscription management and capturing customer history. Zuora in particular produces a wide range of data types, including invoicing, payment, product, refund, and subscription term information, which can proliferate and change very quickly. Using a cloud data warehouse gives ConstructConnect the flexibility and scalability to handle this variability.
“What we’re trying to do with ELT is get the data modeled in the way that is most efficient for analytics and enriched with other sources of data, especially getting the Zuora data integrated with Salesforce data,” explains Buck Brody, Chief Financial Officer and head of ConstructConnect’s finance, accounting, and data analytics teams.
Moving IT and the data engineering team out of a gatekeeping role had several advantages. First, it was faster because it avoided bottlenecks at the data engineer level. The speed allowed the company to react more quickly to changing circumstances so they could adjust products, pricing, and processes from month to month as the market and their customers demanded.
A less obvious but perhaps even more important result was the ability to get buy-in across the organization, because stakeholders in various functions were able to clearly see what the data said and why it mattered.
“By using a modern cloud data warehouse, like a BigQuery or a Snowflake or Redshift, you can get your analysts, not just data engineers, but your financial analysts and data analysts, people that have deep subject matter expertise, much more involved in the modeling of the data and give them more transparency,” explains Brody.
Ultimately, data analysis optimization resulted in tangible improvements to the way the company operated. In particular, ConstructConnect was able to elucidate how various business practices impacted customer lifetime value (CLV). For example, Sales realized that outbound calling activity was generating customers that stayed with the company 58% longer than customers acquired through paid search. As a result, they reallocated resources toward the outbound calling acquisition channel to achieve a greater ROI.
Finance was also able to improve operations based on the CLV data. Their analysis revealed that customers with annual payment terms retained significantly better than those on quarterly terms. As a result, the company incentivized driving customers toward annual contracts.
Those two initiatives alone led to a significant increase in bookings and retention for ConstructConnect. Ultimately, the process produced actionable insights by fostering transparency. “We really showed our internal stakeholders how we came to the conclusions,” says Brody. “And in the process, we educated the organization on how these metrics like CLV work.”
“My advice for subscription companies is to implement best-in-class systems across your tech stack that are accessible to everyone. Collaboration is the key to managing data complexity.”