The SaaSquatch story
SaaSquatch offers a platform that lets companies build multichannel reward campaigns and refer-a-friend programs. It helps businesses reward customers for making referrals, and provides them with analytics tools that let them see how referrals are performing.
Recently, SaaSquatch was faced with a fast-approaching deadline from the Financial Accounting Services Board (FASB) for reporting company finances. Because SaaSquatch is a subscription business, the company must report revenue according to when it earns the money, not when it collects it. SaaSquatch also wanted to uncover metrics that would help it report on business performance to executives, investors, shareholders, and employees, and take measures to improve the company, such as reduce customer churn rates.
The company needed a business intelligence (BI) tool to solve both problems, which meant it first needed a data warehouse and a way to populate it. After testing half-a-dozen potential solutions, it chose Google BigQuery to host its data warehouse. BigQuery was affordable and simple to set up and use, and could scale as SaaSquatch’s data needs grew.
To import data into BigQuery, the company turned to Stitch, whose data pipeline service enables customers to stream data from databases, SaaS tools, ad networks, and more, cutting the time it takes developers to provision a data warehouse from weeks to minutes.
Meeting the FASB deadline
SaasQuatch used Stitch’s data integrations to populate its warehouse by importing data from multiple sources, including SaaSquatch’s own financial data, its website performance metrics, Salesforce, and public information about international exchange rates. Stitch’s ability to easily import data was key to helping SaaSquatch meet the FASB deadline. Logan Volkers, the company’s co-founder and chief operating officer, says, “With Stitch, you don’t need a big data science team to load data into your data warehouse.” Stitch let SaaSquatch consolidate data into BigQuery and then use a BI tool to run queries to find the answers it needed.
Once it had a data warehouse and data pipeline in place, SaaSquatch was able to get results that helped it comply with the FASB reporting deadline. In a single afternoon, it audited months of its revenue, saving the company time and money. The alternative would have been to manually export and manipulate data in Excel, which would have made auditing and ad hoc analysis difficult and time-consuming, Volkers says, or to spend tens of thousands of dollars on specialized analytics tools or additional engineering resources.
Thanks to Stitch and BigQuery we’ve gone from insights updated quarterly to data updated within the hour.
Co-Founder and COO, SaaSquatch
Improving business performance
SaaSquatch also began using this new tech stack to analyze key performance data such as churn rate, success rates of sales calls, and how long it takes to implement referral programs. It uses these metrics for financial reporting, seasonal forecasting, and customer behavior analysis. The metrics are shared with executives and employees so they can better understand how the business is being run, and fix what’s not working well.
SaaSquatch now has an accurate view of customer activities, which helps reduce churn. It analyzes customer behavior and uses that information to improve the product interface and feature set. “We’ve gotten a lot more clarity and certainty around how our business works,” Volkers says.
“As a startup, we need to manage our burn and plan for the future,” Volkers says. “Now we’re able to accurately forecast and report on our cash flows and revenue alongside other business metrics. Thanks to Stitch and BigQuery we’ve gone from insights updated quarterly to data updated within the hour.
“Using the combination of Stitch and BigQuery, we’ve become a data-oriented company, which helps us improve the way we work and ensures we better meet our customers’ needs. Stitch provides the magic that makes BigQuery work, because Stitch is what gets stuff into BigQuery.
“The time to get value using Stitch and BigQuery was incredibly fast; we were set up and querying our data in under a day. The combination of Stitch and BigQuery answered our data needs before other vendors even answered our sales inquiries,” says Volkers.
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