Showpad Accelerates Data Maturity to Unlock Innovation Using Amazon QuickSight

Founded in 2011 and with offices around the world, Showpad provides a single destination for sales representatives to access all sales content and information, along with coaching and training tools to create informed, upskilled, and trusted buying teams. The platform also provides analytics and insights to support successful information sharing and fuel continuous improvement. In 2021, Showpad decided to take the next step in its data evolution and set forth the vision to power innovation, product decisions, and customer engagement using data-driven insights. This required Showpad to accelerate its data maturity by mindfully using data and technology holistically for its customers.

But the company’s legacy BI solution and data were fragmented across multiple tools. “If each tool tells a different story because it has different data, we won’t have alignment within the business on what this data means,” says Jeroen Minnaert, head of data at Showpad. Consistency, ownership, and insufficient data access were also challenges for Showpad across its targeted user base due to a complex BI access process, licensing issues, and insufficient education. Showpad wanted to bring all the data into a unified interface, democratize that data, and drive and unlock innovation through advanced insights.

The company already used AWS in other aspects of its business and found that using Amazon QuickSight would meet all its BI and reporting needs with seamless incorporation into the AWS stack. “We chose Amazon QuickSight because of its embedded analytic capabilities, serverless architecture, and consumption-based pricing,” says Minnaert.

After choosing QuickSight as its solution in November 2021, Showpad took on two streams of development: migrating internal organization-wide BI reporting and building in-product reporting using embedded analytics. Showpad worked closely alongside the QuickSight team for a smooth rollout.

On the internal reporting front, the data team took a “Working Backwards” approach to make sure it had the right process before going all in with its existing dashboards. The company also reimagined its data pipeline and architecture, creating a portable data layer by decoupling the data transformation from visualization, machine learning, or one-time querying tools and centralizing its business logic. The portable data layer facilitated the creation of data products for varied use cases, made available within various tools based on the need of the consumer.

After determining an approach and building the foundation, the team wanted to scale. But with 70 dashboards with over 1,000 visuals and over 1,000 tables ingesting data from more than 20 data sources, the team decided to prioritize the migration order. The company started with dashboards that had the fewest dependencies and worked up to customer success and marketing dashboards that combined product and engineering and revenue operations data. Showpad launched the first dashboard set in April 2022 and completed its internal BI migration by the end of 2022. As of January 2023, Showpad’s QuickSight instance includes over 2,433 datasets and 199 dashboards.

For the second work stream of in-product customer reporting, Showpad released its first version of QuickSight reporting to customers in June 2022. “We went through user research, development, and beta tests in a span of 6 months, which was a big win for us,” says Minnaert. With the foundational architecture in place, shipping to a customer can happen in a few sprints, focusing on iterating and fine-tuning insights instead of solution engineering. The company can then follow up with tailor-made reporting for each customer using the same data so that it tells a consistent story.

Showpad users can quickly prototype reports in a well-known environment—building reports using QuickSight and then testing them with customers—and have increased dashboard development activity by three times across the organization. “After we settle on reports or dashboards, it does not take much engineering effort to bring them to production,” says Minnaert. After a dashboard is agreed on, it can go through Showpad’s automated dashboard promotion process that can take an idea from development to production in weeks, not months. Showpad’s users and customers also benefit from performance gains with 10 times increased speed when using SPICE (Super-fast, Parallel, In-memory Calculation Engine), which is the robust in-memory engine that QuickSight uses. It takes only seconds to load dashboards.

Using the serverless QuickSight, Showpad expects to see a three-times increase in projected return on investment in 2023. It can deprecate custom reporting, infrastructure, and multiple tools with the new data architecture and QuickSight. “The serverless model was also compelling because we did not have to pay for server instances nor license fees per reader. On Amazon QuickSight, we pay for usage. This makes it easy for us to provide access to everyone by default,” says Minnaert. And by providing dashboard and report building across 600 employees, including analysts and nontechnical users, Showpad reduced the time to build and deliver insights from months to weeks.