All posts by Shruthi Panicker

Showpad accelerates data maturity to unlock innovation using Amazon QuickSight

Post Syndicated from Shruthi Panicker original https://aws.amazon.com/blogs/big-data/showpad-accelerates-data-maturity-to-unlock-innovation-using-amazon-quicksight/

Showpad aligns sales and marketing teams around impactful content and powerful training, helping sellers engage with buyers and generate the insights needed to continuously improve conversion rates. In 2021, Showpad set forth the vision to use the power of data to unlock innovations and drive business decisions across its organization. Showpad’s legacy solution was fragmented and expensive, with different tools providing conflicting insights and lengthening time to insight. The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers.

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight, a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers. Showpad migrated over 70 dashboards with over 1,000 visuals. They have rolled out the solution to all its 600 employees, increased dashboard development activity by three times, and reduced dashboard turnaround time from months to weeks. Showpad also launched dashboards and reports to over 1,300 customers worldwide, providing access to tens of thousands of users across all its customers.

Streamlining data-driven decisions by defragmenting the data and reporting architecture

Founded in 2011, dual headquartered in Belgium and Chicago 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 as a company by mindfully using data and technology holistically to help its customers.

But the company’s legacy BI solution and data were fragmented across multiple tools, some with proprietary logic. “Each of these tools were getting data from a different place, and that’s where it gets difficult,” says Jeroen Minnaert, head of data at Showpad. “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.” Showpad also struggled with data quality issues in terms of consistency, ownership, and insufficient data access across its targeted user base due to a complex BI access process, licensing challenges, and insufficient education.

Showpad wanted to unify all the data into a single unified interface through a data lake, democratize that data through a BI solution such that autonomous teams across the company could effectively use data, and drive and unlock innovation in the company through advanced insights data, artificial intelligence, and ML. The company already used AWS in other aspects of its business and found that QuickSight would not only meet all its BI and reporting needs with seamless integrations into the AWS stack, but also bring with it several unique benefits unlike incumbents and other tools evaluated. “We chose QuickSight because of its embedded analytic capabilities, serverless architecture, and consumption-based pricing,” says Minnaert. “Using QuickSight to launch interactive dashboards and reporting for our customers, along with the ability for our customer success teams to create or alter dashboard prototypes on our internal-facing QuickSight instance and then promote those dashboards to customers through the product, was a very compelling use case.”

QuickSight would help local data stewards, who weren’t technical but knew the use cases intimately, to create their own dashboards and prototype them with their customers before promoting them through the product. “The serverless model was also compelling because we did not have to pay for server instances nor license fees per reader. With QuickSight, we pay for usage. This makes it easy for us to provide access to everyone by default. This is a key pillar in our ability to democratize data,” says Minnaert.

A screenshot of Showpad's Platform/Adoption dashboard

Architecting a portable data layer and migrating to QuickSight to accelerate time to value

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 to have a smooth rollout. The company involved members of the QuickSight team in its internal communications and set up meetings every 2 weeks to resolve difficult issues quickly.

On the internal reporting front, the data team took a “working backwards” approach to make sure it had the right approach before going all in with all existing dashboards. Showpad selected five difficult and complex dashboards and took 3 months to explore various possibilities using QuickSight. For example, the team determined that user log-in would be automated with single sign-on and Okta and built a plan for assets organization, asset promotion, and access controls. The company also used the opportunity to reimagine its data pipeline and architecture. A key architectural decision that Showpad took during this time was to create a portable data layer by decoupling the data transformation from visualization, ML, or ad hoc 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—be it a business analyst, data scientist, or business user.

After the solution approach was decided on and the foundation was built, the team wanted to scale. However, with 70 dashboards with over 1,000 visuals with varying levels of complexities, including proprietary logic unique to certain tools, and data from over 1,000 tables ingesting data from over 20 data sources, the team decided to take a measured approach to the migration. The entire data team of 20 people were “all on hands on deck” for the project.

First, Showpad created a landscape of all the dashboards, connecting data sources and dependencies before prioritizing the migration order. The company decided to start with dashboards with the fewest dependencies, like product and engineering dashboards that had a single data source, followed by revenue operations dashboards with a couple of data sources, and lastly with customer success and marketing dashboards that combined product and engineering and revenue operations data. After migration was complete, Showpad validated all the numbers and worked with business stakeholders for quality assurance. It launched the first set of dashboards in April 2022, followed by customer success and marketing dashboards in July 2022. As of January 2023, Showpad’s QuickSight instance includes over 2,433 datasets and 199 dashboards.

Showpad also achieves benefits for its customers by using QuickSight to deliver a wide variety of insights, including usage dashboards, industry comparisons, user comparison, group comparison, and revenue attribution. On the second workstream of in-product customer-facing 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 fast turnaround and a big win for us,” says Minnaert. And Showpad aims to further accelerate the turnaround time to make a report and ship it to a customer.

With the foundational architecture now in place, shipping to a customer can happen in a few sprints, with most of the time spent on iterating and fine-tuning insights instead of engineering a scalable reporting solution. Showpad can also improve the insights it offers to customers. “Using QuickSight in our product makes it a powerful tool,” says Minnaert. “We can launch reporting for our customers so that they can look at and interpret data by themselves.” Showpad can then follow up with tailor-made reporting for each customer using the same data so that it tells a consistent story.

After a dashboard is agreed on, the dashboard can go through Showpad’s automated dashboard promotion process that can take an idea from development to production to a smile on a customer’s face in weeks, not months.

A screenshot of their Shared Space engagement dashboard

Unlocking innovation with self-service BI and rapid prototyping

By providing dashboard and report building to analysts and nontechnical users, Showpad drastically reduced overall turnaround time to build and deliver insights, down from months to weeks. Showpad also increased dashboard development activity by three times across the organization.

Showpad users can quickly prototype reports in a well-known environment—building reports using QuickSight, and then testing them with customers by helping customers understand how the reporting would look and function. “After we settle on reports or dashboards, it does not take much engineering effort to bring them to production,” says Minnaert. “We can make a lot of innovation happen by quickly prototyping and bringing validated prototypes to production.” 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.

Because QuickSight is serverless and uses a session-based pricing model, Showpad expects to see cost savings. By paying per use, Showpad can easily provide access to all its users and customers without purchasing expensive per-reader licenses. Showpad also doesn’t need to pay for server instances or maintain infrastructure for BI. In addition, Showpad can deprecate custom reporting, infrastructure, and multiple tools with the new data architecture and QuickSight. “Much of our cost savings will come from being able to deprecate the custom reporting that we’ve made in the past,” says Minnaert. “The custom reporting used a lot of infrastructure that we no longer need to maintain.” Showpad expects to see a three times increase in projected return on investment in the upcoming year.

Showpad completed its internal BI migration to QuickSight by the end of 2022. Showpad also continues to expand the in-product reporting while continuing to optimize performance for the best customer experience. Showpad hopes to further reduce the time it takes to load a dashboard to under 1 second.

In conjunction with Showpad’s new portable data layer, QuickSight helps users of all types across its organization and customers self-serve data and insights rapidly. Everyone in Showpad gets access to data and insights the day they onboard with Showpad. To make self-service even easier, Showpad will soon launch embedded Amazon QuickSight Q so anyone can ask questions in natural language and receive accurate answers with relevant visualizations that help them gain insights from the data. By helping business users and experts rapidly prototype dashboards and reports in line with user and customer needs, Showpad uses the power of data to unlock innovation and drive growth across its organization. “QuickSight has become our go-to tool for any BI requirement at Showpad—both internal and external customer facing, especially when it comes to correlating data across departments and business units,” says Minnaert.

Get started with QuickSight

Migrating to QuickSight enabled Showpad to streamline data and insights access across teams and customers and reduced overall turnaround time to build and deliver insights from months to weeks.

Learn more about unleashing your organization’s ability to accelerate revenue growth with Showpad. To learn more about how QuickSight can help your business with dashboards, reports, and more, visit Amazon QuickSight.


About the Author

Shruthi Panicker is a Senior Product Marketing Manager with Amazon QuickSight at AWS. As an engineer turned product marketer, Shruthi has spent over 15 years in the technology industry in various roles from software engineering, to solution architecting to product marketing. She is passionate about working at the intersection of technology and business to tell great product stories that help drive customer value.

Deep Pool boosts software quality control using Amazon QuickSight

Post Syndicated from Shruthi Panicker original https://aws.amazon.com/blogs/big-data/deep-pool-boosts-software-quality-control-using-amazon-quicksight/

Deep Pool Financial Solutions, an investor servicing and compliance solutions supplier, was looking to build key performance indicators to track its software tests, failures, and successful fixes to pinpoint the specific areas for improvement in its client software. Deep Pool was unable to access the large amounts of data that its project management software provided, so it used AWS to access, manage, and analyze that data more efficiently.

During a larger migration to the AWS Cloud, the company discovered Amazon QuickSight, a cloud-native, serverless business intelligence (BI) service that powers interactive dashboards that let companies make better data-driven decisions. With QuickSight, Deep Pool could democratize access to this unused data and pinpoint areas for improvement in its software development processes, thereby improving the overall quality of its software.

According to Brett Promisel, Chief Operating Officer for Deep Pool, the company wanted to manage the data that it was collecting from a BI point of view to help it make more informed decisions. Because word of mouth and high-quality software are critical in Deep Pool’s industry, the company wanted to add additional rigorous quality controls to its product development and testing so that it continues to provide top-notch, stable software that its clients can rely on.

In this post, we share how Deep Pool boosted its software quality control using QuickSight.

Enhancing software testing to with data-driven insights

Continuous improvement is a hallmark of leading organizations. Deep Pool wanted achieve greater software quality and decided to improve how it monitored and managed its software testing processes using data.

Typical development processes involve extensive testing. First, the original developer tests the code, and then the code is unit tested. Next, larger groups test the code. For all this testing to be successful and result in product improvement, it needs to be measured and tracked so that developers can learn from it and implement improvements during the development process.

Using QuickSight for data-driven insights, Deep Pool has implemented significant software testing and control. It can now count the number of bugs found or tests failed and time how long it took to create patches and repair issues. It can also better track its work backlog and the progress of functionality requests. Monitoring this information lets the company know that it has successfully implemented improvements, because a decreasing number of bugs over time is a strong indicator of quality control.

Monitoring development to increase efficiency

Better software test management benefits two groups: internal teams and external customers. Deep Pool can now log and communicate important information, such as when a request is made, how it’s being resolved or addressed, and how it’s being tested. In addition to helping internal teams streamline their processes, the company can also use this data to track communications with customers, which are also stored in its project management software. Such knowledge helps the company determine whether customer requests are being promptly addressed and identify common trends that require action on a larger scale.

Seven development teams at Deep Pool independently write the code for the components of the company’s software products, and they must integrate those components to create the final products. With the granularity of the data that is provided by QuickSight, Deep Pool can thoroughly analyze the development and testing of these products. The company now has the ability to trace software bugs down to their original coding, which makes it simple to quickly locate and address any issues that come up. Deep Pool can also measure the results of those mitigating actions and determine whether its repairs were successful.

Attention to detail helps Deep Pool improve software quality, leading to better products and customers who are more likely to give positive referrals.

“Amazon QuickSight is extremely valuable to us when performing quality control. We can now expose our whole development team to how we’re managing databases and servers and measuring performance in a more optimal way,” says Promisel.

Deep Pool has successfully proven that it can use QuickSight to measure its quality control to improve its software and, ultimately, better support its customers. Since the migration to AWS, the number of software issues discovered and logged has dropped by 57%.

The increased quality control that has come from the company’s focus on accessing all its data and optimizing its use has led to better efficiency, which results in the ability to expand its growth without increasing its costs.

“We should be able to increase our customer base without adding the equivalent costs. Making sure we are as efficient as possible lets me manage that way,” says Promisel.

Expanding into more data sources

Deep Pool is also exploring how to expand its use of QuickSight to extract and use data from even more of its databases. In the future, it hopes to analyze its internal metrics, such as sales data, and its external client-related information, such as assets and holdings, to guide how it builds its client software and provides even more custom products.

Deep Pool is also committed to helping its employees be innovative and successful by investing in their futures and skill sets. It understands that well-trained employees can optimize the use of their tools, which results in better products. As such, the company will continue to invest in the training offered by AWS. Using cutting-edge tools and promoting its intent to invest in its employees indicate to Deep Pool’s customers that the company plans to stay innovative and ahead of the technological curve.

To learn more about how QuickSight can help your business with dashboards, reports, and more, visit Amazon QuickSight.


About the Author

Shruthi Panicker is a Senior Product Marketing Manager with Amazon QuickSight at AWS. As an engineer turned product marketer, Shruthi has spent over 15 years in the technology industry in various roles from software engineering, to solution architecting to product marketing. She is passionate about working at the intersection of technology and business to tell great product stories that help drive customer value.