Fivetran > Case Studies > Houseware's Transformation: Building Data Apps with Powered by Fivetran

Houseware's Transformation: Building Data Apps with Powered by Fivetran

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Technology Category
  • Application Infrastructure & Middleware - Data Visualization
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Cement
  • Equipment & Machinery
Applicable Functions
  • Sales & Marketing
Use Cases
  • Building Automation & Control
  • Time Sensitive Networking
Services
  • Data Science Services
  • System Integration
About The Customer
Houseware is a software development company that provides a platform and toolkit for its customers to build internal data products. The company is small, with less than 20 employees, but supports various departments including Sales, Marketing, and Customer Support. Houseware aims to deliver metrics such as ARR, NRR, customer churn, conversion rate, and other KPIs to its customers, rather than just tables, rows, columns, and schemas. The company's goal is to enable its users to build data applications that address the problem of data-informed action, something that most BI tools promise but rarely deliver. Houseware's platform enables the creation of data applications and workflows that can trigger targeted emails based on shopping behavior, alert sales reps to accounts that need attention, and activate custom experiences based on user actions.
The Challenge
Houseware, a software development company with less than 20 employees, was facing significant challenges in providing a platform and toolkit for its customers to build internal data products. The company's goal was to go beyond the scope of general analytics and data visualization tools, delivering metrics such as ARR, NRR, customer churn, conversion rate, and other KPIs. However, they were struggling with a lack of data insight, reliability, and availability. Their marketing campaigns were inefficient, and they were unable to turn data into customer retention optimizations. The trust in data was decreasing due to errors. Users had to learn data analytics tools and database methods, such as table joins, and develop custom metrics from scratch. Data dashboards and analytics often broke down, took too long to produce results, or required too much custom programming. Poor APIs and data pipelines limited the types of analytics that developers could construct to meet customer needs. The tools produced insights without any actionable recommendations, and building data connectors required lots of programming time and effort.
The Solution
Houseware turned to Fivetran for a solution. Powered by Fivetran, Houseware was able to easily connect their data to the Houseware platform. Fivetran provided more than 200 pre-built data connectors with comprehensive documentation. It also integrated with dbt to automate data transformation processes. Fivetran offered a free 14-day trial for each new connector Houseware added to its implementation. It also provided support for handling data at scale with well-crafted APIs that Houseware could build their product on top of. This solution allowed developers to create apps without deep technical knowledge of data source APIs. It provided a wide collection of data integration APIs and connectors needed to cover various client software tool configurations. It enabled easy interpretation and understanding of customer trends revealed by data patterns. It also allowed workflows to adapt to different client and customer needs in how they obtain and process their data. This solution saved on data engineering/devops labor costs through massive automation of common tasks, especially at scaling up their customer base. It also helped build a solid platform that can be used in the future as the basis for a customer self-service portal.
Operational Impact
  • The implementation of Fivetran's solution has led to significant operational improvements for Houseware. Customers can now quickly turn interesting data insights into actionable and operational results. The use of metrics and templates rather than rows and columns has made data analysis more approachable and actionable. Free trials have enabled Houseware to build attractive proof of concepts for new customers. Houseware can now build tools to enable follow-up sales calls based on actual product usage. Data access is no longer the limiting factor in building custom data analytics apps. The company now has a solid platform that can be used in the future as the basis for a customer self-service portal.
Quantitative Benefit
  • More than 200 pre-built data connectors provided
  • 14-day free trial for each new connector added
  • Significant savings on data engineering/devops labor costs through automation

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