Automating Data Analysis: A Case Study of I Will Teach You To Be Rich

• Functional Applications - Warehouse Management Systems (WMS)
• Sensors - Barcode Readers

• Cement
• Equipment & Machinery

• Sales & Marketing
• Warehouse & Inventory Management

• Picking, Sorting & Positioning
• Time Sensitive Networking

• Training

I Will Teach You To Be Rich (IWT), a content company founded by author Ramit Sethi, was facing a significant challenge in managing and analyzing their vast amount of data. The company produces a large volume of content, including books, courses, podcasts, and blog posts, attracting over a million readers every month. However, the team was struggling to track the performance of their content and understand their readers due to the time-consuming process of manually analyzing data. Basic reports on email subscribers took hours to create, leaving no time for critical analysis of the data. The team needed to answer questions like 'How many people read the guide we published in January?' but the process of exporting a report, opening it in a spreadsheet app, manually running a query, and consolidating the results was extremely time-consuming. The team realized they needed a data warehouse to store and easily access their data without the need for a dedicated data analyst.

I Will Teach You To Be Rich (IWT) is a content company founded by author Ramit Sethi. The company's mission is to help readers live 'rich' lives, providing guidance on topics such as finding dream jobs, starting businesses, increasing productivity, and getting out of debt. IWT produces a wide range of content, including books, courses, podcasts, and over a thousand blog posts. The company has a large readership, attracting over a million readers every month. IWT also offers paid guides, online courses, and books to their tens of thousands of customers. The company tracks payments from each sale using Infusionsoft invoices.

To solve their data management and analysis challenge, IWT turned to app automation platform Zapier. Content marketing manager Ciaran Lyons used Zapier to create an automated data analysis workflow without writing a single line of code. The solution involved building a data warehouse using open-source database PostgreSQL, which offered a simple, customizable place to store and analyze data. Lyons set up three Zaps (custom connections in Zapier) to build the data warehouse. The first Zap sent all new IWT readers to the PostgreSQL database. The second Zap tracked the rate at which readers confirmed their email addresses, a key metric for engagement. The third Zap sent new Infusionsoft invoices to PostgreSQL, providing insight into sales. The data warehouse was then connected to Periscope Data, an extension that turns queries into easy-to-read charts, allowing the team to quickly see the number of readers, sales, and other key metrics.

• The implementation of the automated data analysis workflow using Zapier and PostgreSQL has significantly improved IWT's operational efficiency. The team no longer needs to spend hours creating basic reports on email subscribers, freeing up time for critical analysis of the data. The solution has also enabled the team to gain real-time insight into the overall health of the business, answering key questions just by glancing at a chart. The data warehouse has empowered the team to ask more questions of the data and make data-driven decisions. For instance, they discovered that Hotmail users were less likely to confirm their email addresses, leading to a change in their email confirmation process that resulted in a 10% growth in email confirmation. The data warehouse has also facilitated team collaboration, with up-to-date dashboards helping the team rally around successes and tackle new questions. The solution has proven to be a 'superpower' for IWT, enabling them to learn from their data and improve their content and products.

• Saved hundreds of hours over the past year by automating data analysis

• Increased email confirmation rate from 70% to 80%, representing a 10% growth

• Enabled real-time tracking of content performance and reader engagement