Leveraging Self-Serve Analytics to Drive Growth: A Case Study on Kahoot!

• Analytics & Modeling - Machine Learning
• Platform as a Service (PaaS) - Application Development Platforms

• Cement
• Education

• Quality Assurance

• Time Sensitive Networking
• Usage-Based Insurance

• Data Science Services
• Training

Kahoot!, a platform for creating, sharing, and playing learning games or trivia quizzes, has experienced significant growth since its inception in 2012. With over 550,000 paying users and more than 1.5 billion participating players in 200 countries, the company faced the challenge of effectively managing and utilizing its vast product usage data. Despite having adopted Amplitude, a product intelligence platform, Kahoot! was only using a few functionalities and tracking minimal events. The company was suffering from a classic bottleneck where all data requests had to go through the data analysts. This situation was not sustainable given the company's growth and the increasing need for data-driven decision making across different departments.

Kahoot! is a global platform where users can create, share, and play learning games or trivia quizzes. Founded in 2012 as a research project at the Norwegian University of Science and Technology, the company has grown to serve more than 550,000 paying users. In 2020, more than 250 million games were played on Kahoot!, with over 1.5 billion participating players in 200 countries. The company is headquartered in Oslo, with offices in the U.S. and throughout Europe. Kahoot! is used by half of all teachers and students in the United States and 97% of Fortune 500 companies for various purposes including training, onboarding, presentations, and events.

To address this challenge, Kahoot! focused on improving its data governance and promoting self-service analytics. The company set clear naming conventions, made unnecessary information invisible for the end user, and considered which properties had different values and needed to be merged. This groundwork ensured that the product analytics data could be trusted and that the end user didn’t need a background in data science to understand it. Kahoot! also invested time in creating self-service analytics that allowed people across the company to use product data for analysis by themselves. With Amplitude, engineers, PMs, and marketers could understand how users used the product or how the features were performing without having to rely on the data team for everything. The company also incorporated Amplitude into training for new hires to ensure everyone could effectively use the platform.

• The implementation of Amplitude and the focus on self-service analytics have had significant operational benefits for Kahoot!. The company has been able to remove the data bottleneck, allowing for immediate insights and sparking further curiosity among employees. This has led to a deeper dive into results and increased competence in the field of data analysis across the company. Product managers, engineers, marketers, and the customer support team now feel the need for Amplitude to carry out their jobs. The data has become a critical part of product management, informing decisions and driving growth, loyalty, and adoption. The quality of Amplitude’s UI has also enabled product managers to understand the reasoning behind decisions the way a data scientist would. This has led to improved functionalities and quicker decision-making processes.

• Requests to the data team reduced by about 80% due to the self-service nature of Amplitude.

• Implementation of a churn model resulted in a 20% drop in churn.

• Over 150 out of 170 employees use Amplitude for data analysis, with 100 of those being monthly active users.