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Adapting to User Behavior Changes: A Case Study on BetterMe's Use of Amplitude
BetterMe, a leading behavioral healthcare app publisher, faced a significant challenge during the pandemic. Despite being well-positioned to capitalize on the shift from gyms and group fitness classes to home workouts, the company found itself in catch-up mode. The behavioral changes of its users, such as the marked increase in time users were spending on the app, required rapid adaptation. The main challenges were the speed of experimenting and responding to user needs while maintaining a high satisfaction level. The company needed to balance velocity and satisfaction levels, which was a complex task. Additionally, BetterMe needed to understand how its new features were affecting user retention and revenue rates, and which releases were gaining traction and which were not.
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Leveraging Self-Serve Analytics to Drive Growth: A Case Study on Kahoot!
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.
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Data Democratization and Rapid Testing: How Amplitude Scales Canva
Canva, an online design and publishing platform, was facing a challenge in managing and utilizing its vast data. The company wanted to empower non-technical stakeholders with self-serve data to explore different areas as needed. They had a data warehouse, but the barriers to entry were too high for the average user. To grow Canva at scale, non-technical people needed to segment audiences and create funnels. It was difficult for product managers to dive into new releases and see how new features performed or get a breakdown of a funnel. Shortly after launch, the team realized the need for a more detailed product analytics solution.
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Centralizing User Data for Enhanced Analysis: A Case Study on AllTrails
AllTrails, a digital platform providing information on over 350,000 trails to 40 million users worldwide, faced a significant challenge in managing their data architecture. The company's analysts and engineers had developed a homegrown JSON schema library to define event collection, which was built into a custom SDK platform. However, maintaining this custom SDK generator for each platform was time-consuming and often led to delays in the collection of new analytics events. Furthermore, the GitHub repository used for this process was difficult for non-technical team members to navigate, making it challenging to ensure that it met their requirements. The company realized the need to move away from their homegrown SDK library and adopt a customer data platform (CDP) solution.
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