The hosts discuss their research process, AI use, and the possibility of writing a book. They explore NLP for customer research, mention updates to their course, and discuss strange songs and drum riffs at conferences. They also talk about writing a workbook and the complexity of event tracking and assigning meaning to events.
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Quick takeaways
Designing events based on the customer journey and core product features can make event data more user-friendly for non-technical teams.
Prioritizing and minimizing event tracking enables more effective reporting and analysis without overwhelming teams with irrelevant data.
Deep dives
The challenge of defining event data
Event tracking becomes complicated when humans try to assign meaning to events. Different teams may interpret event names differently, leading to confusion and inconsistencies. Designing events from a business and product perspective can help bridge this gap and make event data more user-friendly for non-technical teams. By defining events based on the customer journey and core product features, teams can better understand and use the data. Additionally, having a catch-all interaction layer can accommodate specific use cases that may not be relevant to broader reporting but are still important for certain teams.
The importance of minimizing event tracking
While it can be tempting to track everything, it's important to prioritize and minimize event tracking to ensure that the data collected is meaningful and actionable. Instead of tracking every single event, focus on critical customer events across the customer journey, core product events, and specific interaction events. This targeted approach enables more effective reporting and analysis without overwhelming teams with irrelevant data.
The ongoing development of the workbook
The workbook is a living document that continuously evolves based on feedback and user needs. It aims to provide a comprehensive resource for event tracking and product analytics, covering topics such as event design, data models, and data stacks. The author's experience and feedback from readers inform the content and style of the workbook. Regular updates ensure that the workbook remains relevant and valuable to readers, addressing emerging challenges and industry changes.
Content creation process and platforms
The author's content creation process involves a mix of video, written articles, and podcasts. Inspiration for new content comes from a variety of sources, including other content creators, industry trends, and personal experiences. The author's goal is to provide unique angles and perspectives on topics related to data, events, and product analytics. Tools like lock sack and chat GPT help streamline and facilitate the content creation process. The content is published on platforms like LinkedIn, YouTube, and the author's website, offering a range of formats and accessibility to readers.