The podcast discusses common issues faced by analytics teams, including lack of agency, investment in infrastructure, and improper placement in the organization. It explores the significance of merging performance data from ad channels and engagement data to enhance user acquisition and product tuning. It also emphasizes the importance of empowering analytics teams for organizational success and addressing deeper 'why' and 'how' questions for valuable analysis.
Analytics teams require authority to drive revenue growth by prioritizing tasks and making strategic decisions.
Investing in robust infrastructure and tools is crucial for analytics teams to deliver meaningful insights and drive product improvements.
Deep dives
The Importance of Agency and Authority in Analytics Teams
For analytics teams to provide genuine value and drive revenue growth, they need to prioritize their tasks, define their roadmap, and have the authority to dictate what they should be working on. If an analytics function is perceived as a value driver, it must be empowered to make decisions that contribute to revenue growth. Lack of agency and authority can lead to a reactive approach where the team is solely focused on answering basic what questions instead of delving into deeper insights.
Investing in Infrastructure for Analytics Success
To effectively deliver meaningful insights and drive product improvements, analytics teams must invest in building robust infrastructure and tools that go beyond basic data tabling. Providing front-end visualizations, filtering functionality, and statistical processing capabilities is crucial for data interpretation and decision-making. Without proper infrastructure, teams may struggle with ad hoc analysis and fail to address second-order questions that drive product advancements.
The Significance of Organizational Placement for Analytics Teams
Proper placement of analytics teams within an organization is essential for ensuring independence, effective communication, and the ability to push back when necessary. Reporting lines should be carefully structured to prevent conflicts and ensure that analytics teams can provide unbiased insights and recommendations. Placing analytics teams under product leads or CFOs can hinder autonomy and result in prioritization of trivial tasks over strategic analysis.
Embracing AI for Enhanced Analytics Capabilities
The integration of AI in analytics holds the potential to streamline manual tasks, freeing up analysts to focus on more creative and strategic endeavors. While AI may supplement human efforts in sourcing insights, it can enhance the overall effectiveness and efficiency of analytics teams. The adoption of AI is poised to empower analysts to delve deeper into data analysis, generating valuable insights and driving continuous product enhancements.
In this new podcast series from Mobile Dev Memo, called the MDM Canon, co-hosts Eric Seufert and Stewart Johnson select an article from the Mobile Dev Memo archive and discuss it at length.
This episode focuses on an article titled Why Analytics Teams Fail, first published in June 2016. Specifically, the episode highlights three common issues encountered by analytics teams that can cause them to be ineffective:
1) lack of agency and authority;
2) lack of investment into infrastructure;
3) improper placement in the organization.
Thanks to the sponsors of this week’s episode of the Mobile Dev Memo podcast: