Blog 83: Tools in product management … (5/7)
- Idea2Product2Business Team
- Jul 31, 2024
- 2 min read
Updated: Aug 29, 2024
Continued from blog 82.
Product management is a vast field with multiple sub-fields. They range from:
1. Strategy & planning (various tools highlighted in blog 79).
2. Design (UI/UX) (various tools highlighted in blog 80).
3. Execution & tactics (various tools highlighted in blog 81).
4. Go-to-market (various tools highlighted in blog 82).
5. Metrics & performance (various tools highlighted in blog 83)
6. Product development & technology (various tools highlighted in blog 84).
7. Cross-functional (various tools highlighted in blog 85).
There are several specialised tools catering to each of these sub-fields. In this blog we look at the fifth sub-field metrics & performance.
Product Analytics:
Product analytics is understanding how users engage with our product. To do this analysis, we need to collect the right data (i.e., metrics). Hence, tracking these metrics is critical (refer to blog 58: product analytics for better decision making).
· LogRocket: LogRocket combines session replay, product analytics, and error tracking to empower software teams to create the ideal product experience.
· Heap: Heap is the analytics solution for product managers that makes it possible to understand customer behaviour at scale.
· Mixpanel: Mixpanel is a real-time analytics platform that helps companies measure and optimize user engagement.
· Amplitude: Amplitude aims to help software teams build better products by turning user data into meaningful insights. Analyses metrics related to freemium & free trial strategy (blog 90). Also used for attribution models (blog 91).
Recent times have seen a rise in the use of AI (artificial intelligence) in product management. AI is helping to derive valuable insights and automate routine tasks. Some key use cases of AI, ML, and analytics in metrics & performance are:
Performance monitoring and analytics. AI, ML, and analytics is used for the following:
- Monitor user behaviour and performance metrics.
- Modify products based on real-time feedback and data-driven insights.
- Tools like Mixpanel and Amplitude provide AI-driven analytics for performance monitoring.
Track KPIs. AI, ML, and analytics is used for the following:
- AI can automatically surface insights and trends from product data that humans may overlook.
- NLP allows product managers to quickly retrieve relevant KPIs by asking questions about data sets.
- AI-powered anomaly detection and alerts can detect deviations in KPIs.
- Tools like Tableau and Looker use AI to provide insights into KPIs.
Note: The list of companies mentioned above are ONLY a SAMPLE list and NOT an exhaustive list.
Jump to blog 100 to refer to the overall product management mind map.
Source:
Web/Google research as of July 2024
I wish you the best for your journey. 😊