In the ever-evolving world of digital platforms, product management is as much about decision-making as it is about understanding data. PMs rely heavily on KPIs and data analytics to validate ideas, prioritize features, and deliver results. For any company, where user need is at the core, data serves as the foundation for building an exceptional user experience.

Lets understand by taking Flexihire as an example and do a product teardown.

The role of KPIs:

KPIs are the compass guiding for every product managers toward success. They allow PMs to identify bottlenecks, track improvements, and measure overall platform effectiveness.

For example, KPIs relevant to Flexhire's application process could be:

• Conversion Rates: Percentage of users who complete their applications.
• Time to Hire: Average duration from application submission to a candidate being hired.
• Drop-off Rates: Where candidates abandon the process and why.
• User Engagement: Metrics like profile completeness and active session duration.

Data analytics driving Product decisions:

On proper understanding of data analytics, it can give the PMs actionable insights.

1. Testing new feature with A/B Testing : By doing A/B Test PMs can validate their hypothesis early on and efforts and resources can be used in right direction
2. Personalized job recommendation for candidates: By leveraging user segmentation and machine learning, Flexihire can share recommendations to the candidate based on their job application history, skill set and interests.

Data helps a PM in many ways

1. in prioritizing a product feature or enhancements
2. in validating hypothesis
3. in improving user satisfaction

There are many tools in the market which can be used for analysing the data efficiently:

Google Analytics, Tableau, Amplitude

Key Takeaways:

• Data is a PM’s Superpower and it guides the PMs to take informed decisions but also builds credibility with stakeholders.
• KPIs should be Actionable and creates a focus on metrics that lead to specific outcomes, like improving the conversion rate.
• Use of data to continuously iterate and optimize the product.