Segmentation breaks down aggregate metrics into meaningful subgroups, revealing insights that overall averages might hide. For example, your product's average usage time might seem stable, but segmenting by user type could show new users spending less time while power users compensate by spending more, a potential early warning of future problems.

Common segmentation approaches include:

• Demographic factors (age, location, industry)
• Behavioral characteristics (usage frequency, feature adoption)
• Acquisition channels (organic search, social media, referrals)
• Time-based cohorts (users who joined during specific periods)

When segmenting data, avoid creating groups too small for statistical significance. Similarly, too many segments can lead to analysis paralysis. Focus on segments that directly relate to your key business questions and provide actionable insights that can drive specific improvements to your product or strategy.