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With AI Insights by OWOX, product teams reveal the behaviors, flows, and value moments that shape retention and NRR – delivered straight into the tools they already use




















True Activation Rate
Measure how many accounts reach real product value, not just complete onboarding steps
High-Value Feature Adoption
Track usage of features strongly correlated with retention and expansion
Expansion Trigger Completion
Grow the share of users reaching behaviors that historically precede upgrades
Early Churn Risk Detection
Catch accounts showing predictive decline signals at least 30 days early
NRR Contribution from Releases
Ensure new features contribute positively to expansion and long-term revenue

Learn which sequences of behaviors lead users to sustained value.
See which features correlate with retention, upgrades, and expansion.
Pinpoint where users get stuck in signup, onboarding, or activation.
Choose roadmap items that reliably improve activation and NRR.

Users appear “activated” but haven’t reached real value.
Heavy usage doesn’t equal retention – key value drivers stay hidden.
Subtle declines in behavior stay invisible until it’s too late.
Friction blocks users from hitting behaviors that lead to expansion.
Features “look good” but fail to improve activation, adoption, or NRR.
Context: The team wants to understand what true activation looks like across segments.
Problem: Linear onboarding metrics hide the deep behaviors that separate retained users from churned ones.
💬 True activation requires 3–6 key behaviors – activated accounts dive deeper into custom usage, while non-retained accounts stop at surface actions.
Context: Some features drive retention and upgrades even with low usage.
Problem: Product teams prioritize popular features instead of those that actually drive revenue.
💬 Two underrated features strongly predict retention and expansions – promote them earlier in onboarding to increase long-term value.
Context: Churn often looks random because warning signs are subtle.
Problem: Early behavioral drops go unnoticed until accounts are already lost.
💬 Weekly active usage dropped 22% and collaboration decreased – this account shows two early churn indicators with a 30+ day lead time.
Context: Upgrades happen when users hit specific behavioral thresholds.
Problem: Friction stops users from reaching upgrade trigger moments.
💬 Users who upgrade hit 3–4 trigger behaviors. Remove friction in the paywall and flow steps to guide more users to upgrade readiness.
Context: New features are shipped, but the impact on activation and expansion is unclear.
Problem: Some releases look successful, but show zero value impact – or hurt retention.
💬 That recent release increased usage but had no measurable impact on activation or NRR – consider repositioning or iteration.
Get governed, accurate insights – straight from your data warehouse, delivered where your team already works. No setup hassle. Your first AI Insight can start delivering value the same day