Product Analytics for Enterprise Applications
The product-analytics discipline — funnels, retention, adoption, dashboards, anomaly detection — pointed at the apps your workforce and AI agents actually run the business in, not just customer-facing web and mobile.
Core analytics, end to end
Everything you expect from a modern product-analytics platform — built for enterprise and workforce applications.
Funnel & conversion analysis
Track progression through any multi-step workflow, see where work drops off, and break conversion down by segment — region, team, channel, or case type.
Cohort retention
Build behavioral cohorts (e.g. users who adopted an AI assist or a new flow) and see whether the behavior — and its outcome lift — sticks week over week.
Feature adoption & engagement
Quantify depth and breadth of adoption for every feature and step, so you know what drives value and what to retire, automate, or augment.
Customizable dashboards
Role-tailored dashboards with KPI cards, trends, and breakdowns — built without engineering and shared across the organization.
Anomaly detection & alerts
Statistical, threshold-free detection that surfaces the branches, teams, or metrics drifting from the network baseline — and what drove the change.
Segmentation & ad-hoc exploration
Slice every chart by shared global filters, click any datapoint to drill, and follow the path from aggregate to cohort to the individual session.
Ask the Data
A copilot that answers in plain language
Ask a question in natural language and get a grounded answer with the right chart — then pin it to a dashboard. Every answer is generated against a governed semantic layer and shows the query it ran, so business teams can explore without waiting on an analyst.
Beyond the dashboard
Close the loop from insight to action and back to evidence.
Adoption & experimentation
- ✓ A/B tests & feature flags with significance and a clear ship/hold verdict
- ✓ In-app guides, onboarding checklists, and walkthroughs
- ✓ Adoption funnels that prove a rollout actually changed behavior
Voice of the user
- ✓ In-product surveys, NPS/eNPS, and always-on feedback widgets
- ✓ AI sentiment & theme clustering on open-text feedback
- ✓ Feedback tied back to behavior, so you see what users say next to what they do
The enterprise difference
Consumer product-analytics tools stop at customer-facing web and mobile. Pyze captures the apps employees and AI agents work in — across web, mobile, and desktop — and pairs the behavioral data with the documented SoP, so you measure not just what happened, but whether it matched the way the work is supposed to be done.
See Pyze Product Analytics on your workflows
A 30-minute walkthrough on one of your own processes — funnels, retention, anomalies, and the Ask-the-Data copilot.