retention analysis
- AI Strategy (315)
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- Leadership (76)
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- Product Management Leadership (306)
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AI Churn Prediction: From Risk Scores to Retention Action
A practical operating model for defining churn risk, routing interventions, choosing whether to build or buy, and proving retention impact.
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Measuring Enterprise AI Value: A Practical Adoption System
A practical system for connecting enterprise AI usage to repeat behavior, workflow outcomes, quality guardrails, and defensible financial impact.
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AI-Assisted Behavioral Analytics: A Product Leader’s Playbook
A practical operating model for using AI to investigate user behavior, validate product insights, build cohorts, and turn launch data into safer decisions.
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How Cohort Retention Analysis Turns Churn Into Action
Learn how to define useful customer cohorts, interpret retention differences carefully, and convert churn signals into focused product decisions.
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A Practical Framework for Measuring New Feature Success
A practical framework for deciding whether a new feature earns adoption, improves the user experience, and contributes to a meaningful product or business outcome.
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Behavioral Analytics for AI Agent Activation and Retention
A practical framework for measuring an AI agent’s first useful outcome, repeat value, and behavior-triggered interventions without mistaking activity for trust.
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Migrate Analytics Platforms Without Chaos: 7 Proven Lessons to Plan, Move, and Land Cleanly
Migrating analytics platforms doesn’t have to derail roadmaps or erode trust. I share seven battle-tested lessons—shaped by work with Human37 and Amplitude—that help teams align on…
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Stop Support Tickets Before They Start: How AI Unsticks Users and Lifts Conversions
Stuck users don’t just stall—they open tickets and quietly abandon funnels. By pairing behavioral analytics, session replay, and targeted in-app guides with an AI Assistant, it’s…
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Analytics-Led Growth Engineering: A Practical Operating Model
Build a growth engineering system that connects trusted behavioral data, focused experiments, safe releases, and durable activation and retention gains.
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Product Analytics for Retention: A Practical Operating System
Build a trustworthy retention analytics loop that connects valuable behavior, clean instrumentation, diagnosis, and controlled product experiments.
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Behavioral Customer Data for Proactive SaaS Retention
Learn how to turn behavioral customer data into clear risk reasons, timely retention plays, and a weekly product and customer success operating loop.
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I Pointed a “Ralph Wiggum” AI Loop at My Product for a Week—The Data That Stopped Chaos
I pointed a “Ralph Wiggum loop” at my product for a week to see how an agentic AI would perform under tight guardrails. The loop moved…
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How a Digital Analytics Visionary Shapes My Product Strategy for Growth, Retention & Monetization
Data is my compass for product decision-making, and I operationalize it through behavioral analytics, rigorous A/B testing, and continuous discovery. I start by mapping user journeys…
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How to Build a SaaS Retention and Expansion System
Build a closed-loop SaaS system that turns product, support, CRM, and billing signals into measurable retention and expansion playbooks.
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4 Costly Agent Analytics Myths—And the Data-Backed Metrics I Rely on Instead
Agent Analytics can mislead when we over-index on speed, containment, or early green dashboards. I share four common myths I see in human and AI agent…
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How to Link AI Evals to Retention Without Chasing Proxies
A practical playbook for finding early AI quality signals that predict retention, validating causality, and turning them into product decisions.
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Mastering Product Marketing with Amplitude Analytics: Proven Playbooks for Sustainable Growth
Discover how I apply Amplitude Analytics and behavioral analytics to connect product strategy with go-to-market strategy. Learn practical methods to improve user activation, run rigorous retention…
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Churn Prediction: A Practical Build-Versus-Buy Framework
A practical framework for choosing build, buy, or hybrid churn prediction based on speed, proprietary data, activation, talent, and total cost.
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How We Taught Agentic AI to Speak Product Analytics—and Unlocked Actionable Insights
I describe how we taught agentic AI to understand the nuanced language of product analytics and deliver trustworthy answers grounded in our metric catalog and event…
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Stop Misleading A/B Tests: Master Sample Size Assumptions for Reliable Results
Sample size calculators are only as reliable as the assumptions behind them. I show how I validate baseline rates, set a meaningful minimum detectable effect (MDE),…
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Browse topics
- AI Strategy (315)
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