AI product intelligence

AI Product Usage Intelligence

Turn product usage, customer success, support and revenue signals into clear priorities, risk scores and next-best actions.

Book an AI Opportunity Call Try live demo Explore workflow

Graphite pencil illustration of a SaaS product usage intelligence workspace with connected signal cards and account health objects — AI Product Usage IntelligenceAccount health, churn risk and next-best actions from connected product signals.

Outcome

From scattered SaaS signals to clear customer priorities.

AI Product Usage Intelligence is a decision layer for B2B SaaS teams. It combines product usage, CRM, support, billing and customer success signals to show which accounts are healthy, at risk or ready for expansion - and why.

Lower churn risk

Designed into the product workflow with clear owner, context and measurable outcome.

Better CS prioritization

Designed into the product workflow with clear owner, context and measurable outcome.

Higher product adoption

Designed into the product workflow with clear owner, context and measurable outcome.

Use case clarity

Start with the workflow moment we want to improve.

B2B SaaS teams increasingly have access to more AI tools and more product data, but the value appears when AI is redesigned into daily workflows and decisions rather than added as a generic assistant.

Step 01

Connect SaaS signals from product analytics, CRM, support and billing.

Solves Customer success teams do not know which accounts need attention first.

How Account health: Medium risk

Step 02

Select the business question: churn risk, activation, expansion, adoption or renewal.

Solves Product teams see dashboards but struggle to connect usage patterns to action.

How Signals: usage dropped 42% in 14 days, admin has not logged in for 9 days, support ticket mentions missing feature, renewal is in 21 days.

Step 03

Generate account-level health and opportunity scores.

Solves Sales and CS teams miss renewal, expansion and churn signals hidden across tools.

How Recommended action: Customer Success should schedule a check-in and offer onboarding around the unused feature set.

Step 04

Explain the signals behind each score.

Solves Leadership wants AI impact but does not want another standalone analytics demo.

How Confidence: High

Step 05

Recommend the next best action for CS, sales or product.

Solves Customer success teams do not know which accounts need attention first.

How Human owner: Customer Success Manager

From signal to action

Usage data becomes a prioritized account decision.

The product turns product, support, CRM and billing context into evidence-backed priorities that teams can actually act on.

Connect SaaS signals from product analytics, CRM, support and billing.

Customer health score

Select the business question: churn risk, activation, expansion, adoption or renewal.

Churn-risk explanation panel

Generate account-level health and opportunity scores.

Product adoption signals

Explain the signals behind each score.

The next step is logged, routed and ready for human review where needed.

Working underneathProduct analyticsCRM signalsHealth scoringCS action log

Trust & Control Layer

Useful AI with visible boundaries.

Every recommendation should expose the signals behind it, confidence level, suggested owner and human action status.

Product architecture

Core modules and data sources.

B2B SaaS companies with existing product, customer and revenue data but no clear operating system for account-level decisions.

Includes

Designed as a product system.

Not designed for: Very early products with no usage, customer or support data yet.

Customer health scoreChurn-risk explanation panelProduct adoption signalsNext-best-action engineRenewal and expansion opportunity viewCustomer timeline and evidence drawerPostHogAmplitudeMixpanelHubSpotSalesforceStripe

Delivery model

From product sprint to MVP and optimization.

Product Sprint

Map the decision journey, UX flow, AI behavior and trust boundaries.

MVP Build

Build the assistant, knowledge layer, handoff and measurement loop.

Optimization

Improve prompts, flows, analytics, content and business outcomes.

Explore adjacent AI product patterns.

AI Financial Decision AssistantFrom financial uncertainty to explainable next steps.AI Insurance Coverage ConciergeFrom coverage confusion to advisor-ready guidance.AI Guided Product AdvisorFrom product confusion to guided recommendations.

Final CTA

From scattered SaaS signals to clear customer priorities.

Book an AI Opportunity Call