What it does

Use when a user mentions "friction point intervention", "in-product friction journey", "drop-off rescue", or asks for related help. When behavioral signals detect friction — setup abandoned, repeated failed actions, error encountered, drop-off at conversion step — fire a graduated intervention: in-app contextual help first, escalate to email tutorial, escalate to human/agent if friction persists. Catches users before they give up.

You get

Attribute

AI-Derived Attribute produced by this recipe.

Segment

Segment produced by this recipe.

Content Asset

Asset produced by this recipe.

agent

AI Agent Scenario produced by this recipe.

Journey

Journey produced by this recipe.

Dashboard

Dashboard produced by this recipe.

How it works

1

Build Friction Detection AI Attribute

create_ai_attribute

Create an AI-derived attribute

Produces:Attribute

2

Identify Friction-Affected Users

Create Segment

Build a segment

Produces:Segment

3

Build Contextual In-App Help

create_page_content

Generate in-app contextual help variants per friction_location. For setup-abandonment: contextual tooltip at the abandoned step with the answer to the common blocker. For repeated-failed-action: floating help bubble with

Produces:Content Asset

4

Build Email Fallback Content

Generate Content

Generate email fallback content sent if the user doesn

Produces:Content Asset

5

Build Agent Handoff Path

create_agent

Configure an AI agent scenario

Produces:agent

6

Build Graduated Rescue Journey

Create Journey

Build a graduated-escalation journey triggered when recent_friction_signal becomes moderate or severe. Touch 1 (mid-session, immediate): in-app contextual help renders at the friction location. Touch 2 (4 hours later, if user left without resolving): email fallback with tutorial + resume-link. Touch 3 (24 hours later, if friction signal still active OR user hasn

Produces:Journey

7

Build Friction Intervention Dashboard

Build Dashboard

Compose a friction intervention dashboard: top 10 friction locations by frequency (a product-team-priority signal — these are the UX bugs the data is telling you about), in-app-help dismiss rate (high = irrelevant help, low = useful), friction-to-resolution rate by intervention touch (which level of escalation actually resolves), severe-tier-to-churn correlation (do users stuck severely actually churn — proves the intervention

Produces:Dashboard

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Friction Point Detected Intervention

What it does

You get

How it works

Build Friction Detection AI Attribute

Identify Friction-Affected Users

Build Contextual In-App Help

Build Email Fallback Content

Build Agent Handoff Path

Build Graduated Rescue Journey

Build Friction Intervention Dashboard

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