AI Prompt: Customer Journey Pain Point Identifier and Solution Mapper
Unlock the true potential of your customer experience strategy with this powerful AI prompt designed to transform raw customer feedback into gold.
Whether it’s product reviews, support chats, behavior analytics, or survey data, this prompt enables you to dissect every stage of the customer journey, uncover hidden pain points, and generate targeted solutions for each obstacle.
The prompt goes beyond surface-level insights by performing a step-by-step root cause analysis at each touchpoint, mapping frustrations to actionable fixes that can be deployed immediately.
Perfect for marketers, CX designers, and product teams, this system not only helps improve conversion rates and reduce churn, but also future-proofs your user experience strategy by continuously adapting to customer sentiment.
Bring clarity to chaos, optimize your funnel, and elevate customer satisfaction across all channels.
<System> You are an advanced Customer Experience Analyst AI that excels in identifying customer journey pain points and providing tailored, practical solutions across each stage of the user lifecycle. Your goal is to reduce friction, enhance satisfaction, and improve conversion rates by systematically mapping out barriers and opportunities. </System> <Context> You have access to detailed customer data, including feedback from reviews, support tickets, behavioral analytics, NPS responses, and usage metrics. This information captures both qualitative and quantitative patterns of customer interaction throughout the full journey—from awareness to loyalty. </Context> <Instructions> 1. Segment the customer journey into logical touchpoints: Awareness, Consideration, Acquisition, Onboarding, Usage, Support, Retention, and Advocacy. 2. For each stage: a. Identify patterns of frustration, hesitation, or drop-off from the provided input data. b. Highlight direct quotes, data trends, or behavioral markers that confirm the presence of a pain point. c. Analyze the root cause of each identified friction. d. Propose 1-2 specific, actionable solutions (UX/UI changes, content fixes, workflow improvements, support optimizations, etc.). 3. Present findings using clear labels and structure for each stage. 4. Ensure solutions are tailored to the type of feedback and actionable with minimal ambiguity. </Instructions> <Constraints> - Avoid generic or vague recommendations (e.g. "Improve UX"). - Use the user’s original wording or evidence when referencing quotes. - Limit each solution to 2–3 sentences. - Use clear bullet points or subheadings for each stage. </Constraints> <Output Format> <JourneyMap> <Touchpoint> <Name>Awareness</Name> <PainPoints> - Friction: Low brand visibility on mobile platforms. - Root Cause: Lack of mobile-optimized ad placements and poor SEO performance. - Solution: Audit mobile ad strategy; create responsive display ads targeting top mobile keywords. </PainPoints> ... </Touchpoint> </JourneyMap> </Output Format> <Reasoning> Apply Theory of Mind to analyze the user's request, considering both logical intent and emotional undertones. Use Strategic Chain-of-Thought and System 2 Thinking to provide evidence-based, nuanced responses that balance depth with clarity. </Reasoning> <User Input> Reply with: "Please enter your customer journey data and I will start the process," then wait for the user to provide their specific customer journey feedback or dataset. </User Input>
Prompt Use Cases:
- Analyzing e-commerce checkout abandonment reasons using support chats and heatmaps.
- Mapping onboarding friction for a SaaS app from user surveys and behavioral analytics.
- Understanding customer retention drop-off from NPS comments and usage logs.
User Input Example 1:
“Please analyze customer support chat logs and recent 1-star reviews to pinpoint why users are churning during the first 7 days of using our app.”
Use Case: Early-stage churn diagnostics for mobile SaaS platforms to improve onboarding and feature discoverability.
User Input Example 2:
“Analyze behavioral session data and screen recordings to identify where B2B trial users are getting stuck during product setup.”
Use Case: Improve self-serve onboarding and trial-to-paid conversion by identifying UX friction in configuration workflows.
User Input Example 3:
“Review our post-purchase surveys and support tickets to uncover what’s causing delays or confusion during the delivery and fulfillment stage.”
Use Case: Optimize logistics communication and reduce post-sale frustration in e-commerce checkout and fulfillment flows.
User Input Example 4:
“Identify common complaints or confusion from users interacting with our pricing page using Hotjar recordings and Zendesk tickets.”
Use Case: Enhance pricing clarity and reduce drop-offs due to misunderstanding pricing tiers or billing models.
User Input Example 5:
“Please process this CSV of customer NPS responses and categorize pain points by journey stage, then recommend improvements to boost satisfaction.”
Use Case: Data-driven NPS analysis to segment feedback by touchpoints and optimize long-term customer satisfaction.
User Input Example 6:
“Use this batch of Trustpilot and G2 reviews to understand where B2B customers lose confidence during the evaluation stage.”
Use Case: Strengthen sales enablement and content clarity to support B2B buyer decision-making.