Mental Model Mapping 🧭 Prompts

Purpose: Mental Model Mapping helps UX teams understand how users think about a system, task, or concept so designs align with users' expectations and mental organisation.

Design Thinking Phase: Define

Time: 45–60 min session + 1–2 hours analysis

Difficulty: ⭐⭐

When to use:When shaping IA or onboarding flows based on user logicTo identify mismatches between system behaviour and user expectationsWhen redesigning features based on cognitive gaps uncovered in usability testing

What it is

Mental Model Mapping is a qualitative research method used to visualise how users perceive and mentally organise tasks, goals, and systems. It captures users’ thought processes through interviews or observational data and maps these to highlight overlaps and gaps between user models and system models.

📺 Video by NNgroup. Embedded for educational reference.

Why it matters

Product success hinges on how well your solution fits the way users think and behave. Mental Model Mapping creates a visual comparison between current product design and how users expect it to behave or be structured. It brings clarity to redesign decisions, uncovers hidden friction points, and gives the design team the confidence that they’re addressing real, not assumed, misalignments.

When to use

• Before restructuring navigation or IA to reflect user logic
• To guide prioritisation of feature improvements in early-stage roadmap planning
• Post usability testing, to dig deeper into unexpected user errors or slowdowns

Benefits

• Rich Insights: Helps uncover user needs that aren’t visible in metrics.
• Flexibility: Works across various project types and timelines.
• User Empathy: Deepens understanding of behaviours and motivations.

How to use it

1. Conduct open-ended user interviews using task-based framing (e.g. “Walk me through how you do X”).

2. Note explicit actions as well as mental triggers, assumptions, tools used, and emotional checkpoints in each story.

3. Cluster statements into conceptually similar groupings to reflect users' internal thinking structure.

4. Map these groupings as a vertical user model stack — task flow layered with insights, thoughts, and motivators.

5. Overlay your current system model horizontally to visually highlight gaps and alignment.

6. Analyse mismatched areas to generate design opportunities or refinement points.

Example Output

Fictional Example: A financial wellness app team maps future saving behaviour for Gen Z users.

• User model includes: “Worry about bills → Google saving hacks → Look for TikTok finance tips → Use banking app to set goal reminder.”
• System model jump-starts with: “Open app → Navigate to goals tab → Pre-fill income & saving ratio → Suggest goal.”
• Gap: Users require trusted advice before even considering savings, while app assumes users initiate savings without needing confidence-building or guidance.

Common Pitfalls

• Insufficient data: Mapping on too few interviews creates weak or misleading patterns. Aim for at least 8–10 varied sessions.
• Assuming linear thinking: Mental models aren't always logical task flows. Look for intent and triggers, not only sequence.
• Polishing too early: Jumping to design based on partial mental maps undercuts this method's real value — system-user misalignment diagnosis.

10 Design-Ready AI Prompts for Mental Model Mapping – UX/UI Edition

How These Prompts Work (C.S.I.R. Framework)

Each of the templates below follows the C.S.I.R. method — a proven structure for writing clear, effective prompts that get better results from ChatGPT, Claude, Copilot, or any other LLM.

C.S.I.R. stands for:

• Context: Who you are and the UX situation you're working in
• Specific Info: Key design inputs, tasks, or constraints the AI should consider
• Intent: What you want the AI to help you achieve
• Response Format: The structure or format you want the AI to return (e.g. checklist, table, journey map)

Level up your career with smarter AI prompts.Get templates used by UX leaders — no guesswork, just results.Design faster, research smarter, and ship with confidence.First one’s free. Unlock all 10 by becoming a member.

Prompt Template 1: “Draft a User Mental Model from Raw Interview Data”

Draft a User Mental Model from Raw Interview Data

Context: You are a UX researcher organising qualitative interview notes into a usable mental model.
Specific Info: Interview transcripts describe how [users plan trips using multiple travel tools], including [brands/tools mentioned] and [point of frustration].
Intent: Create a layered mental model illustrating user thought flow, decision cues, and emotional anchors.
Response Format: Provide a structured mental model diagram (text-based), grouped by themes, actions, and emotional stages.

If the emotional stages or tools are unclear, ask clarifying questions before responding.
Suggest a next step, like validating the model with another user type.

Prompt Template 2: “Compare User Mental Model to System Model for Gaps”

Compare User Mental Model to System Model for Gaps

Context: You are a UX designer aligning a product's current flow with the user mental model.
Specific Info: The system model includes [X screens/features] and assumes [user goals]. User mental model reveals [contrasting assumptions or task logic].
Intent: Identify conceptual and interaction mismatches between models.
Response Format: Provide a 2-column comparison table with mismatches and design recommendations.

Clarify if any steps or user assumptions are vague.
Suggest how this gap may affect onboarding or task completion.

Prompt Template 3: “Generate Interview Questions to Elicit Mental Models”

Generate Interview Questions to Elicit Mental Models

Context: You are preparing interviews to uncover how [users manage their digital privacy].
Specific Info: You need open-ended, action-focused questions to expose thought patterns, emotions, and strategies.
Intent: Get 8–10 interview prompts that target behaviour, decisions, and feelings across the journey.
Response Format: Provide a numbered list of user research questions, including 1 for closing reflection.

Ask if there are specific age groups or technologies in focus.
Suggest 1 probing follow-up for each question where relevant.

Prompt Template 4: “Distil Mental Model Themes from Multiple Interviews”

Distil Mental Model Themes from Multiple Interviews

Context: You are analysing notes from [12] user interviews for a new [habit-forming app].
Specific Info: Users described daily routines, blockers, and motivations. Themes vary but reveal behavioural patterns.
Intent: Pull out key mental model themes to inform IA and features.
Response Format: Provide a summary with 3–5 themes, supporting user quotes, and possible design implications.

Flag if user goals were too broad or missing.
Recommend a visualisation format to present findings to stakeholders.

Prompt Template 5: “Visualise User Mental Model into Layered Flow”

Visualise User Mental Model into Layered Flow

Context: You synthesised how [freelancers invoice clients] from interviews and want to build a reference model.
Specific Info: Users follow non-linear patterns influenced by tools, emotions, and client needs.
Intent: Create a mental model diagram: surface actions, motivations beneath, and deeper beliefs/values.
Response Format: Output a layered flow with three tiers (actions, thoughts, beliefs).

Check if there’s alignment with existing persona or product goal.
Suggest ways to story-tell this model in a stakeholder deck.

Prompt Template 6: “Reverse-Engineer Mental Model from Product Errors”

Reverse-Engineer Mental Model from Product Errors

Context: You’re investigating why users incorrectly complete a [multi-step returns form].
Specific Info: Analytics shows high abandonment at step 2; users expect [alternative flow or information].
Intent: Reconstruct the likely mental model causing confusion.
Response Format: Provide probable user mental model, mismatch points, and redesign suggestions.

Confirm if error messaging or assistive text exists in the flow.
Propose a micro-interaction or UI fix that resolves expectation gap.

Prompt Template 7: “Guide Product Messaging with User Mental Models”

Guide Product Messaging with User Mental Models

Context: You are revising in-app onboarding to match how [first-time SaaS users] approach learning new tools.
Specific Info: The mental model includes [assumed user tasks] and avoidance of [specific technical jargon].
Intent: Optimise copy and UI language to reflect user understanding.
Response Format: Provide a language tone/messaging table matched to mental models and stages.

Determine whether onboarding is contextual or staged.
Suggest 1 messaging principle based on behavioural science.

Prompt Template 8: “Align Cross-Team Understanding With a Shared Model”

Align Cross-Team Understanding With a Shared Model

Context: You need to help product, design, and support align on how [users manage account recovery].
Specific Info: Teams perceive flow differently; support hears pain but design assumes ease of use.
Intent: Frame a shared user-centric model to resolve discrepancies.
Response Format: Generate a 1-page visual summary that synthesises multiple perspectives.

Ask for user feedback or NPS scores if relevant.
Recommend a workshop format to align teams on outcomes.

Prompt Template 9: “Unlock Feature Opportunities from User Model Gaps”

Unlock Feature Opportunities from User Model Gaps

Context: Your mental model mapping revealed [several unmet assumptions] about how users navigate [task X].
Specific Info: Your product currently [does not offer relevant features] or assists too late in the flow.
Intent: Translate user expectation gaps into actionable feature ideas.
Response Format: Provide a feature opportunity list, each tied to user thinking or assumption.

Confirm if users had workaround strategies for the gap.
Suggest a prioritisation rubric for evaluating these ideas.

Prompt Template 10: “Prepare a Design Crit Using Mental Model Findings”

Prepare a Design Crit Using Mental Model Findings

Context: You’re presenting Figma flows to critique with mental model overlays.
Specific Info: Your design attempts to match [layered user decision points] from the interviews.
Intent: Guide the team through flows while referencing mental model insights for validation/critique.
Response Format: Provide talking points, model callouts, and critique goals.

Confirm if flows highlight decision friction or moments of doubt.
Include 1 question to provoke deeper discussion in the room.

Recommended Tools

• Optimal Workshop (for card sorting and hierarchy testing)
• Miro (great for cluster mapping and collaborative model building)
• Dovetail (tagging and analysing interview verbatims)
• Figma (for model overlays on product flows)
• ChatGPT + plugins (for clustering quotes or structuring raw thoughts)

Learn More

• NNGroup: UX Research & Design Articles
• Interaction Design Foundation – Topics
• Google Design Sprint Kit