User Research
First-Time Electric Car Buyer
An empathy map for a user who is environmentally conscious and researching their first electric vehicle (EV).
Analysis & Interpretation
Background
This empathy map delves into the mindset of a first-time electric car buyer. It captures the complex mix of excitement, anxiety, and information overload that characterizes a major, technology-forward purchase.
Key Strategic Insights
- Contradiction Between Thoughts and Actions: The user ‘Thinks’ (‘This is overwhelming’) but ‘Does’ (‘Creates a spreadsheet to compare’). This reveals a persona who is methodical and logical in their actions, even when feeling emotionally stressed. This means they need data and clear comparisons, not just emotional marketing.
- Fear and Information Gaps are Key Pains: The dominant pains are emotional (‘Anxious about a bad financial decision’) and informational (‘Confused by technical jargon’). Addressing these directly—through clear explainers, cost-of-ownership calculators, and testimonials—is critical.
- External Validation is Crucial: The user’s actions (‘Watches YouTube reviews’, ‘Reads articles’) and words (‘I wish I could just talk to another EV owner’) show a deep need for third-party validation and social proof. They don’t just trust the manufacturer’s claims.
Strategic Summary
This persona is a ‘Cautious Innovator’. They are excited by the new technology but need to overcome significant anxiety with data and social proof. To win this customer, a brand must provide clear, simple educational content, transparent pricing, and authentic testimonials or user stories. The marketing strategy should focus on demystifying the technology and building trust.
How This Was Built
This canvas demonstrates how a SaaS team can use visual thinking and AI support to align marketing, product, and analytics teams around conversion goals.
AI for Persona Discovery
The AI Insight Tool generated initial ideas for the Says, Thinks, Does, and Feels sections, helping capture the mindset of potential customers.
Visual Structuring for Clarity
Colors were used to differentiate emotional, behavioral, and cognitive aspects, while tags connected related insights for easier cross-reference.
AI Reflection & Pattern Review
After completing the map, the AI Analysis feature highlighted recurring concerns and revealed empathy gaps to focus on for future interviews.
Bring This Example to Life
Open this empathy map in the workspace to explore audience insights, refine key observations, and use AI feedback to deepen your understanding of what truly drives your customers.