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Analyze Product Perception: Understand How Users Talk About Your Product

TL;DR: What this template does

This template analyzes how customers describe your product in natural conversation.
Upload interviews or feedback sessions and get a sentiment-rich, theme-based report of how your product is perceived — from value props to confusion points.

What is product perception and why should you care?

You might describe your product one way — but how do your users actually talk about it?

That disconnect is where positioning, onboarding, and product clarity often break down.

Definition: Product perception refers to the collective language, sentiment, and mental models users express when describing your product, brand, or experience.

How does this template work?

Step 1: Upload Descriptive Feedback
  • Use support, onboarding, or discovery call transcripts
  • Accepts text, video, and audio
  • Ideal for users who’ve tried or are using your product
Step 2: Extract Themes — Content Analysis
  • AI analyzes how users frame your product (what it is, does, solves)
  • Clusters language into themes: confusion, delight, expectations
  • Pulls emotional signals: “it’s too complex,” “it just works,” etc.
Step 3: Get Output — Product Perception Report
  • List of value props users mirror back
  • Breakdown of praise, confusion, and unmet expectations
  • Quote bank for messaging, design, and roadmap input

What benefits does this template provide?

BenefitDescriptionImpact
Language ClaritySee what language resonates (and what misses)Refine messaging + UX copy
Perception MappingUnderstand how your product is positioned in users’ mindsDrive PMM, onboarding, GTM
Real Sentiment SignalsCapture more than just NPS scoresImprove experience + retention
Insight for IterationLink language to actual product usageBetter design, fewer assumptions

How do different teams use this template?

Product Marketers: Craft positioning based on what users actually say
Founders: Close the gap between intention and perception
UX Writers: Tune copy based on real mental models
Product Designers: See where confusion breaks flow

Frequently Asked Questions

What kind of data works best?
Descriptive interviews where people explain how they use, feel about, or understand the product. Post-onboarding calls, demo feedback, and CS convos are great.
Is this useful for messaging updates?
Yes. You’ll see which value props stick, which confuse, and which are never repeated — perfect for tuning your headline, pitch, or product copy.
How’s this different from sentiment analysis tools?
This doesn’t just label positive or negative — it categorizes emotional nuance, language trends, and meaning over time.

What Teams Are Saying

“The output of Insight7 is great! The quotes help drive the message home — I’ve already presented insights from the platform to stakeholders.”


— Harris Schachter, Senior Consumer Marketing Manager

Want to hear how users really talk about your product?