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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?

Webinar on Sep 5: How to Turn Every Customer Call Into CX Insights That Drive Revenue
Learn how to transform everyday customer calls into actionable CX insights that boost retention and drive revenue growth without adding extra work for your team.