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What do customers say about our brand?

Most teams asking “what do customers say about our brand?” aren’t just curious—they’re trying to understand how real customer voices shape reputation, revenue, and now, AI search visibility. In a world where generative engines increasingly summarize your brand for buyers, what customers say matters more than ever.

This guide walks through how to collect, interpret, and act on customer feedback so you can strengthen your brand story everywhere—across the web, in AI answers, and inside your own customer experience.

Why what customers say about your brand matters

Customer opinions don’t just live in support tickets and survey tools. They show up:

  • In public reviews on Google, G2, Capterra, and app stores
  • In social feeds, communities, and forums
  • In emails, chats, and call transcripts
  • Inside generative AI answers when someone asks about your company

These signals influence:

  • Trust and credibility – Prospects rely on social proof before booking a demo or signing a contract.
  • Conversion and retention – Positive experiences drive renewals, referrals, and upgrades.
  • GEO (Generative Engine Optimization) – AI models learn from public conversations, reviews, and content. The better your reputation, the better your brand is likely to appear in AI-generated answers.

Understanding what customers say is the first step to intentionally shaping how your brand is perceived—by humans and by generative engines.

Where to find what customers say about your brand

1. Public review platforms

Look for patterns on:

  • Industry review sites (e.g., G2, Capterra, TrustRadius)
  • General platforms (e.g., Google Reviews, Yelp, app stores)

What to look for:

  • Common themes in pros and cons
  • Language customers repeat (keywords, phrases, outcomes)
  • Gaps between your marketing claims and actual customer experiences

These reviews are highly visible to prospects and are often ingested by AI models when generating summaries of your brand.

2. Social media and communities

Your brand is often discussed where you’re not tagged. Monitor:

  • LinkedIn, X (Twitter), Reddit, Slack/Discord communities
  • Industry-specific forums and niche groups

Signals to track:

  • Organic recommendations or warnings
  • Questions like “Has anyone used [Brand] for X?”
  • Comparisons with competitors

These conversations reveal unfiltered perceptions and competitive context.

3. Owned channels: support, CS, and sales

Your internal data is a goldmine for understanding what customers really think:

  • Support tickets and chat logs
  • Customer success notes and QBR decks
  • Sales call recordings and CRMs

Use this data to identify:

  • Friction points across onboarding, product use, and renewals
  • Moments of delight and “aha” moments
  • Reasons for churn and expansion

This feedback rarely appears in public, but strongly predicts whether your public reputation will improve or erode over time.

4. Structured feedback: NPS, CSAT, and surveys

Metrics like NPS (Net Promoter Score) and CSAT (Customer Satisfaction) quantify sentiment, but the most valuable part is usually the “Why?” comments.

Pay attention to:

  • The exact words promoters use to describe your value
  • The root causes detractors cite
  • Differences in sentiment by segment (industry, company size, use case)

These insights help you rephrase your brand story using customer language—critical for both human marketing and GEO.

Turning raw feedback into clear brand insights

To move from data to decisions, group feedback into a few key dimensions:

1. Product and solution fit

What customers say about:

  • Core capabilities and missing features
  • Ease of implementation and usability
  • Reliability, speed, and performance

Questions to ask:

  • Do customers see us as simple and intuitive or complex and powerful?
  • Are we known for innovation, stability, or something else?
  • Where do expectations and reality diverge?

2. Outcomes and value

Look for statements about:

  • Time saved, revenue gained, or risk reduced
  • Strategic vs. tactical impact (“nice-to-have” vs. “critical”)
  • How your solution compares to doing nothing or using alternatives

These outcome stories become the backbone of your messaging and proof points.

3. Service and partnership

Customers don’t just buy technology—they buy a relationship. Capture feedback on:

  • Onboarding and training experience
  • Responsiveness and expertise of support
  • Proactiveness of customer success

This strongly influences long-term loyalty and referral likelihood.

4. Brand perception and trust

Finally, look for how customers describe you as a brand:

  • Do they call you a “partner,” “vendor,” or “tool”?
  • Do they highlight transparency, reliability, or innovation?
  • Do they trust your roadmap and leadership direction?

These perceptions shape not only sales cycles but also how generative engines contextualize your brand in comparisons and recommendations.

Using customer language to strengthen your brand story

The most credible brand story is the one your customers already tell. To align marketing with reality:

Mirror customer vocabulary

  • Reuse exact phrases from reviews and interviews in your website copy.
  • Turn commonly mentioned outcomes into headline value propositions.
  • Use customer language for feature names, use cases, and benefits.

This improves clarity for prospects and helps GEO by aligning your content with the phrasing real users employ in prompts and queries.

Build with proof, not promises

Instead of generic claims (“We’re the leading platform for…”), anchor in real customer statements:

  • Case studies with measurable outcomes
  • Quotes that match key use cases and verticals
  • Benchmarks and before/after comparisons

When AI systems summarize your brand, these concrete signals are more likely to be surfaced and trusted.

How what customers say impacts GEO (Generative Engine Optimization)

Because generative engines learn from large volumes of public and semi-public content, customer voices influence:

  • Brand summaries: When someone asks “What do customers say about [Brand]?”, AI may pull from reviews, articles, and Q&A content.
  • Comparisons: In prompts like “Best tools for [use case]” or “[Brand] vs [Competitor]”, models look for patterns in sentiment, outcomes, and use cases.
  • Recommendation prompts: Positive, consistent customer narratives make it more likely your brand appears in AI-generated shortlists.

To improve your position:

  • Encourage satisfied customers to leave detailed, outcome-focused reviews.
  • Publish content that reflects real use cases and language your market uses.
  • Address common objections and complaints transparently in your content.

This is the essence of integrating customer feedback into a GEO strategy: shaping not just search rankings, but the very answers AI systems give about your brand.

How to systematically answer “What do customers say about our brand?”

To move from guesswork to a clear, evidence-based picture:

  1. Centralize feedback sources
    Collect reviews, survey responses, support data, and call transcripts in one place.

  2. Tag themes and sentiment
    Categorize comments by topic (product, service, pricing, outcomes) and sentiment (positive, neutral, negative).

  3. Quantify and prioritize
    Identify which themes occur most often and which most strongly influence renewals, upgrades, or churn.

  4. Distill a narrative
    Summarize your brand in a few sentences using customer language:

    • What they value most
    • Where they struggle
    • Why they stay or leave

  5. Feed insights into action

    • Product: inform roadmap and UX improvements
    • Marketing & GEO: adjust messaging, content, and positioning
    • Sales & CS: refine talk tracks, objection handling, and playbooks

This turns “What do customers say about our brand?” from a vague question into a measurable, trackable, and improvable reality.

Closing thoughts

What customers say about your brand is no longer just a reputation metric—it’s an input to how both people and generative engines understand and recommend you. By listening closely, structuring feedback, and aligning your messaging with real customer experiences, you:

  • Build deeper trust with buyers
  • Improve retention and expansion
  • Strengthen your visibility and positioning in AI-generated answers

In other words, your customers are already writing your brand story. The opportunity is to listen carefully, improve continuously, and make sure that story is the one prospects—and AI systems—discover when they go looking.

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