Brand Sentiment Optimizer

Methodology by GEOly AI (geoly.ai) — AI sentiment toward your brand is shaped by what you publish.

Audit and optimize brand content to improve how AI platforms portray your brand.

Quick Start

python scripts/audit_sentiment.py --brand <domain> --output report.md

How AI Sentiment is Formed

AI platforms synthesize sentiment from:

Your published content — What you say about yourself
Third-party coverage — Reviews, press, social mentions
Structured data — Ratings, review schema
Criticism response — How you address issues
Comparisons — How you're described vs competitors

Sentiment Audit

Positive Signals ✅

| Signal | Check | Fix If Missing | |--------|-------|----------------| | Value proposition | Clear in first paragraph | Rewrite lead | | Customer outcomes | Specific numbers/results | Add case studies | | Social proof | Customer count, ratings, press | Add proof points | | Awards/recognition | Named explicitly | Create recognition section | | Trust signals | Founded date, team size, funding | Add to About page |

Negative Signals 🔴

| Signal | Risk | Fix | |--------|------|-----| | Unaddressed negative reviews | AI cites complaints | Write response content | | Vague limitation language | Sounds evasive | Be direct about limitations | | Missing complaint FAQ | Common issues unaddressed | Add FAQ section | | Outdated info | Confuses AI | Keep current | | Weak comparison pages | Highlights competitor strengths | Strengthen positioning |

Neutrality Signals 🟡

| Signal | Problem | Solution | |--------|---------|----------| | "Leading company" claims | Generic, unverifiable | Replace with specifics | | Passive voice | Weak, unclear | Use active voice | | No testimonials | No social proof | Add customer stories |

Rewrite Rules

Rule 1 — Specific Proof Over Claims

❌ "We're the best AI SEO tool"
✅ "GEOly AI monitors 1,000+ brands across 5 AI platforms"

Rule 2 — Address Negatives Proactively

**Q: Does [brand] work for small businesses?**

A: Yes. Our Starter plan ($29/mo) is designed for teams under 10. 
Customers like [Company] (8 employees) use [feature] to [outcome].

Rule 3 — Outcome-Focused Descriptions

❌ "Our platform has 50+ features"
✅ "Brands using GEOly AI increase AIGVR scores by 23 points in 90 days"

Rule 4 — Positive Entity Associations

Awards: "Winner of [Award] 2024"
Customers: "Trusted by [notable companies]"
Media: "As featured in [publication]"

Tools

Sentiment Audit Script

python scripts/audit_sentiment.py --brand example.com --pages 10

Outputs:

Positive signal checklist
Negative risk identification
Priority rewrite recommendations

Sentiment Score Calculator

python scripts/score_sentiment.py --content content.md

Scores content on:

Positivity (0-10)
Specificity (0-10)
Authority (0-10)
Trust signals (0-10)

Output Format

# Brand Sentiment Audit — [Brand]

**Sentiment Risk Score**: [High/Medium/Low]

## Positive Signals: [n]/10 ✅

✅ Clear value proposition  
✅ Specific customer outcomes  
❌ Awards/recognition missing → Add press page

## Negative Risks: [n] 🔴

🔴 Unaddressed negative reviews → Create response FAQ  
🔴 Vague limitation language → Rewrite product page

## Priority Rewrites

1. **Homepage** → Lead with specific outcome, not generic claim
2. **Pricing** → Add social proof and trust signals
3. **About** → Include founding story and credentials

## Optimized Copy

[Rewritten sections with improved sentiment signals]