# Your ARI Score Explained: What It Means and How to Improve It
**Primary keyword:** ARI score interpretation
**Length:** 1,000 words
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## What Your ARI Score Means
**ARI (AI Readability Index):** 1–100 scale measuring how well AI agents understand you.
### Score Ranges
**80–100: Excellent**
- AI agents understand you clearly
- You show up in recommendations
- Your positioning survives compression
- Agents can match you to customer needs
**60–79: Good**
- AI agents get most of it
- You show up in recommendations (but not top)
- Some clarity gaps remain
- Fix biggest gaps for 80+
**40–59: Fair**
- AI agents get the gist but unclear details
- You might appear in recommendations (depends on customer query)
- Major clarity needed
- Fix 3–4 things to get to 60+
**20–39: Weak**
- AI agents flatten you to category average
- You're not recommended unless customer asks by name
- Complete positioning overhaul needed
**<20: Severe** - AI agents can't understand what you do - You're invisible to agent-mediated discovery - Urgent: rebuild product pages, add specs, clarify positioning --- ## Score Breakdown: The 5 Dimensions Your ARI report breaks down into 5 dimensions: 1. **Opinion Density** (Do you take positions?) 2. **Factual Provability** (Are claims backed by data?) 3. **DOM Extractability** (Can AI easily pull your data?) 4. **Semantic Specificity** (Is your positioning specific?) 5. **Differentiation Signal** (Do you stand out or blend in?) Each dimension is scored 1–100. Your overall ARI is the average. --- ## Improvement Path **If you score 40–59:** - Fix 1 dimension (biggest gap) to move from 40 → 50 - Fix another dimension to move from 50 → 60 - Takes 2–4 weeks per dimension **If you score 60–79:** - 1–2 quick wins get you to 70+ - Usually: add schema + clarify positioning - Takes 1–2 weeks **If you score 80+:** - Maintenance only - Monthly reviews to keep score high --- ## Quick Wins by Dimension **Low Opinion Density?** → Rewrite product description to be more opinionated about who you serve **Low Factual Provability?** → Replace vague claims with data (add case studies, metrics, testing results) **Low DOM Extractability?** → Add structure (headers, bullets), add schema markup **Low Semantic Specificity?** → Narrow your audience ("for teams 5–50" not "for teams") **Low Differentiation Signal?** → Add comparison section, explain how you're different --- **Word count:** 1,000