# Using Metrics in Backlink Audits: A Practical Guide

Learn how to use SEO metrics effectively in backlink audits. Understand what metrics to track, how to interpret them, and common pitfalls to avoid.

Canonical: https://backlinkgrid.com/backlink-audit/using-metrics


Metrics provide structure for backlink audits, turning subjective assessments into comparable data. However, metrics are often misunderstood or over-relied upon. This guide explains how to use metrics effectively in your audits.

## Metrics Overview

### Purpose of Metrics

Metrics help you:

- **Compare objectively**: Benchmark against competitors or past performance
- **Filter efficiently**: Quickly sort large link datasets
- **Identify patterns**: Spot trends in link acquisition
- **Track progress**: Measure improvement over time

### Metrics Limitations

Remember that metrics:

- **Are estimates**: Not actual Google ranking factors
- **Can be manipulated**: Inflated through artificial means
- **Miss context**: Don't capture relevance or editorial quality
- **Lag reality**: Update on varying schedules

Use metrics as tools, not definitive answers.

---

## Key Audit Metrics

### Referring Domains

**What it is**: Count of unique domains linking to your site

**Why it matters**: More important than total backlinks—indicates breadth of link profile

**How to use**:
- Track growth/decline over time
- Compare to competitors
- Goal setting for link building

**Benchmark interpretation**:

| Change | Interpretation |
|--------|---------------|
| Growing steadily | Healthy acquisition |
| Declining | Losing links faster than gaining |
| Spiky | Investigate causes |
| Flat | May need more link building |

### Total Backlinks

**What it is**: Raw count of all links pointing to your site

**Why it matters**: Shows distribution—one domain linking many times vs many linking once

**How to use**:
- Calculate backlinks per referring domain
- Identify sites linking heavily (normal for genuine partnerships, suspicious otherwise)

**Healthy patterns**:
- Average 1-3 links per referring domain for most sites
- Some variation is normal
- Very high averages may indicate spam or site-wide links

### Domain Authority/Rating

**What it is**: Third-party estimates of domain strength (Moz DA, Ahrefs DR, etc.)

**Why it matters**: Helps categorise link quality at scale

**How to use**:
- Set minimum thresholds for opportunities
- Calculate average quality of link profile
- Compare competitor authority levels

**Important caveats**:
- Can be manipulated
- Different tools show different numbers
- Doesn't measure relevance

See: [Authority Metrics Explained](/backlink-quality/authority-metrics)

### Follow vs Nofollow Ratio

**What it is**: Proportion of followed (value-passing) links

**Why it matters**: Followed links directly pass PageRank

**Healthy ranges**:
- 60-80% followed is typical for healthy profiles
- Too high (95%+) might look unnatural
- Too low may indicate link earning challenges

**How to use**:
- Track in audit overview
- Investigate if ratio is unusual
- Natural profiles have mix of both

### Anchor Text Distribution

**What it is**: Categories of text used in links to your site

**Why it matters**: Unnatural anchor text patterns suggest manipulation

**Categories to track**:

| Type | Example | Target % |
|------|---------|----------|
| Branded | "Backlink Squares" | 40-60% |
| URL/Naked | "backlinkssquares.com" | 15-25% |
| Generic | "click here", "this site" | 10-20% |
| Keyword-rich | "SEO backlink tools" | 5-15% |
| Other | Everything else | Variable |

**Warning signs**:
- Exact-match keywords over 20%
- Single phrase dominating
- Unnatural concentration

### Link Velocity

**What it is**: Rate of new link acquisition over time

**Why it matters**: Sudden changes may indicate issues or opportunities

**How to track**:
- New referring domains per month
- Compare to historical averages
- Note significant events (content launches, PR)

**Concerning patterns**:
- Sudden spikes without clear cause
- Sustained unnatural velocity
- Abrupt drops in acquisition

### Traffic Estimates

**What it is**: Estimated visitors to linking domains

**Why it matters**: Links from sites with real traffic provide referral value and suggest legitimacy

**How to use**:
- Filter for minimum traffic thresholds
- Identify high-value links (high traffic + high relevance)
- Flag suspicious discrepancies (high authority, zero traffic)

**Tools**:
- SimilarWeb
- Ahrefs organic traffic estimate
- Semrush traffic estimates

---

## Metric-Based Segmentation

### Quality Tier Assignment

Use metrics for initial categorisation:

**Tier 1 (High Quality)**:
- DA/DR: 50+
- Traffic: 10,000+/month
- Followed: Yes
- Relevance: Verify manually

**Tier 2 (Good Quality)**:
- DA/DR: 30-50
- Traffic: 1,000-10,000/month
- Followed: Yes
- Relevance: Verify manually

**Tier 3 (Acceptable)**:
- DA/DR: 15-30
- Traffic: 100-1,000/month
- Followed: Either
- Relevance: Check if concerning

**Tier 4 (Low Quality)**:
- DA/DR: under 15
- Traffic: under 100/month
- Followed: Either
- Relevance: Probably low

**Tier 5 (Review Required)**:
- Spam scores flagged
- Traffic/authority discrepancy
- Other concerning signals

### Efficiency Through Metrics

For large audits, use metrics to prioritise:

1. **Auto-approve**: High authority + traffic + clean signals
2. **Auto-flag**: Spam scores + zero traffic + low authority
3. **Manual review**: Middle ground and discrepancies

This approach handles thousands of links efficiently while catching issues.

---

## Comparative Metrics

### Historical Comparison

Track your own metrics over time:

**Monthly tracking**:
- Referring domains: ____
- Average DR/DA: ____
- New domains this month: ____
- Lost domains this month: ____

**Trend analysis**:
- Is quality improving?
- Is growth rate adequate?
- Any concerning changes?

### Competitive Comparison

Benchmark against competitors:

**Metrics to compare**:

| Metric | Your Site | Comp 1 | Comp 2 | Gap |
|--------|-----------|--------|--------|-----|
| Referring domains | | | | |
| DR/DA | | | | |
| Monthly velocity | | | | |
| Follow % | | | | |

**Gap analysis**:
- Where are you behind?
- What's realistic to close?
- What tactics might help?

---

## Spotting Metric Manipulation

### Red Flags

**High authority, no traffic**:
- DR 70, but under 500 visitors/month
- Suggests artificial inflation
- Often PBN or expired domain

**Sudden authority jumps**:
- DA increased 20 points in one month
- Usually indicates manipulation
- Investigate the cause

**Mismatched signals**:
- High authority but thin content
- No social presence despite size
- Traffic from unusual sources

### Verification Steps

When metrics look suspicious:

1. **Check traffic independently**: SimilarWeb, not just SEO tool
2. **Review content quality**: Visit and read
3. **Check their backlinks**: Who links to them?
4. **Research reputation**: What do others say?

---

## Common Metric Mistakes

### Over-Reliance on Single Metrics

**Mistake**: Judging quality solely by DA/DR

**Problem**: Misses relevance, context, manipulation

**Solution**: Use multiple metrics plus manual verification

### Ignoring Context

**Mistake**: Applying same thresholds everywhere

**Problem**: New sites may have low metrics legitimately

**Solution**: Consider site age, industry, and specifics

### Chasing Metric Improvements

**Mistake**: Optimising for DA/DR rather than actual SEO value

**Problem**: May acquire poor links that inflate metrics

**Solution**: Focus on quality and rankings, let metrics follow

### Inconsistent Measurement

**Mistake**: Using different tools/methods across audits

**Problem**: Can't compare accurately over time

**Solution**: Standardise your metrics and tools

---

## Practical Application

### Audit Workflow

**Step 1: Export data with metrics**
- Referring domains
- DR/DA scores
- Traffic estimates
- Follow status
- Spam scores

**Step 2: Initial sort**
- Highest to lowest authority
- Flag low traffic despite high authority
- Identify spam score outliers

**Step 3: Segment by tier**
- Assign quality tiers based on metrics
- Count distribution across tiers

**Step 4: Manual review**
- Sample from each tier
- Focus on flagged discrepancies
- Verify tier assignments

**Step 5: Calculate summary metrics**
- Average quality
- Distribution percentages
- Comparison to benchmarks

### Reporting Metrics

**For stakeholder reports**:

- Keep it simple
- Focus on trends
- Provide context
- Avoid jargon

**Key metrics to report**:
- Referring domains (growth)
- Average quality score
- Comparison to competitors
- Notable changes

---

## Summary

Using metrics effectively in audits:

**Key metrics to track**:
- Referring domains (breadth)
- Domain authority (quality proxy)
- Traffic estimates (legitimacy)
- Anchor text distribution (naturalness)
- Follow ratio (value potential)

**Best practices**:
- Use multiple metrics together
- Combine with manual verification
- Track consistently over time
- Compare to meaningful benchmarks

**Avoid**:
- Over-reliance on single metrics
- Ignoring context
- Chasing metric improvements
- Inconsistent measurement

Metrics are valuable tools when used appropriately—as inputs to judgment, not replacements for it.

---

## What to Read Next

- [Authority Metrics Explained](/backlink-quality/authority-metrics)
- [Audit Tools Compared](/backlink-audit/audit-tools)
- [Competitor Backlink Analysis](/backlink-audit/competitor-analysis)