January 21, 2025 12 min read
Most sites have dozens or hundreds of pages that could drive more traffic with strategic updates. The problem? Identifying which pages to prioritize and what specific changes will move the needle takes hours per page.
Content audits are necessary but painful. Spreadsheets. Manual analysis. Subjective scoring. By the time you finish auditing 100 pages, your data is already outdated and you're exhausted.
AI changes the economics of content audits entirely. What used to take a content strategist 40 hours now takes 2-3 hours of setup plus AI processing time. The analysis is often more thorough than manual reviews because AI doesn't get tired or skip steps.
This guide provides a practical framework for AI-powered content audits specifically for WordPress and Shopify sites, with actionable prompts, tooling recommendations, and prioritization strategies.
Why Your Content Needs Regular Audits
Before diving into AI implementation, let's establish why this matters with concrete data.
The Reality of Content Decay
Content degradation isn't theoretical—it's measurable and predictable. Here's what happens to typical blog content over time:
Data source: Analysis of 847 client blog posts tracked over 3 years (2021-2024). Posts without regular updates showed consistent decline patterns across industries.
Search algorithms evolve constantly:
- Google updates search intent interpretation quarterly
- Competitor content improves, raising the bar for rankings
- User expectations for content depth and format change
- SERP features (Featured Snippets, People Also Ask) shift which content types win visibility
Your content degrades over time:
- Statistics and examples become outdated
- Internal links break as site structure changes
- Technical SEO elements (meta tags, schema, images) fall out of compliance
- Screenshots and UI examples become visually dated, reducing trust
- Legal and regulatory information becomes inaccurate or incomplete
Opportunity cost is high:
- Pages ranking positions 11-20 need minor optimization to break into top 10
- High-traffic pages with poor conversion rates waste your best visibility
- Content gaps mean competitors capture traffic you should own
- Outdated content damages brand authority and user trust
Content Audit Impact: Real Numbers
Here's what happens when you implement systematic content audits versus ad-hoc updates:
Client reality check: We audited a WordPress site with 200 blog posts. Manual audit identified 12 priority updates. AI audit found 47 pages with specific, actionable optimization opportunities. The difference? Traffic increased 63% within 90 days of implementing AI recommendations.
The manual audit team focused on obvious issues (missing meta descriptions, thin content). AI identified subtle patterns: pages with high impressions but low CTR, topic clusters with broken internal linking, and ranking position clusters where small improvements would compound.
Manual audits miss opportunities because humans get overwhelmed. AI doesn't.
The Cost of Ignoring Content Audits
Let's quantify what you lose by not auditing regularly:
Scenario: E-commerce site with 500 pages (300 products, 150 blog posts, 50 category/info pages)
Without systematic audits:
- 40-60 pages have missing or poor meta descriptions (3-5% CTR loss per page)
- 80-120 pages have outdated content (15-30% traffic decline)
- 20-30 high-potential pages stuck on page 2 (missing 80% of available traffic)
- 15-25 pages have technical issues (slow load, broken links, missing schema)
Estimated annual opportunity cost: $45,000-$85,000 in lost organic traffic value for a mid-size business (based on industry average $2-$4 per organic visit value).
With AI-powered quarterly audits:
- Investment: 40-60 hours annually ($3,000-$6,000 if outsourced)
- Return: Capture 40-60% of missed opportunities
- Net value: $15,000-$45,000 additional annual traffic value
- ROI: 3-8x in year one, improving in subsequent years
The AI Content Audit Framework
Our proven four-stage process works for both WordPress and Shopify:
Process Overview and Timeline
Here's how the complete audit process flows, with realistic time estimates:
STAGE 1: DATA COLLECTION (2-4 hours)
├─ Content Inventory Export (1-2 hours)
│ └─ WordPress: REST API or plugin export
│ └─ Shopify: CSV exports + manual collection
├─ Performance Data Gathering (30-60 min)
│ └─ [Google Analytics 4](https://analytics.google.com): Traffic, engagement, conversions
│ └─ [Google Search Console](https://search.google.com/search-console): Rankings, impressions, CTR
└─ Technical SEO Crawl (30-60 min)
└─ [Screaming Frog](https://www.screamingfrog.co.uk/seo-spider/) or similar tool
└─ Export technical issues, page speed, schema status
STAGE 2: AI-POWERED ANALYSIS (1-3 hours)
├─ Data Consolidation (30 min)
│ └─ Merge all data sources into master spreadsheet
├─ AI Processing (15-45 min)
│ └─ Feed data to Claude/ChatGPT with structured prompts
│ └─ Review and refine AI recommendations
└─ Opportunity Categorization (30-60 min)
└─ Group findings by issue type and priority level
STAGE 3: PRIORITIZATION & PLANNING (2-3 hours)
├─ Priority Scoring (60-90 min)
│ └─ Apply impact vs. effort framework
│ └─ Calculate ROI potential for top opportunities
├─ Resource Planning (30-60 min)
│ └─ Assign updates to team members
│ └─ Estimate hours required per update
└─ Calendar Building (30 min)
└─ Create content refresh schedule
└─ Set measurement checkpoints
STAGE 4: IMPLEMENTATION & MEASUREMENT (Ongoing)
├─ Quick Wins Week 1-2 (5-10 hours)
│ └─ Meta tag updates, title optimization
├─ Medium Updates Week 3-6 (10-20 hours)
│ └─ Content expansions, internal linking
├─ Major Refreshes Week 7-12 (15-30 hours)
│ └─ Complete rewrites, structure overhauls
└─ Performance Tracking (Monthly)
└─ Compare pre/post metrics
└─ Feed results back to AI for learning
TOTAL TIME INVESTMENT: 10-15 hours setup + 30-60 hours execution
TRADITIONAL APPROACH: 80-120 hours for comparable results
TIME SAVINGS: 70-80%
Stage 1: Data Collection
- Export content inventory (URLs, titles, meta, word count, etc.)
- Pull performance metrics (traffic, rankings, engagement)
- Gather technical SEO data (page speed, mobile usability, errors)
Stage 2: AI-Powered Analysis
- Feed data to AI with structured prompts
- Identify optimization opportunities by category
- Score pages for update priority
Stage 3: Prioritization & Planning
- Rank pages by potential impact vs. effort required
- Create specific action items for each page
- Build content refresh calendar
Stage 4: Implementation & Measurement
- Execute updates systematically
- Track performance changes
- Feed results back into audit process for continuous improvement
Let's break down each stage with platform-specific instructions.
Stage 1: Collecting Your Content Data
AI analysis quality depends on input data quality. Here's exactly what to gather.
Content Inventory Checklist
Use this comprehensive checklist to ensure you capture all critical data points:
Priority order: If time is limited, collect Basic Content → Dates → Performance → SEO Elements first. These four categories provide 80% of the value for AI analysis.
WordPress Data Collection
Core content inventory:
Use a plugin like Export All URLs, SEOPress, or Rank Math to export:
- Page URLs
- Titles (H1 and title tag)
- Meta descriptions
- Word count
- Publication date and last modified date
- Author
- Categories and tags
- Featured image status
- Number of internal links pointing to the page
WordPress REST API Data Export Script:
// Node.js script to extract content data from WordPress REST API
const axios = require('axios');
const fs = require('fs');
const WORDPRESS_URL = 'https://your-site.com';
const API_BASE = `${WORDPRESS_URL}/wp-json/wp/v2`;
async function fetchAllPosts() {
let allPosts = [];
let page = 1;
let hasMore = true;
while (hasMore) {
try {
const response = await axios.get(`${API_BASE}/posts`, {
params: {
page: page,
per_page: 100,
_embed: true // Include author and featured media
}
});
const posts = response.data;
// Extract relevant data
const postData = posts.map(post => ({
id: post.id,
url: post.link,
title: post.title.rendered,
title_tag: post.yoast_head_json?.title || post.title.rendered,
meta_description: post.yoast_head_json?.description || '',
word_count: post.content.rendered.split(/\s+/).length,
published: post.date,
modified: post.modified,
author: post._embedded?.author?.[0]?.name || '',
categories: post._embedded?.['wp:term']?.[0]?.map(t => t.name) || [],
tags: post._embedded?.['wp:term']?.[1]?.map(t => t.name) || [],
featured_image: post._embedded?.['wp:featuredmedia']?.[0]?.source_url || null,
excerpt: post.excerpt.rendered.replace(/<[^>]*>/g, '').substring(0, 200)
}));
allPosts = allPosts.concat(postData);
// Check if there are more pages
hasMore = posts.length === 100;
page++;
console.log(`Fetched page ${page - 1}: ${posts.length} posts`);
} catch (error) {
if (error.response?.status === 400) {
// No more pages
hasMore = false;
} else {
console.error('Error fetching posts:', error.message);
break;
}
}
}
return allPosts;
}
async function exportToCSV(posts) {
const headers = Object.keys(posts[0]).join(',');
const rows = posts.map(post => {
return Object.values(post).map(value => {
// Handle arrays and escape commas
if (Array.isArray(value)) {
return `"${value.join('; ')}"`;
}
return `"${String(value).replace(/"/g, '""')}"`;
}).join(',');
});
const csv = [headers, ...rows].join('\n');
fs.writeFileSync('wordpress-content-inventory.csv', csv);
console.log(`Exported ${posts.length} posts to CSV`);
}
async function exportToJSON(posts) {
fs.writeFileSync('wordpress-content-inventory.json', JSON.stringify(posts, null, 2));
console.log(`Exported ${posts.length} posts to JSON`);
}
// Execute
(async () => {
console.log('Starting WordPress content export...');
const posts = await fetchAllPosts();
await exportToCSV(posts);
await exportToJSON(posts);
console.log('Export complete!');
})();
WordPress SQL Query for Advanced Data:
-- Export comprehensive content data directly from WordPress database
SELECT
p.ID,
p.post_title,
p.post_name AS slug,
p.post_status,
p.post_date,
p.post_modified,
p.post_type,
LENGTH(p.post_content) - LENGTH(REPLACE(p.post_content, ' ', '')) + 1 AS word_count,
(SELECT meta_value FROM wp_postmeta WHERE post_id = p.ID AND meta_key = '_yoast_wpseo_title') AS seo_title,
(SELECT meta_value FROM wp_postmeta WHERE post_id = p.ID AND meta_key = '_yoast_wpseo_metadesc') AS meta_description,
(SELECT meta_value FROM wp_postmeta WHERE post_id = p.ID AND meta_key = '_yoast_wpseo_focuskw') AS focus_keyword,
(SELECT COUNT(*) FROM wp_comments WHERE comment_post_ID = p.ID AND comment_approved = 1) AS comment_count,
u.display_name AS author,
CONCAT('https://your-site.com/?p=', p.ID) AS permalink
FROM
wp_posts p
LEFT JOIN
wp_users u ON p.post_author = u.ID
WHERE
p.post_status = 'publish'
AND p.post_type IN ('post', 'page')
ORDER BY
p.post_modified DESC;
Performance metrics:
From Google Analytics 4:
- Organic sessions (last 90 days)
- Average engagement time
- Bounce rate
- Conversion events (if tracked)
From Google Search Console:
- Average position
- Total impressions
- Total clicks
- Click-through rate
Technical SEO data:
From Screaming Frog or similar crawler:
- Page load time
- Mobile usability issues
- Schema markup status
- Image optimization (alt text, size)
- H1/H2/H3 structure
Consolidation:
Combine all data sources into a single spreadsheet with one row per URL. Most critical columns:
- URL
- Title
- Meta Description
- Word Count
- Organic Sessions (90 days)
- Average Position
- Impressions
- Page Load Time
- Schema Status (yes/no)
- Last Modified Date
Shopify Data Collection
Product pages:
From Shopify admin or via CSV export:
- Product URLs
- Product titles
- Descriptions (length in characters)
- Meta titles and descriptions
- Image count and alt text status
- Collections assigned
- Availability status
Shopify CSV Export Enhancement Script:
// Enhance Shopify product export with additional SEO data
const fs = require('fs');
const csv = require('csv-parser');
const createCsvWriter = require('csv-writer').createObjectCsvWriter;
async function enhanceShopifyExport(inputFile, outputFile) {
const products = [];
// Read base Shopify export
fs.createReadStream(inputFile)
.pipe(csv())
.on('data', (row) => {
products.push({
handle: row.Handle,
title: row.Title,
description: row['Body (HTML)'],
description_length: row['Body (HTML)'].length,
word_count: row['Body (HTML)'].split(/\s+/).length,
meta_title: row['SEO Title'] || row.Title,
meta_description: row['SEO Description'],
meta_title_length: (row['SEO Title'] || row.Title).length,
meta_description_length: (row['SEO Description'] || '').length,
url: `https://your-store.myshopify.com/products/${row.Handle}`,
product_type: row.Type,
vendor: row.Vendor,
tags: row.Tags,
published: row['Published'],
image_count: countImages(row),
// Add placeholders for performance data to merge later
sessions_90d: '',
avg_position: '',
impressions: '',
clicks: ''
});
})
.on('end', async () => {
const csvWriter = createCsvWriter({
path: outputFile,
header: [
{id: 'url', title: 'URL'},
{id: 'title', title: 'Title'},
{id: 'description_length', title: 'Description Length'},
{id: 'word_count', title: 'Word Count'},
{id: 'meta_title', title: 'Meta Title'},
{id: 'meta_title_length', title: 'Meta Title Length'},
{id: 'meta_description', title: 'Meta Description'},
{id: 'meta_description_length', title: 'Meta Description Length'},
{id: 'product_type', title: 'Product Type'},
{id: 'vendor', title: 'Vendor'},
{id: 'image_count', title: 'Image Count'},
{id: 'sessions_90d', title: 'Sessions (90d)'},
{id: 'avg_position', title: 'Avg Position'},
{id: 'impressions', title: 'Impressions'},
{id: 'clicks', title: 'Clicks'}
]
});
await csvWriter.writeRecords(products);
console.log(`Enhanced export created: ${outputFile}`);
console.log(`Next: Merge with GA4 and GSC data for complete inventory`);
});
}
function countImages(row) {
// Count image columns in Shopify export
let count = 0;
for (let i = 1; i <= 10; i++) {
if (row[`Image Src ${i}`]) count++;
}
return count;
}
// Usage
enhanceShopifyExport('shopify-export.csv', 'shopify-enhanced-inventory.csv');
Performance metrics:
From Google Analytics 4:
- Product page views
- Add-to-cart rate
- Conversion rate
- Organic traffic percentage
From Google Search Console:
- Same as WordPress (impressions, clicks, position, CTR)
Collection pages:
Export collection URLs and titles. Check:
- Description length and quality
- Keyword optimization
- Internal linking from homepage/nav
- Traffic and conversion performance
Blog content (if applicable):
Follow WordPress process above for Shopify blog posts.
Pro Data Collection Tips
Segment by content type:
Create separate tabs or files for:
- Blog posts
- Product pages
- Collection/category pages
- Service pages
- Landing pages
Different content types need different optimization strategies. Segmentation helps AI provide more relevant recommendations.
Include competitive context:
For your top 20 highest-traffic pages, add columns:
- Top 3 competitor URLs for the target keyword
- Competitor average word count
- Competitor content format (list, guide, comparison, etc.)
This context helps AI identify specific competitive gaps.
Data Quality Checks Before AI Analysis
Run these validation checks before feeding data to AI:
Pro tip: Create a data quality scorecard. Don't proceed to AI analysis until your data quality score is 85%+ (all checks passed except minor missing optional fields).
Stage 2: AI-Powered Analysis with Specific Prompts
Now the AI does the heavy lifting. Here are battle-tested prompts for different audit objectives.
Understanding AI Analysis Capabilities
Before diving into prompts, understand what AI can and cannot reliably analyze:
AI Excels At:
- Pattern recognition across large datasets (100+ pages)
- Comparing your content to established best practices
- Identifying technical issues (missing meta, length problems)
- Spotting content gaps based on semantic relationships
- Prioritizing opportunities using multi-factor scoring
- Generating specific, actionable recommendations
AI Struggles With:
- Understanding nuanced brand voice (needs examples)
- Evaluating content accuracy (can't fact-check stats)
- Judging visual content quality (images, videos)
- Predicting exact ranking improvements (too many variables)
- Understanding industry-specific terminology without context
Mitigation strategy: Provide AI with examples, context, and constraints. Review critical recommendations manually before implementation.
Prompt 1: Comprehensive Page Audit
Upload your content inventory spreadsheet and use this prompt:
Analyze this content inventory for optimization opportunities. For each page, evaluate:
1. SEO Technical Issues:
- Is the meta description optimized (140-160 chars, includes primary keyword, compelling)?
- Does the title tag follow best practices (50-60 chars, keyword at front, click-worthy)?
- Is word count competitive (compare to typical top 10 results for the keyword)?
2. Content Quality Indicators:
- Based on the title, does the content likely match search intent?
- Are there obvious content gaps based on related keywords and questions?
- Is the content recent enough or does the topic require freshness?
3. Performance Red Flags:
- Pages with high impressions but low CTR (under 3% for position <10)
- Pages with good rankings (position 1-10) but poor engagement time
- Pages ranking positions 11-20 that could break into top 10
4. Technical Optimization:
- Missing or weak schema markup
- Slow page load times (over 3 seconds)
- No featured image or poor image optimization
Output as a table with columns:
URL | Priority (High/Medium/Low) | Issues Found | Recommended Actions | Estimated Impact
Focus on the top 30 highest-opportunity pages first.
What you'll get: A prioritized list of pages with specific issues and actions. This typically identifies 3-5x more opportunities than manual audits.
Sample AI Output Interpretation:
When AI returns recommendations, look for these high-value patterns:
Prompt 2: Content Gap Analysis
Based on this content inventory, identify content gaps:
1. Keyword Coverage Gaps:
- What related keywords or topics are missing based on the existing content?
- Where do we have superficial coverage that should be expanded?
- What competitor topics are we not addressing?
2. Funnel Stage Gaps:
- Do we have sufficient top-of-funnel educational content?
- Are we missing middle-funnel comparison/evaluation content?
- Do we have enough bottom-funnel conversion-focused pages?
3. Format Gaps:
- Are we missing visual content (infographics, videos)?
- Do we need more interactive tools or calculators?
- Should we create downloadable resources (templates, checklists)?
For each gap, provide:
- Gap description
- Target keywords to address
- Recommended content type/format
- Priority level (based on search volume and competition)
Focus on gaps where we can realistically compete given our domain authority.
Why this works: AI connects patterns across your entire content inventory that humans miss. It spots topic clusters you started but didn't complete, identifies format preferences in your niche, and recommends logical content expansion.
Real-world content gap example:
Client: B2B SaaS company selling project management software Existing content: 45 blog posts, mostly feature explanations and company updates AI-identified gaps:
Result after filling gaps: 127% increase in organic traffic over 6 months, 43% increase in demo requests.
Prompt 3: Shopify Product Description Audit
Specific prompt for e-commerce product pages:
Analyze these Shopify product pages for SEO and conversion optimization:
For each product:
1. Title Optimization:
- Does the title include the primary keyword naturally?
- Is it under 60 characters for full display in search results?
- Does it differentiate from competitors?
2. Description Analysis:
- Is the description at least 300 words? (minimum for SEO)
- Does it address key buying questions? (features, benefits, use cases)
- Is it formatted for scannability? (bullets, short paragraphs, bolded key terms)
3. Meta & Schema:
- Is Product schema implemented correctly?
- Does the meta description include price, brand, and key benefit?
- Are review ratings displayed (if available)?
4. Image Optimization:
- Are all images using descriptive alt text?
- Is there a minimum of 3-5 product images?
- Are images under 200KB for fast loading?
5. Conversion Elements:
- Does the description create urgency or scarcity where appropriate?
- Are there customer use case examples or testimonials?
- Is cross-sell or upsell context provided?
Output as a scored table with specific recommendations for each product.
Result: Specific, actionable product page improvements. Especially valuable for stores with 50+ products where manual review isn't practical.
Product Description Optimization Framework:
Use this framework to evaluate AI recommendations for product pages:
Example transformation:
Before (Poor product description):
Camping Tent - 4 Person
Spacious camping tent perfect for family trips.
Made with durable materials. Easy to set up.
Price: $199
After (Optimized for SEO + Conversion):
4-Person Waterproof Camping Tent with Vestibule – Quick Setup Family Tent
Perfect for weekend camping trips and music festivals, this spacious 4-person tent
combines weather protection with family-friendly features.
Key Features:
• Sleeps 4 adults comfortably with 60 sq ft interior space
• Fully seam-sealed rainfly keeps you dry in heavy rain (tested to 2000mm)
• Color-coded poles and clips allow 10-minute setup (even in the dark)
• Large vestibule (20 sq ft) for gear storage and cooking area
• Multiple mesh windows provide ventilation while keeping bugs out
• Includes tent body, rainfly, poles, stakes, guy lines, and carry bag
Use Cases:
- Family camping: Room for parents + 2 kids with space for bags
- Festival camping: Quick setup when you arrive tired
- Car camping: Spacious enough to stand and change clothes
- Backyard adventures: Great starter tent for kids
Construction:
75D polyester fabric with full-coverage rainfly, fiberglass poles rated for 30mph winds
What Customers Say: "Set this up at sunset after a long drive - took 12 minutes with
my 10-year-old helping. Stayed dry through a storm that night." - Sarah M., Vermont
In Stock: 43 available | Fast Shipping: Order by 2PM for same-day dispatch
SEO improvement: Original had ~30 words, new version has ~200 words with natural keyword placement Conversion improvement: Addresses objections (setup difficulty, space, weather), provides social proof, creates urgency
Prompt 4: Internal Linking Opportunity Finder
Analyze this content inventory to identify internal linking opportunities:
1. Orphan Pages:
- Which pages have few or no internal links pointing to them?
- Why are these pages isolated?
- What existing content should link to them?
2. Content Clusters:
- Identify topically related pages that should cross-reference each other
- Suggest natural anchor text for linking between cluster pages
- Highlight pillar pages that need more supporting cluster links
3. Conversion Path Optimization:
- Which high-traffic blog posts should link to service/product pages?
- What educational content should point to bottom-funnel content?
- Are there broken internal link opportunities? (old posts referencing topics we've since published on)
Output format:
Source Page | Target Page | Recommended Anchor Text | Context for Link | Priority
Prioritize links that improve user journey from awareness to conversion.
Why this matters: Internal linking is one of the most underutilized SEO tactics. This prompt helps AI map your content relationships and build a strategic linking plan.
Internal Linking Strategy Matrix:
Use this to guide your internal linking implementation:
Real linking implementation case study:
Client: Home services company with 60 blog posts Problem: High bounce rate, low conversion despite decent traffic AI-identified opportunity: Only 3 blog posts linked to service pages; most internal links went to other blog posts
Solution implemented:
- Added contextual links from educational content to relevant service pages
- Created topic clusters around main service categories
- Built conversion paths from awareness → consideration → decision
Example link insertion:
Original sentence: "Regular HVAC maintenance can save homeowners hundreds of dollars annually."
Optimized sentence: "Regular HVAC maintenance can save homeowners hundreds of dollars
annually. Our preventive maintenance plans include bi-annual inspections, filter
changes, and priority service scheduling to keep your system running efficiently."
Links added:
- "HVAC maintenance" → /services/hvac-maintenance (contextual)
- "preventive maintenance plans" → /plans/preventive-maintenance (conversion)
Results:
- Average session duration: +45% (users navigating deeper)
- Service page traffic: +89% (from internal referral)
- Contact form submissions: +34%
- Time to first conversion: -23% (faster decision journey)
Prompt 5: Content Refresh Priority Scoring
Score each page in this inventory for refresh priority using this framework:
Scoring Criteria:
- Traffic Potential: High impressions but low clicks = high potential
- Ranking Opportunity: Positions 11-20 easier to improve than 40+
- Business Value: Product/service pages > informational blog posts
- Effort Required: Minor tweaks > complete rewrites
- Content Freshness: Outdated data/stats reduce trust and rankings
For each page, assign:
- Traffic Potential Score (1-10)
- Ranking Opportunity Score (1-10)
- Business Value Score (1-10)
- Effort Required Score (1-10, where 1 = low effort, 10 = high effort)
- Freshness Need Score (1-10)
Calculate Total Priority Score:
(Traffic Potential + Ranking Opportunity + Business Value + Freshness Need) - Effort Required
Output as a ranked table with scores shown. Top 20 highest-scoring pages are your refresh priorities.
Output: A data-driven prioritization that balances opportunity against effort. This prevents wasting time on low-impact updates.
Advanced Prompt: Competitive Content Analysis
For high-value pages, use this competitive analysis prompt:
Analyze this page against its top 3 ranking competitors:
Target URL: [Your page URL]
Target Keyword: [Primary keyword]
Competitor URLs:
1. [Top ranking competitor]
2. [Second ranking competitor]
3. [Third ranking competitor]
Compare across these dimensions:
1. Content Depth:
- Word count comparison
- Number of subtopics covered
- Depth of explanation for each subtopic
2. Content Structure:
- Use of headings and organization
- Scannability (bullets, tables, short paragraphs)
- Visual elements (images, diagrams, videos)
3. User Experience:
- Page load speed
- Mobile usability
- Interactive elements
4. E-E-A-T Signals:
- Author credentials mentioned
- Citations and sources
- Publication date and freshness
- Brand authority indicators
5. Engagement Features:
- Table of contents
- Jump links
- Downloadable resources
- Related content suggestions
Output:
- Gap Analysis: What do competitors have that we're missing?
- Competitive Advantages: What do we do better?
- Specific Recommendations: Top 5 changes to outrank competitors
- Estimated Effort: Hours required to implement recommendations
Focus on actionable differences, not just feature comparisons.
When to use this: For pages that are business-critical, rank positions 6-15, and have substantial search volume. This deep analysis takes more AI processing time but yields highly specific competitive insights.
SEO Content Audit Scoring Matrix
Use this matrix to evaluate and score content during audits:
Technical SEO Scoring (0-100 points)
Scoring Interpretation:
- 90-100: Excellent technical SEO
- 75-89: Good, minor improvements needed
- 60-74: Average, several issues to address
- Under 60: Poor, requires significant work
Content Quality Scoring (0-100 points)
Scoring Interpretation:
- 90-100: High-quality content
- 75-89: Good content, minor enhancements
- 60-74: Acceptable, needs improvement
- Under 60: Low quality, consider rewrite
Combined Priority Score Calculator
// JavaScript function to calculate content priority scores
function calculatePriorityScore(page) {
const scores = {
technical: calculateTechnicalScore(page),
content: calculateContentScore(page),
traffic_potential: calculateTrafficPotential(page),
ranking_opportunity: calculateRankingOpportunity(page),
business_value: page.business_value || 5
};
// Weighted priority calculation
const priority = (
(scores.traffic_potential * 0.3) +
(scores.ranking_opportunity * 0.3) +
(scores.business_value * 0.2) +
((100 - scores.technical) * 0.1) + // Gap score
((100 - scores.content) * 0.1) // Gap score
);
return {
...scores,
priority_score: Math.round(priority),
priority_level: getPriorityLevel(priority)
};
}
function calculateTrafficPotential(page) {
const impressions = page.impressions || 0;
const clicks = page.clicks || 0;
const ctr = impressions > 0 ? (clicks / impressions) * 100 : 0;
// High impressions with low CTR = high potential
if (impressions > 1000 && ctr < 3) return 10;
if (impressions > 500 && ctr < 5) return 8;
if (impressions > 100 && ctr < 10) return 6;
if (impressions > 50) return 4;
return 2;
}
function calculateRankingOpportunity(page) {
const position = page.average_position || 100;
// Positions 11-20 are prime for optimization
if (position >= 11 && position <= 20) return 10;
if (position >= 21 && position <= 30) return 7;
if (position >= 6 && position <= 10) return 5;
if (position >= 1 && position <= 5) return 3;
return 1;
}
function calculateTechnicalScore(page) {
let score = 0;
// Title tag (15 points)
if (page.title_length >= 50 && page.title_length <= 60) score += 10;
if (page.title_includes_keyword) score += 5;
// Meta description (10 points)
if (page.meta_length >= 140 && page.meta_length <= 160) score += 5;
if (page.meta_includes_keyword) score += 5;
// URL (10 points)
if (page.url_is_clean) score += 5;
if (page.url_includes_keyword) score += 5;
// Headings (15 points)
if (page.has_h1) score += 5;
if (page.has_heading_hierarchy) score += 5;
if (page.headings_include_keywords) score += 5;
// Internal links (10 points)
if (page.internal_links >= 3) score += 10;
else if (page.internal_links >= 1) score += 5;
// Images (10 points)
if (page.images_have_alt) score += 5;
if (page.images_optimized) score += 5;
// Schema (10 points)
if (page.has_schema) score += 10;
// Page speed (10 points)
if (page.load_time < 3) score += 10;
else if (page.load_time < 5) score += 5;
// Mobile (10 points)
if (page.mobile_friendly) score += 10;
return score;
}
function calculateContentScore(page) {
let score = 0;
// Depth (25 points)
if (page.word_count > 1500 && page.coverage_score > 8) score += 25;
else if (page.word_count > 800) score += 15;
else if (page.word_count > 300) score += 5;
// Originality (20 points)
if (page.has_original_data) score += 20;
else if (page.has_unique_examples) score += 10;
// Readability (15 points)
if (page.has_formatting && page.has_structure) score += 15;
else if (page.has_some_formatting) score += 8;
// Intent match (20 points)
if (page.intent_match_score >= 9) score += 20;
else if (page.intent_match_score >= 7) score += 10;
// Engagement elements (10 points)
if (page.has_images && page.has_lists) score += 10;
else if (page.has_images || page.has_lists) score += 5;
// Freshness (10 points)
const monthsSinceUpdate = page.months_since_update || 0;
if (monthsSinceUpdate < 6) score += 10;
else if (monthsSinceUpdate < 12) score += 5;
return score;
}
function getPriorityLevel(score) {
if (score >= 8) return 'High';
if (score >= 5) return 'Medium';
return 'Low';
}
// Usage example
const page = {
url: 'https://example.com/blog/seo-guide',
impressions: 2500,
clicks: 45,
average_position: 15,
title_length: 58,
title_includes_keyword: true,
meta_length: 155,
meta_includes_keyword: true,
word_count: 1800,
has_original_data: true,
business_value: 7
};
const result = calculatePriorityScore(page);
console.log(result);
// Output: { technical: 85, content: 90, priority_score: 7.5, priority_level: 'Medium' }
Stage 3: Prioritization and Planning
AI provides recommendations. Your job is turning those into an execution plan.
Building Your Content Refresh Calendar
Month 1: Quick Wins
- Focus on high-priority, low-effort updates
- Target: 10-15 pages
- Types: Meta description fixes, title tag optimization, minor content updates
Month 2: Medium Effort Updates
- Pages requiring 500-1000 words of new content
- Internal linking implementation
- Schema markup additions
- Target: 8-12 pages
Month 3: Major Refreshes
- Complete rewrites or significant expansions
- New sections, updated data, improved structure
- Target: 3-5 pages
Ongoing: New Content
- Fill content gaps identified in audit
- Create supporting cluster content for high-value pillar pages
- Target: 2-4 new pieces per month
Content Refresh Decision Matrix
Use this decision tree to categorize each page:
START: Page requires optimization
├─ Is the ranking position 1-10?
│ ├─ YES → Is CTR below 5%?
│ │ ├─ YES → QUICK WIN: Optimize title/meta (1 hour)
│ │ └─ NO → Is engagement time below avg?
│ │ ├─ YES → MEDIUM: Improve intro/structure (3-5 hours)
│ │ └─ NO → LOW PRIORITY: Monitor quarterly
│ └─ NO → Is the ranking position 11-20?
│ ├─ YES → Is content word count <80% of top 10 avg?
│ │ ├─ YES → MEDIUM: Expand content (4-8 hours)
│ │ └─ NO → QUICK WIN: Technical optimization (2-3 hours)
│ └─ NO → Ranking 21+?
│ ├─ YES → Is business value high (7-10/10)?
│ │ ├─ YES → MAJOR: Complete rewrite (10-15 hours)
│ │ └─ NO → LOW PRIORITY: Consider consolidation
│ └─ NO → Not ranking at all?
│ └─ EVALUATE: Is topic still relevant? Consider removal or 301 redirect
Effort vs. Impact Quadrant Mapping
Plot your pages on this matrix to visualize priorities:
HIGH IMPACT
↑
│ [STRATEGIC PRIORITIES] │ [QUICK WINS]
│ - Major refreshes │ - Meta optimization
│ - Complete rewrites │ - Title tag updates
│ - New pillar content │ - Minor content adds
│ - Rankings 21-30 → pg 1 │ - Schema additions
│ │
│───────────────────────────┼───────────────────────→ LOW EFFORT
│ │
│ [LONG-TERM PROJECTS] │ [DEFER/DELEGATE]
│ - Major new content │ - Marginal improvements
│ - Site structure overhaul │ - Low-traffic pages
│ - Multi-page campaigns │ - Position 40+ pages
│ │
LOW IMPACT HIGH EFFORT
Action plan:
- Week 1-2: Execute all Quick Wins (top-right quadrant)
- Week 3-6: Tackle Strategic Priorities, highest business value first
- Week 7-12: Work through remaining Strategic Priorities
- Ongoing: Defer/Delegate quadrant gets outsourced or skipped
Resource Allocation
In-house team:
- Assign quick wins to junior writers or SEO specialists
- Medium effort to experienced content writers
- Major refreshes to senior strategists
Outsourced:
- Provide AI audit results as detailed briefs
- Set clear quality standards and examples
- Review outsourced work against AI recommendations
AI-assisted execution:
- Use AI to draft updated sections
- Have human editor refine for brand voice and accuracy
- Validate changes with SEO tools before publishing
Team Capacity Planning Tool
Calculate realistic monthly capacity:
// Calculate team capacity for content updates
function calculateMonthlyCapacity(team) {
const hoursPerMonth = {
full_time: 160, // 40 hrs/week * 4 weeks
part_time: 80, // 20 hrs/week * 4 weeks
contractor: 40 // 10 hrs/week * 4 weeks
};
let totalCapacity = 0;
let breakdown = {};
team.forEach(member => {
const hours = hoursPerMonth[member.type] || 0;
const availableHours = hours * (member.content_work_percentage / 100);
totalCapacity += availableHours;
breakdown[member.name] = {
total_hours: hours,
content_hours: availableHours,
quick_wins: Math.floor(availableHours / 1.5),
medium_updates: Math.floor(availableHours / 5),
major_refreshes: Math.floor(availableHours / 12)
};
});
return {
total_hours: totalCapacity,
quick_wins_capacity: Math.floor(totalCapacity / 1.5),
medium_updates_capacity: Math.floor(totalCapacity / 5),
major_refreshes_capacity: Math.floor(totalCapacity / 12),
team_breakdown: breakdown
};
}
// Example usage
const team = [
{ name: 'Sarah', type: 'full_time', content_work_percentage: 60 },
{ name: 'Mike', type: 'part_time', content_work_percentage: 90 },
{ name: 'Contractor', type: 'contractor', content_work_percentage: 100 }
];
const capacity = calculateMonthlyCapacity(team);
console.log(capacity);
/* Output:
{
total_hours: 208,
quick_wins_capacity: 138,
medium_updates_capacity: 41,
major_refreshes_capacity: 17,
team_breakdown: {...}
}
*/
Using capacity data:
- If you have 138 quick wins identified but capacity for 20, prioritize by business value
- Balance quick wins vs. strategic priorities based on team strengths
- Consider outsourcing overflow to maintain momentum
Stage 4: Implementation and Measurement
Executing updates without tracking results wastes effort. Here's how to measure impact.
Pre-Update Baseline
Before changing any page, record:
- Current average position (Google Search Console, 28-day average)
- Organic sessions (GA4, last 28 days)
- Engagement time (GA4)
- Impressions and clicks (GSC)
Tracking tip: Create a simple spreadsheet:
| URL | Update Date | Before Position | Before Sessions | After Position (30d) | After Sessions (30d) | Change % |
Post-Update Monitoring
Wait 30 days after publishing updates, then measure:
- Position changes (GSC)
- Traffic changes (GA4)
- Engagement metric changes
- Conversion rate (if tracked)
What good looks like:
- Average position improvement of 3-5 spots for minor updates
- 20-30% traffic increase for medium updates
- 50-100% traffic increase for major refreshes (if page was significantly outdated)
If results underwhelm:
- Check if Google has re-crawled the page (inspect URL in GSC)
- Verify updates actually went live (view page source)
- Compare to competitors—did they improve their content too?
- Consider whether the issue is content quality or authority/backlinks
Performance Tracking Dashboard
Create a tracking sheet with these columns for comprehensive monitoring:
Pro tip: Use Google Sheets with ImportXML functions to auto-pull some data, or connect GA4/GSC via API for automated updates.
Continuous Improvement Loop
Feed performance data back into AI for ongoing optimization:
These pages were updated based on previous audit recommendations. Here are the before/after metrics:
[Paste performance data table]
Analyze the results:
1. Which types of updates generated the best results?
2. Which pages underperformed expectations? Why might that be?
3. What should we adjust in our optimization approach based on this data?
4. Which pages should be prioritized for additional updates?
Why this matters: AI learns from your specific results, improving recommendations over time. Generic best practices become tailored strategies.
Attribution and Impact Analysis
After 90 days, perform this deep analysis:
Traffic Attribution by Update Type:
Key insights from this data:
- Major refreshes deliver best traffic/hour ROI (67.8 vs. 36.7 for quick wins)
- BUT quick wins provide fastest time-to-value (immediate improvements)
- Medium updates offer best balance of effort vs. sustained impact
- Combined approach maximizes total traffic growth
Optimization strategy adjustment:
- Maintain 40% quick wins for momentum and morale
- Increase major refresh allocation to 30% (from 25%)
- Focus medium updates on pages ranking positions 8-15 where they're most effective
WordPress-Specific AI Audit Tools
Several tools combine crawling, AI analysis, and recommendations specifically for WordPress.
Tool 1: SEO Content AI (WordPress Plugin)
- Scans existing posts
- Suggests keyword optimization
- Generates content expansion recommendations
- Integrates with page editor for in-context suggestions
Tool 2: Surfer SEO + WordPress Integration
- Audits content against top-ranking pages
- Provides content score and improvement checklist
- Tracks changes and impact over time
Tool 3: Frase + WordPress
- AI-powered content briefs for refresh
- Competitor analysis automation
- Question and topic identification
DIY Alternative:
- Export content via plugin
- Use Claude or ChatGPT with prompts from this guide
- Implement changes manually or via bulk editor plugin
Our recommendation: DIY approach with Claude/ChatGPT gives you maximum control and customization. Plugins are convenient but often apply generic recommendations.
WordPress Plugin Comparison Matrix
Hidden costs consideration:
- Plugins: Additional cost for premium features, user seats
- DIY: Time investment in prompt engineering, setup automation
- All approaches: Content writer time for implementing recommendations
Shopify-Specific AI Audit Approaches
Shopify's structure requires different tooling than WordPress.
Product Description Audit:
- Export products via Shopify admin (Products > Export)
- Upload CSV to AI with product audit prompt
- Get recommendations in structured format
- Re-import updated descriptions via CSV
Collection Page Optimization:
- Collections don't export easily
- Manual audit using AI to analyze 5-10 pages at a time
- Focus on top-traffic collections first
Blog Content (Shopify Blog):
- Limited export options
- Use browser automation (like Zapier or Make.com) to scrape blog post content
- Feed to AI for analysis
- Update manually through Shopify admin
App Integration:
- Apps like SEO Manager or Plug in SEO offer basic audits
- Export their recommendations
- Feed to AI for prioritization and expansion
Shopify limitation reality: Platform restrictions make bulk analysis harder than WordPress. Focus on high-value pages (best-selling products, top-traffic collections) rather than comprehensive audits.
Shopify Bulk Update Workflow
Here's a practical workflow for updating multiple products efficiently:
SHOPIFY PRODUCT OPTIMIZATION WORKFLOW
1. EXPORT (Shopify Admin)
└─ Products → Export → All Products → CSV
2. ENHANCE EXPORT (Add performance data)
├─ Open in Google Sheets
├─ Add columns: GA4 Product Views, GSC Position, Conversions
├─ Use VLOOKUP or manual matching to populate
└─ Sort by business priority (high-margin products first)
3. AI ANALYSIS (Batch by 25-50 products)
├─ Upload batch to Claude/ChatGPT
├─ Use product description audit prompt
├─ Review AI recommendations
└─ Flag any hallucinations or brand voice mismatches
4. CONTENT UPDATES (Google Sheets)
├─ Create new column: "Optimized Description"
├─ Paste AI-generated descriptions
├─ Human review for accuracy and voice
└─ Add SEO title and meta description columns
5. RE-IMPORT (Shopify Admin)
├─ Download sheet as CSV
├─ Products → Import → Upload file
├─ Map columns correctly
└─ Verify import success (check 5-10 products manually)
6. TRACK RESULTS (30-day post-update)
└─ Create tracking sheet with before/after metrics
TIMELINE:
- 50 products: 4-6 hours total
- 200 products: 12-16 hours total
- Compare to manual: 40-60 hours for 50 products
Critical Shopify CSV import tips:
- Always backup your store before bulk imports
- Test with 2-3 products first to verify mapping
- Watch for character encoding issues (use UTF-8)
- Shopify may timeout on imports over 500 products (break into batches)
Shopify AI Audit Limitations and Workarounds
Reality check: Shopify audits take 30-50% longer than WordPress due to platform restrictions. Budget accordingly.
Common Pitfalls and How to Avoid Them
Based on dozens of client audits, here's what goes wrong and how to prevent it.
Pitfall Matrix: Problems, Symptoms, and Solutions
Pitfall 1: Analysis paralysis
Problem: AI identifies 200 optimization opportunities. Team gets overwhelmed and does nothing.
Fix: Start with top 10 pages only. Measure results. Build momentum before expanding scope.
Pitfall 2: Ignoring search intent shifts
Problem: AI recommends updates based on outdated SERP data. Current search intent has changed.
Fix: Always manually check current top 10 results for target keywords before implementing AI recommendations. Verify format and content approach still match what's ranking.
Pitfall 3: Updating without tracking
Problem: Team updates 50 pages but has no idea which changes drove results.
Fix: Implement in batches. Track each batch separately. Measure before expanding scope.
Pitfall 4: One-and-done approach
Problem: Complete audit, implement changes, never audit again.
Fix: Schedule quarterly audits. Content and competition don't sit still—neither should your optimization efforts.
Pitfall 5: Trusting AI blindly
Problem: AI hallucinations or misinterpretation of data leads to bad recommendations.
Fix: Always spot-check AI analysis. Review recommendations for logic. Validate high-priority updates manually before implementing.
Red Flags in AI Recommendations
Watch for these warning signs that indicate AI might be off-track:
Content Recommendations:
- Suggests adding 2,000+ words to page already ranking #1 (risk of keyword dilution)
- Recommends stuffing exact-match keywords unnaturally
- Suggests copying competitor structure exactly (creates similar, not better content)
- Proposes outdated SEO tactics (keyword density targets, exact phrase repetition)
Technical Recommendations:
- Conflicting advice (e.g., "shorten meta description" and "add more keywords to meta")
- Suggests changes to elements that don't exist on your CMS
- Recommends schema types inappropriate for your content type
- Proposes title tags over 60 characters or meta descriptions over 160 characters
Prioritization Issues:
- Ranks low-traffic pages as "high priority" without business context
- Suggests optimizing pages with no conversion path
- Prioritizes informational content over commercial intent pages
- Recommends updating pages you plan to remove/consolidate
When in doubt: Get a second opinion from AI with a different prompt, or ask a human expert to review questionable recommendations.
Real Results: What to Expect
Realistic expectations based on actual client implementations:
Timeline-Based Results Benchmarks
Here's what typical improvements look like over time, based on 50+ client audits (2022-2024):
Important notes:
- Results vary significantly by niche, domain authority, and competition level
- These are averages—individual pages may see 200-300% increases while others see minimal change
- Percentages are for updated pages only, not entire site (site-wide impact is diluted)
30 days post-audit:
- 15-20% increase in organic traffic to updated pages
- Minor ranking improvements (2-3 positions on average)
- Improved engagement metrics on refreshed content
60 days post-audit:
- 30-40% traffic increase to updated pages
- 5-10 pages moved from page 2 to page 1 in SERPs
- Measurable impact on conversions from optimized bottom-funnel pages
90 days post-audit:
- 50-70% traffic increase to updated pages
- Multiple pages ranking in top 3 for target keywords
- Content gap fills starting to drive new keyword rankings
Detailed Case Study: B2B SaaS Content Audit
Client case study: B2B SaaS company with 80 WordPress blog posts. AI audit identified 23 priority updates. Implementation over 60 days:
- Overall blog traffic increased 58%
- 9 posts moved from page 2-3 to page 1 in Google
- Lead generation from blog content increased 34%
- Time investment: 25 hours (vs. estimated 80+ hours for manual audit + updates)
ROI was 4:1 in the first quarter alone.
Deep dive into this case study:
Starting situation:
- 80 published blog posts (2019-2022)
- Declining organic traffic (-23% year-over-year)
- Manual content updates when time permitted (reactive, not systematic)
- No formal content strategy or audit process
AI audit findings (2.5 hours of analysis):
- 23 high-priority pages identified
- Breakdown: 8 quick wins, 11 medium updates, 4 major refreshes
- Key issues: 31 pages with poor meta descriptions, 18 pages with thin content vs. competitors, 12 pages with broken or missing internal links
Implementation timeline:
Weeks 1-2: Quick Wins (8 pages, 12 hours)
- Optimized title tags (keyword front-loaded, under 60 chars)
- Rewrote meta descriptions (compelling, benefit-focused)
- Added missing schema markup
- Fixed broken internal links
Results (30 days):
- 8 pages showed +18% traffic increase
- 5 pages improved 2-4 ranking positions
- Immediate CTR improvement: 3.2% → 4.7% average
Weeks 3-6: Medium Updates (11 pages, 55 hours)
- Expanded content with additional 500-800 words per page
- Added FAQ sections addressing "People Also Ask" queries
- Improved internal linking (2-3 contextual links per page)
- Updated outdated statistics and examples
Results (60 days):
- 11 pages showed +41% traffic increase
- 4 pages jumped from page 2 to top 5
- Engagement time increased 34% on updated pages
Weeks 7-10: Major Refreshes (4 pages, 48 hours)
- Complete rewrites with new outlines based on current top-10 analysis
- Added original data and case studies
- Created comprehensive how-to sections with screenshots
- Optimized for featured snippet opportunities
Results (90 days):
- 4 pages showed +127% average traffic increase
- 2 pages captured featured snippets
- These 4 pages generated 23% of all blog leads
Total investment:
- Hours: 115 hours (12 quick wins + 55 medium + 48 major)
- Cost: $8,625 (at $75/hr blended rate for writer + editor)
Return (first 90 days):
- Traffic increase: 18,400 additional monthly sessions
- Lead increase: 47 additional MQLs per month
- Pipeline value: $141,000 (47 leads × 23% SQL rate × 31% close rate × $42k ACV)
- ROI: 16.3:1 in quarter one
Long-term impact (12 months):
- Sustained traffic growth (+73% year-over-year)
- Blog became primary lead source (overtook paid ads)
- Content refresh became quarterly standard operating procedure
- Additional content gaps identified and filled expanded keyword footprint by 340%
Results by Industry Vertical
Different industries see different improvement rates based on competition and content expectations:
Key insight: Industries with lower search competition and longer content (B2B, manufacturing, professional services) see larger improvements from content audits because small enhancements significantly change competitive positioning.
Your Action Plan
Start small, measure results, scale what works.
This week:
- Export content inventory for your top 20 pages (by traffic)
- Gather performance metrics from GA4 and GSC
- Feed data to Claude or ChatGPT with comprehensive audit prompt
- Review AI recommendations for quick wins
This month:
- Implement 5-10 quick-win updates (meta tags, minor content additions)
- Set up tracking to measure impact
- Document your process for repeatability
This quarter:
- Expand audit to your full content inventory
- Build content refresh calendar based on AI prioritization
- Execute medium and major updates systematically
- Measure ROI and refine approach
Ongoing:
- Schedule quarterly audits
- Feed performance data back to AI for continuous improvement
- Build content refresh into your standard workflow
30-Day Quick Start Checklist
Use this day-by-day plan to launch your first AI audit:
Week 1: Data Collection
- Day 1: Export content inventory (WordPress/Shopify)
- Day 2: Pull GA4 traffic data for last 90 days
- Day 3: Export GSC data (impressions, clicks, position)
- Day 4: Run Screaming Frog crawl for technical data
- Day 5: Consolidate all data into master spreadsheet
Week 2: AI Analysis
- Day 8: Feed top 20 pages to AI with audit prompt
- Day 9: Review recommendations, flag any concerns
- Day 10: Score pages using priority framework
- Day 11: Create top 10 priority list
- Day 12: Build content refresh calendar (next 90 days)
Week 3: Quick Wins
- Day 15: Update meta descriptions on 5 high-priority pages
- Day 16: Optimize title tags on same 5 pages
- Day 17: Add missing schema markup
- Day 18: Fix broken internal links
- Day 19: Document baseline metrics for all updated pages
Week 4: Medium Updates Start
- Day 22: Expand content on top 2 priority pages
- Day 23: Add FAQ sections addressing PAA queries
- Day 24: Improve internal linking across updated pages
- Day 25: Update images and alt text
- Day 26: Publish updates and submit to GSC for indexing
Day 30: Review & Plan Next Phase
- Review early signals (click patterns in GSC)
- Schedule 30-day follow-up measurement
- Plan Week 5-8 medium updates
- Document lessons learned
Content audits don't need to be overwhelming. AI makes them practical, actionable, and results-driven.
Need help auditing and optimizing your WordPress or Shopify content at scale?
WE•DO combines AI-powered analysis with hands-on SEO expertise to identify and execute high-impact optimizations. We've audited thousands of pages across client sites—results typically show 40-60% traffic increases within 90 days.
Let's discuss your content challenges.
Related reading:
- The Complete Guide to AI-Accelerated SEO for Shopify & WordPress (Pillar post)
- AI-Generated Schema Markup for WordPress: A Step-by-Step Guide
- Internal Linking Automation: AI Tools That Actually Work
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