- Updated all plugins/themes
- Changed all passwords
- Installed security plugin (Wordfence)
- Set up monitoring
Site back online: 72 hours after discovery.
3/ Week 1: Google communication:
Clearing blacklist:
Day 4: Request malware review
- Submitted reconsideration in GSC
- Documented all cleanup actions
- Listed security measures implemented
Day 5-7: Monitor status
- Google reviewed within 48 hours
- Malware warning removed
- Safe Browsing cleared
But rankings still down 73%. Traffic still at 15K.
Real recovery work begins now.
4/ Week 2-3: Spam URL cleanup:
Deindexing bad pages:
Challenge: 12,000 spam URLs still in Google index
Solution sequence:
- Created list of all spam URLs
- Returned 410 Gone status (not 404)
- Submitted removal requests in GSC (bulk)
- Created updated sitemap (clean URLs only)
- Disavowed spam domains linking to spam pages
Progress: 8,400 spam pages removed from index by week 3.
5/ Week 4-5: Content restoration:
Fixing legitimate pages:
Issues found:
- 80 legitimate pages affected by hack
- Spam text injected into footers
- Hidden links added to content
- Meta descriptions corrupted
Cleanup process:
- Manually reviewed all 80 pages
- Removed injected spam
- Restored original content
- Verified clean code
Quality check: Each page manually inspected.
6/ Week 6-7: Link profile analysis:
Addressing damage:
New toxic backlinks from hack:
- 240 spam links acquired during hack period
- Links to spam pages created
- Links from malware networks
Actions:
- Exported all backlinks
- Identified hack-related links (240)
- Created disavow file
- Submitted to GSC
Protecting authority from spam link association.
7/ Week 8-9: Content enhancement:
Rebuilding trust signals:
Enhanced top 30 pages:
- Added 300-500 words per page
- Updated statistics and examples
- Improved formatting
- Added FAQ sections with schema
- Strengthened E-E-A-T signals
Showing Google: Site is active, maintained, legitimate.
Real estate agent went from page 5 to owning page 1 in 11 months.
Competitive market with 200+ agents fighting for same keywords.
The secret? Hyperlocal SEO done the right way.
Here's the hyperlocal SEO strategy that worked: 🧵👇
1/ The competitive challenge:
Starting position:
Market: Major metro area (population 2M+)
Competition: 200+ active real estate agents
Established players: 20+ with DR 50-70
Our agent: New site, DR 12, zero rankings
Target keywords highly competitive:
- "Real estate agent [City]" (8,100 searches/month)
- "Homes for sale [City]" (12,400 searches/month)
- "[Neighborhood] real estate" (30+ neighborhoods)
David vs Goliath times 200.
2/ The hyperlocal strategy:
Go narrow and deep:
Instead of competing citywide immediately:
- Target 8 specific neighborhoods first
- Create comprehensive neighborhood content
- Build neighborhood-level authority
- Expand outward after dominance
Neighborhood selection criteria:
- Active home sales (inventory turnover)
- Agent knows area intimately (expertise)
- Search volume exists (demand validation)
- Lower competition (achievable wins)
We built 180 quality links in 18 months using a simple CRM system.
No scattered spreadsheets. No lost opportunities.
Skipped juggling emails and forgetting prospects.
Here's the link building CRM that actually scales:
1/ Why you need a link CRM:
The tracking problem:
Without system:
- Lost follow-ups (forget to reply)
- Duplicate outreach (email same person twice)
- No relationship history (what did we discuss?)
- Can't measure what works (which tactics convert?)
With CRM:
- Automated follow-up reminders
- Full contact history
- Performance tracking by tactic
- Relationship progression visible
We tested both. CRM increased link acquisition by 140%.
2/ The CRM structure:
Core components:
Contacts database:
- Name, email, website
- Domain authority
- Relationship status (cold/warm/partner)
- Last contact date
- Notes on interactions
Opportunities pipeline:
- Prospect → Pitched → In Discussion → Secured → Published
- Each stage has automated tasks
- Conversion rates tracked per stage
Campaign tracking:
- Group prospects by campaign type
- Track performance by tactic
- A/B test subject lines and approaches
- Marketing (main category)
→ Email Marketing (subcategory)
→ Content Marketing (subcategory)
→ Social Media (subcategory)
Issues with this approach:
- Topics overlap (email content strategy fits where?)
- Rigid hierarchy (can't show natural relationships)
- Manual decisions (subjective categorization)
- Missing connections (related topics in different silos)
Example: "Email automation workflows" could fit in email OR marketing automation OR content strategy.
Forced choice limits topical relevance signals.
2/ How AI clustering works:
Semantic relationship mapping:
AI analysis process:
- Analyzes all content on site
- Identifies semantic relationships
- Groups by topic similarity (not manual categories)
- Creates natural content clusters
Example output:
Cluster 1: Email deliverability ecosystem