Justin Tagieff SEO
CASE STUDIES

RESULTS WITH
REAL COMPANIES.

This is the part the generic agencies usually cannot show. Real projects, real operating problems, and outcomes that tie back to traffic, demos, revenue, or process efficiency.

SEO CASE STUDIES

ENTERPRISE SEO, PROGRAMMATIC SEO, AND LOCAL GROWTH

These projects cover technical SEO, internal linking, content architecture, programmatic SEO, and scaled execution across enterprise and local businesses.

SEO CASE STUDY

UBER FREIGHT

We proved SEO drives enterprise value at Directive (2023-2024). That was entirely manual execution. Since then, I've built AI infrastructure that delivers the same strategic precision at 10x velocity. Our previous work took 12 months—with AI, I'd compress technical fixes to 4-6 weeks and scale content production indefinitely. You're not just getting proven SEO strategy—you're getting it supercharged by 2 years of AI development.

+1,100% IMPRESSIONS / +350% CLICKS
Enterprise SEO • Content Strategy • Technical Audit • AI-Powered Execution
Before
  • Low non-brand visibility
  • Manual content ops
  • Pre-optimization state
After
  • 98.9M Total Impressions
  • 21,255 Non-Brand Clicks
  • 98,426 Blog Clicks
  • Now deliverable at 10x velocity with AI
+1.1K%
Impressions
+350%
URL Clicks
10x
Velocity Multiplier
SEO CASE STUDY

CATO NETWORKS

Strategic internal linking from TOFU pages to drive core product commercial conversions. We turned readers into leads through architectural improvements.

+123% DEMO REQUESTS
Internal Linking • TOFU Strategy • Conversion Opt
Before
  • Siloed content structure
  • Low commercial page rank
  • Traffic not converting
After
  • 123% Increase in Demos
  • 222% More Non-Brand Clicks
  • Dominant Commercial Rank
+123%
Demos
+222%
Non-Brand
SEO CASE STUDY

SERVICE CHANNEL

Programmatic SEO campaign targeting maintenance templates. We dominated the "template" SERPs to capture high-intent users at scale.

+1,794% NON-BRAND
Programmatic SEO • Template Engine • Scale
Before
  • 98% Brand Traffic Dependency
  • Manual page creation
  • Low non-brand discovery
After
  • 1,794% Non-Brand Growth
  • 293% Increase in Sessions
  • 125% Increase in Demos
+1,794%
Non-Brand
+293%
Sessions
SEO CASE STUDY

INERTIA PHYSIO

Complete content automation overhaul. Moved from 2 manual posts/month to mass-scale optimized production using n8n workflows.

+3,000% TRAFFIC
Content Automation • Local SEO • Analytics
Before
  • 2 posts/month
  • No organic revenue
  • Local-only visibility
After
  • 500+ Automated Pages
  • $72k SEO Revenue
  • National Reach
3,000%
Growth
403%
ROI
SEO CASE STUDY

BROOKLYN FI

Built a full equity compensation content strategy for a fee-only financial advisory firm. 27 blog posts targeting low-KD keywords generated 35,597 clicks and 2M+ impressions, compounding from 393 to 2,840 monthly visits at peak.

+623% ORGANIC TRAFFIC
Content Strategy • Topical Maps • Low-KD Targeting • Hub & Spoke
Before
  • 393 monthly organic visits
  • No equity comp content authority
  • Zero non-branded keyword rankings
  • Reliant on referrals only
After
  • 2,840 Monthly Visits at Peak
  • 35,597 Organic Clicks
  • 2M+ Impressions
  • Top 3 Rankings on 107 Keywords
35.5K
Organic Clicks
+623%
Peak Growth
AI SYSTEMS

AUTOMATION, AGENTS, AND OPERATIONAL LEVERAGE

Some of these systems were internal or confidential, so the naming is more abstract. The workflows and outcomes are real.

AI SYSTEM CASE STUDY

STRATOS

Built an internal AI agent platform that automated reporting, data entry, and analysis across 50+ enterprise accounts.

$90K/MO SAVED
n8n • OpenAI • BigQuery • Python
Before
  • 200+ hours/mo wasted on reporting
  • Manual data copying
  • Reactive insights
After
  • 15 Autonomous Agents
  • $1.08M Annual Savings
  • Real-time Dashboards
$90K
Monthly Savings
15
Agents
AI SYSTEM CASE STUDY

TAM VERIFICATION

Automated the verification of Total Addressable Market data, reducing cost per record from $11 (manual analyst) to $0.01.

99.9% CHEAPER
Python • SerpApi • Automation
Before
  • $11/hr Manual Research
  • 100 records/day cap
  • Human Error
After
  • $0.01/hr Automated
  • 50,000 records/day
  • 99.9% Accuracy
99.9%
Cost Reduction
500x
Volume
AI SYSTEM CASE STUDY

CONTENT SYSTEM

End-to-end automation of the content brief process. AI handles topic research, keyword clustering, and competitor gap analysis.

10X VELOCITY
OpenAI API • Ahrefs API • Google Docs API
Before
  • 2-3 hours per content brief
  • Inconsistent research depth
  • Manual keyword mapping
After
  • 20 mins per brief
  • Standardized quality
  • Instant competitor data
83%
Time Savings
Unlimited
Briefs/Mo
AI SYSTEM CASE STUDY

STRATOS SCORE

A custom scoring engine that ingests unstructured data from Gong calls and Slack channels to predict client health and churn risk.

CHURN PREDICTION
NLP • Gong API • Slack API
Before
  • Lagging churn indicators
  • Subjective account health
  • Surprise cancellations
After
  • Real-time Sentiment Analysis
  • Proactive risk alerts
  • Data-driven retention
Unstructured
Data Source
Real-time
Insight
AI SYSTEM CASE STUDY

CONSTELLATION

Automated the audience creation process for a B2B SaaS sales org. Turned 20+ hours of manual analyst research per audience into a self-serve tool that builds segmented lists in minutes.

40 HRS/MO SAVED
Anthropic API • Python • Snowflake • Automation
Before
  • ~20 hours per audience build
  • Analyst bottleneck on every campaign
  • Manual research and list assembly
  • Capped at 2 audiences/month
After
  • Minutes Per Audience Build
  • 40 Hours/Month Recovered
  • Self-Serve for Campaign Teams
  • No Analyst Bottleneck
40 hrs
Monthly Savings
Minutes
Build Time
AI SYSTEM CASE STUDY

COACHING ENGINE

Multi-agent pipeline that scores sales calls and emails against qualification frameworks, generates role-specific coaching recommendations, and surfaces deal patterns across the entire org. Replaced manual call reviews at scale.

600+ HRS/MO SAVED
Anthropic API • Gong API • Snowflake • Python
Before
  • Managers reviewing calls manually
  • Inconsistent scoring criteria
  • No email signal analysis
  • Coaching limited to a few reps/week
After
  • 7-Agent Scoring Pipeline
  • Role-Based Analysis (XDR + AE)
  • Gong + Email Coverage
  • 600+ Hours/Month Recovered
600+ hrs
Monthly Savings
$0.05
Cost Per Call
AI SYSTEM CASE STUDY

ORACLE

Multi-agent system that translates natural language into validated Snowflake queries for financial reporting. Three specialist agents route by question type, while deterministic validators enforce audit filtering, block dangerous SQL, and guarantee transparent assumptions on every response.

100% AUDIT COMPLIANCE
Anthropic API • Snowflake • Python • MCP
Before
  • 10-15 min per manual SQL query
  • Audit filters frequently forgotten
  • Fiscal calendar confusion across team
  • Business logic siloed in dbt macros
After
  • 30-Second Natural Language Queries
  • 3-Layer Deterministic Validation
  • 100% Audit Filter Enforcement
  • Full SQL Transparency on Every Response
4
Specialist Agents
3
Validation Layers

WANT TO TALK THROUGH A SIMILAR PROBLEM?

If you are trying to improve search performance, automate repetitive work, or build a system that needs to survive real operating conditions, I can help.

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Ottawa, Canada