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The journey from the “Growth Hacking Boom” to the present day has been a relentless cycle of innovation, disruption, and adaptation. Understanding this evolution is essential to mastering the next phase of growth.
2015–2017: The Growth Hacking Boom
This era marked the peak of the original “growth hacker.” The focus was on identifying clever, often one-off, levers for exponential user acquisition. The ethos was virality and product loops—lessons popularized by companies like Dropbox and Airbnb. Success was defined by rapid experimentation and mastering a few key tools like Intercom and Mixpanel.
- Core Focus: Virality, product loops, and email hacks.
- Key Channels: Facebook Pages, organic Instagram, and early-stage mega-influencers.
- Cost of Acquisition: Facebook Ads were the wild west—cheap, broad targeting, and low competition.
- Career Marker: The “T-shaped marketer” who could dabble in everything from code to copy.
2018–2020: Platform Maturity & Paid Scaling
As platforms matured, the game changed. Paid media evolved from a clever hack to a central pillar of growth. Facebook and Google adapted, limiting our ability to manually target audiences and pushing us towards automated tools like CBO (Campaign Budget Optimization) and Smart Campaigns. Competition intensified, driving CAC up. The focus shifted internally as teams realized: Retention is the new acquisition.
- Core Focus: Performance marketing, basic CRM (email/SMS), and retention strategies.
- Key Platforms: Facebook & Google evolving to restrict manual levers.
- Career Marker: The rise of the Specialist—Media Buyers, CRM Heads, and Data Analysts—to optimize sophisticated but isolated channels.
2020–2024: From Performance to Full-Funnel Growth Marketing
This period was defined by the iOS 14 tracking limitations, which delivered a massive blow to the core of performance marketing. Attribution became a dark art, full of gaps and guesswork. To survive, teams were forced to mature their approach:
- Data Resilience: Brands aggressively built 1st-party data stacks (emails, loyalty programs) to regain control.
- The Creative Lever: With targeting and attribution obscured, creatives became the #1 lever in paid performance. Performance marketers could no longer just manage budgets; they had to become experts in creative testing.
- Full-Funnel Ownership: The focus solidified into Growth Marketing—the clear mandate to own the entire funnel and improve stages like Retention and Referral to offset expensive Acquisition.
- Core Focus: Full-funnel mapping, 1st-party data, and creative-led performance.
- Key Challenge: Attribution is messy; performance is a strategic, end-to-end problem.
- Career Marker: The Growth Marketer who must own and be accountable for improving the full customer journey.
2024 Onwards: The AI-Integrated Marketer
This entire journey has been a relentless push toward efficiency, ownership, and adaptability. We’ve mastered the What (channels), the Where (data), and the Why (full-funnel context).
The goal is no longer to be a T-shaped marketer or a full-funnel owner, but to become an AI-Integrated Marketer. This means codifying exactly where human brilliance is required and where machine scale should take over.
This is the very challenge the SEA 3.0 Framework is designed to solve:
| Layer 1: Strategy (Human Advantage) | → Direction |
| Layer 2: Execution (Human × AI) | → Leverage |
| Layer 3: Automation (AI Advantage) | → Scale |
We are moving from a world of fragmented hacks and isolated funnels to a unified system where human intuition directs, and AI executes and scales.
The confluence of data proliferation and advanced artificial intelligence (AI) has initiated a paradigm shift in business strategy.
In 2017, I introduced the A3R3 Funnel to evolve the Pirate Metrics for the modern startup. Today, it’s about the seismic shift caused by Artificial Intelligence.
The old models that treated strategy and execution as separate, sequential steps are obsolete. The future of growth belongs to the businesses that master the Human × AI collaboration across every layer.
I’m proud to introduce the SEA 3.0 Framework, a three-layered, stacked model for modern growth marketing that ensures clarity at the top, leverage in the middle, and efficiency at the base.
The SEA 3.0 Framework: An Overview
The core insight of SEA 3.0 is that AI does not replace the marketer; it amplifies them. Our framework defines the roles of the Human and the Machine at three distinct layers:
| Layer | Focus | Advantage | Core Function |
| 1. Strategy (S) | Direction & Clarity | Human Advantage (Empathy, Unique Insight, Ethics) | Defines the What and the Why |
| 2. Execution (E) | Speed & Precision | Human × AI Collaboration | Defines the How and the How Fast |
| 3. Automation (A) | Scale & Efficiency | AI Advantage (Volume, Consistency, Cost) | Defines the Scale and the Continuous Learning |
| Stacking Principle | Clarity at the Top → Leverage in the Middle → Automation at the Base |
Layer 1: Strategy (S) — The Human-Led Advantage
Focus: Direction, Clarity, and Leverage
The Strategy Layer is the exclusive domain of human intelligence. AI excels at optimization, but it can only optimize towards a goal that a human has set. This layer requires empathy, critical thinking, and ethical judgment.
1. Funnel Planning & Audience Insight
- Define Your North Star: The human team must establish the North Star Metric (NSM) and the One Metric That Matters (OMTM) for each stage of your buyer journey (Awareness → Acquisition → Activation → Revenue → Retention → Referral).
- Buyer Journey Alignment: We must move beyond the “one-size-fits-all” funnel. Human insight identifies pathways for multiple segments by understanding unique pain points, a critical task often missed by raw, pattern-matching AI.
2. Growth Loops Design
- The Input → Output → Loop Mechanism: While AI can run thousands of A/B tests, only a human can design a novel, defensible growth loop (e.g., Acquisition → Engagement → Acquisition).
- Forecasting Failure Points: Human experience documents the key failure points and assumptions for each loop, preventing the AI from simply amplifying a flawed system.
3. Experiment Design & Governance
- Hypothesis Bank & ICE Scoring: Maintain a human-curated hypothesis bank, prioritizing based on the classic ICE (Impact–Confidence–Ease) framework.
- Ethical Thresholds: Define success/failure thresholds and ethical guardrails before testing. This prevents the AI from engaging in practices that might erode brand trust for a fractional conversion lift.
Layer 2: Execution (E) — The Human × AI Collaboration
Focus: Speed, Creativity, and Precision
This is the sweet spot of the framework. AI becomes your hyper-efficient co-pilot, handling the high-volume, repetitive, or complex data tasks, while the human adds nuance, brand voice, and final quality control. This symbiotic relationship is where measurable revenue growth is accelerated.
1. Campaign Setup & Scaling
- Channel Selection Matrix: The human decides the channel selection matrix (Paid vs. Organic vs. Owned). The AI then takes over for speed and scale:
- AI for Efficiency: Use AI for rapid keyword clustering, dynamic ad copy variations, and budget pacing optimization in real-time.
- Human Control: The human ensures all tracking links (UTM, pixels) and compliance standards are flawless before the AI takes control.
2. Creative & Copy Production
- AI Drafts, Human Refinement: This is the crucial “Human in the Loop” model. AI drafts thousands of ad creatives, landing page sections, or email subject lines. The human team refines these drafts for nuance, brand voice, and emotional resonance—the elements that drive deep connection.
- Systematic A/B Testing: The team maintains a swipe file & test vault of high-performing assets. AI assists in running sophisticated A/B/n tests on headlines, calls-to-action (CTAs), and formats, freeing up human time for ideation, not just setup.
3. Analytics & Attribution
- Real-Time Dashboards: Leverage tools (GA4, Looker) for real-time data visualization.
- Attribution Clarity: The human defines the attribution model (Last-Click vs. Multi-Touch vs. Media Mix Modeling). The AI’s role is to power anomaly detection and predictive alerts, notifying the human team when performance deviates significantly from the expected curve, allowing for agile, human-led intervention.
Layer 3: Automation (A) — The AI-Led Efficiency
Focus: Scale, Consistency, and Cost Efficiency
The Automation Layer is where repetitive, high-volume tasks are handed over completely to the machine. This is AI’s greatest strength: scaling impact without scaling cost. The goal here is efficiency.
1. Reporting & Contextual Insight
- Automated Dashboards + Context: Automation moves beyond just showing metrics. AI is leveraged to create automated dashboards with contextual insights, not just reporting variance, but explaining the likely cause (e.g., “CPC spiked by 15% due to competitor budget increase on keywords X, Y, Z”).
- Executive Summaries: Daily, concise executive summaries are auto-generated, saving senior leaders hours of dashboard diving.
2. Testing Loops & Continuous Learning
- Auto-Generation & Rotation: AI manages the auto-generation of test variants for ads, landing pages, and email sequences. It handles the automated rotation and winner selection based on pre-set human KPIs.
- Feed-Forward System: Results from the testing loops are fed back into the AI’s training data, creating a Continuous Learning cycle that refines the quality of future AI-generated copy and creative assets.
3. Content Systemization
- Content Calendar Automation: The high-level editorial calendar is auto-generated from funnel/loop priorities.
- Repurposing at Scale: AI-assisted repurposing (long-form blog → short-form social posts, video snippets, email newsletters) is managed centrally, ensuring consistency, speed, and massive content scale across all channels.
Conclusion: The SEA Change for Growth
The SEA 3.0 Framework is the indispensable new playbook for the Human × AI era. It is not just about using AI tools; it is a philosophical shift that mandates humans focus on the 10× leverage points of Strategy, while delegating the 1× routine tasks to Automation.
In 2017, the A3R3 Funnel was an update to the user journey. The SEA 3.0 Framework is an update to how growth teams operate. By stacking these layers, you stop chasing efficiency and start mastering profitable, scalable, and human-centric growth.
The future of business will not be defined by which companies possess the most advanced AI but by which companies achieve the most harmonious and intelligent integration of human and artificial intelligence.
I wanted to introduce the SEA framework in this post as I’ve been thinking over this and documenting it over the past few months.
In the near future, I will publish updates on how I’m using this framework to stay ahead of the curve in the evolving landscape of marketing with AI.