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█▓▒░ Growth project ░▒▓█

I build this little vercel project to test a few things.

Project:
https://gmd-assessment.vercel.app/

Github:
https://github.com/micheleborn/gmd-assessment

The Context

This project was built as part of a Growth Marketing Designer assessment — a role that requires end-to-end ownership of landing pages, from design to deployment, with performance measured by conversion rate .

But the brief came with a twist:

No clear audience
No defined product positioning
No brand guidelines
No funnel stage

So instead of “executing,” I had to define the strategy from scratch.

The Goal

Design and build three landing page variants:

/control
/variant-1
/variant-2

Each with:

A different conversion hypothesis
A consistent structure for testing
Measurable behavioral tracking

Step 1 — Defining the Strategy (Before Design)

Instead of jumping into UI, I started with who this is for.

Target audience (assumed)

Mid-size DTC brands ($3M–$30M)
Paid acquisition fatigue (Meta, CPMs rising)
Distrust in attribution
Pressure from finance teams

Core emotional state

“I don’t trust my growth anymore.”

That became the foundation of everything.

Step 2 — Hypothesis Design

Each variant explores a different persuasion model:

1. Control — USP Clarity

Straightforward messaging
“What it does” framing
Minimal psychological layering

2. Variant 1 — Authority + Social Proof

Borrowed credibility
Proof-driven messaging
Reduces skepticism

3. Variant 2 — Risk Mitigation (Most interesting)

Focus on predictability + control
Addresses emotional anxiety directly
Designed for decision-makers under pressure

This is not UI variation.
This is psychological positioning testing.

Step 3 — UX & UI Decisions

UX Principles

Single goal: conversion
No distractions, no navigation complexity
Repeated CTA for scanning behavior
Clear hierarchy (problem → solution → action)

UI Decisions

Clean, high-contrast typography
Modular components reused across variants
Visual consistency to isolate messaging impact

Important:
I intentionally avoided “fancy design”
Because design should not contaminate the experiment

Step 4 — Development (Next.js + Vercel)

Built with:

Next.js + TypeScript
Component-based architecture
Route-based variant system

Routing strategy

/control
/variant-1
/variant-2

Each route:

Injects different content
Reuses the same components

This ensures:

Fast iteration
Clean experiment structure
Scalability for future tests

Deployment

Deployed via Vercel
Instant previews + production parity
CI/CD built-in

Step 5 — Analytics (PostHog)

Implemented full tracking:

Events

variant_viewed
signed_up
CTA clicks (with placement tracking)

Data captured

Variant name
CTA location (hero, footer, etc.)
Referral codes

Every interaction is measurable.

Also:

Ensured event capture before redirect
Structured for funnel analysis

Step 6 — Experiment Design

This is the part most people skip.

What I controlled:

Same layout across all variants
Same CTA wording
Same visual design

What I changed:

Messaging strategy only

That’s how you isolate causality

What AI Changed

This project took ~3 days.

Without AI, it would realistically take ~2 weeks.

AI helped with:

Validating messaging directions
Exploring persuasion angles
Speeding up iteration

But:
The strategy decisions were still human

Key Takeaways

Conversion is psychology first, design second
Most landing pages fail because they skip strategy
A/B testing is useless without clear hypotheses
Speed matters — but only if direction is correct

Final Thought

This wasn’t a design exercise.

It was:
Strategy
Psychology
Engineering
Measurement

All in one system.

I actually love the way this turned out – super happy with the results.