Feature Walls
Turning Missed Traffic into Growth
Executive Summary
BUSINESS PROBLEM
Highest-traffic pages, lowest clarity
Users couldn’t understand the product
No team owned the value narrative → conversion gap
CHALLENGES
Fragmented ownership (Growth, MKTG, Eng)
Conflicting goals: persuasion vs. reusability
Outdated content, stale messaging
MY ROLE
Identified unowned space
Secured buy-in from Growth leadership
Led design across teams
Ran prototyping + A/B testing (static, video, interactive)
IMPACT
+22% conversions
+11% cluster upgrades
–11% paid deletions
6 teams adopted pattern → systemization
Business Context
Underleveraged Properties
Feature Walls were MongoDB’s highest-traffic pages — thousands of visits daily — but conversions lagged. Users couldn’t tell what MongoDB actually offered. Content was outdated, the value unclear, and pricing hidden.
I saw a high-leverage opportunity: clarify value, increase trust, and guide activation.
Alignment
Validating the Project
It all started when I stumbled on an unowned gap in an old growth doc and pitched a test to the Director of Growth.
Hypothesis
Defining Success
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Moderated Card Sort Results
Aligning Execution
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Feature Overview
Iterating on Concepts
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
My Role & Team
A Collaborative Process
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Getting Started Guide
Iterating on Concepts
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Demo Playground
A Research Insight
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Before & After
A New Pattern Emerges
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Impact
A/B Test Success
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Reflections
Pricing Calculator
From there the hypothesis was: if we clarify value and pricing early, users will engage deeper and convert more often.
I built conviction showing these inconsistencies and competitor teardowns, and earned a pilot to run an A/B test on the Search product feature wall.
Interactive Component
The narrative
Now let's dive deeper into the context of the problem and why it mattered
Interactive Component
