Skeema Chrome Extension

Skeema Chrome Extension

Skeema Chrome Extension

AI Tab Sorting Feature

Fall 2025

Fall 2025

Fall 2025

Role: UX Researcher & Designer

Role: UX Researcher & Designer

Role: UX Researcher & Designer

Data-Driven UX & AI-Centered Design

Tools: Figma, Tableau

Data-Driven UX & AI-Centered Design

Overview

Skeema is a Chrome extension that helps users organize their Google Chrome tabs into named project groups. I was given access to Skeema's actual user activity data and survey responses, and tasked with analyzing that data to identify UX problems and propose design improvements.

Challenge

Data Analysis

Data-Driven Hypothesis

Redesigned UX

Reflection

Challenge

Data Analysis

Data-Driven Hypothesis

Redesigned UX

Reflection

Challenge

Skeema's core value proposition is tab grouping, yet the data told a different story about how users actually behaved.


The core question: If users say they love the grouping feature, why aren't they using it?

Data Analysis: Surfacing the Contradiction

Findings from analyzing survey responses and user activity data, creating visualizations in Tableau to look for patterns.

Grouping was clearly the most-loved feature


79.7%

of survey respondents said their favorite Skeema feature was "being able to sort all my tabs into projects"

Yet only

1.25%

of total tabs opened came from project groups

Even active users weren't using the feature they claimed to love


0 tabs

were the median number of tabs opened from project groups, when I narrowed the analysis to active users (last activity in the latest week of dataset).

Even power users weren't using the feature they claimed to love


0 median

When I narrowed the analysis to the most active users (last activity within one week), the median number of tabs opened from groups was still

Even active users weren't using the feature they claimed to love


0 median tabs

were opened from project groups, when I narrowed the analysis to active users (last activity in the latest week of dataset).

Why this matters

Users valued grouping conceptually but weren't executing it in practice. The feature wasn't broken, the workflow to get there was too effortful.

Data-Driven Hypothesis

Users, even those who are decently active on the extension, do not effectively use the grouping feature on Skeema. We could increase the use of groups by making it efficient for users to check on the progress of their projects.

HYPOTHESIS: If Skeema offers algorithmic suggestions that group similar tabs together, either by suggesting tabs to add to projects or suggesting which project a tab belongs to, then users will create and use projects more, because the cognitive load of the grouping process will be reduced.

Redesigned UX: A Comprehensive System for Community Polling

Tabs Section

"Suggested Tabs"

Original

When viewing a project, the Tabs section showed the most recently opened tabs, requiring users to scroll through a long list of unrelated tabs to find ones relevant to their project.

Redesign

Added a "Suggested" tab as the default view, surfacing tabs algorithmically matched to the current project based on tab titles, content, and item descriptions. Users can still access all tabs via the "Tabs" tab. This eliminates the scroll burden and presents the most relevant matches first.

Chrome Extension Pop-Out

Chrome Extension Pop-Out

"Suggested Project"

Original

When moving a tab to a project, the pop-out displayed all projects in the order they were created with no prioritization or guidance.

If the user has many projects and sub-projects, searching for the best one for the tab would be difficult.

Redesign

Added a "Suggested Project" section at the top of the list, highlighting the project the current tab most likely belongs to (based on tab name, content, and existing items in that project). Users can still see all projects below, but the top suggestion reduces decision effort.

Defining a Metric Framework

Defining a Metric Framework

Defined success metrics across three dimensions to measure whether the redesign achieved its goals

Reflection

When I presented my project to Skeema's founder, he validated my findings, confirming that my redesign suggestions aligned closely with Skeema's own planned future direction, which confirmed that the data analysis was sound.


I learned that data can tell you where users are dropping off, but it takes interpretive thinking to understand why. The real skill was connecting a statistical anomaly (1.25% group usage despite 79.7% feature love) into a coherent behavioral hypothesis and then a concrete design intervention.


If I were to continue building this project, I would run usability testing specifically around the Suggested tab interaction and track the retention metrics above after a feature release to measure actual behavior change.