InsideSchools

Data-Driven Filter System Redesign

Redesigning Filters to Match User Mental Models
ROLE:
UX Consultant, Data Analyst
TOOLS:
Figma, MS Excel
TEAM:
2 Editors, 1 Developer

Overview

InsideSchools helps families navigate the NYC public schools system. While analyzing data from migrant family workshops, I uncovered a critical insight that the website users were struggling to find existing information on the Educational Guides & Reports page, a vital resource for information.

It was experiencing high abandonment rates due to poor filtering capabilities. To address this, I proposed a new filter categorization system and provided crucial usability inputs that shaped the final implementation alongside our editors and developer.

ROLE:
UX Consultant, Data Analyst
TOOLS:
Figma, MS Excel
TEAM:
2 Editors, 1 Developer

Overview

InsideSchools helps families navigate the NYC public schools system. While analyzing data from migrant family workshops, I uncovered a critical insight that the website users were struggling to find existing information on the Educational Guides & Reports page, a vital resource for information.

It was experiencing high abandonment rates due to poor filtering capabilities. To address this, I proposed a new filter categorization system and provided crucial usability inputs that shaped the final implementation alongside our editors and developer.

Filter by  Grade 
Filter by  Topic
Combine  Search, Grade, & Topic filters  

How I went about it

Data Analysis & problem identification

I led the analysis of workshop feedback from 400+ stakeholders, processing over 6,000 data points to uncover critical user needs. From the data, I identified that questions from families naturally clustered around common terms (e.g., "transport", "language") but they could not search the resources on the webpage using those terms.

The resources web page only allowed users to filter content by grade levels
Common terms used in questions from families in workshops

enhancing filter system

I proposed implementing a tag-based filtering system that aligns with users' natural thought patterns. To validate this approach, I mapped existing resources against the terms from the data and shared it with the editorial team and developer to facilitate team alignment.

A High-Level Flow for a Tag-Based Filtering System

final design Usability Inputs

After the team finalized the taxonomy of the tags and a development stage UI of the page, I identified key opportunities to enhance usability before the final implementation.

Before
After
Restructuring the visual hierarchy to make search bar more prominent and place the filters at the same level
Before
After
Adding clear indicators of how many resources matched each filter combination
and improving system feedback when filters are applied
Before
After
Redirecting users to reach out in case of no matches
Development Stage UI
Redesigned UI

Takeaway

What began as workshop data analysis revealed a broader usability issue, reinforcing the importance of staying open to unexpected insights. This experience has transformed how I approach user research:

  1. I now dedicate time to analyzing secondary patterns in user data, not just the primary metrics
  1. I've incorporated "insight mining" sessions into my research process, where I specifically look for unexpected connections