CASE STUDEIS #2

Amar Ujala – Redesigning the My City Selection Experience

Amar Ujala Hero Banner — Redesigning the My City Selection Experience

Transforming a Shallow Filter into a Structured Preference System

While working at Amar Ujala, I was exploring the app as part of a broader product audit when I noticed friction in a critical flow:

Selecting your preferred city to read news

At first glance, it worked. But from a product thinking perspective, it was shallow.

The Problem I Identified

There was a CTA on the top header: “शहर चुनें” (Choose City). When users tapped it, they landed on:

Users tapped it, they landed on:

Long static city list without categories
No clear state hierarchy or grouping
Similar city names mixed together causing confusion
No way to select or follow multiple preferred cities
No explicit save confirmation feedback

From data:

~68% tapped directly on city name expecting filtering
Redirected immediately instead of saving preference
Users were unsure if their selection was stored
Many assumed it saved but got reset on next launch
Tier 2/3 users expected a simple “tap once” model

“So yes — the intent was clear. If someone wanted Noida news, they clicked Noida.”

But here's the deeper issue:

The feature was supposed to act as a preference filter system, yet it was behaving like a navigation shortcut but there was no structured way to:

Select multiple citiesUnderstand state hierarchyManage preferencesPreview selectionsFeel in control

Stakeholder Collaboration

I discussed this observation with Zahid Qurashi (Sr. Product Manager at Amar Ujala).

Instead of jumping into UI changes, we went deeper into metrics:

Click behavior across city drop-down CTA
Drop-off analysis on location selection pages
Session patterns after city redirection
Heatmaps on state navigation lists
Navigation loops between home and local feeds

Research Phase

We expanded research in three directions:

1. Competitor benchmarking

2. Persona mapping

3. Journey mapping + heatmaps

Surprisingly, direct competitors weren't solving this elegantly either.

That was encouraging.

But we didn't want to redesign based on ego.

So we broadened the scope to study:

Filtering systems in e-commerce apps
Category selection flows in content platforms
Preference selection patterns in news & media apps

We weren't redesigning a city list. We were redesigning a selection system.

The Strategic Shift

We reframed the journey:

FROMExploring cities

→

TOSelecting & managing preferences

The New Solution (Second UI Iteration)

Amar Ujala New Solution — Second UI Iteration Architecture

Clear State → City Segeration

Left Panel: State / Right Panel: Cities Under selected State

Visual Hierarchy

Selection Based Model

Checkboxes instead of direct redirect. Multi-select Enabled

Clear Selection Indicators

Confirmation Layer

“Save” CTA / Preview of selected cities

Strong Communaction of action

Validation – UAT & A/B Testing

We conducted: UAT with 100+ participants

Mix of existing AU users and non-users
Different reader personas & age groups

Initial reactions:

Existing users: “Feels different and modern.”
New users: “Much clearer.”

Results showed:

Stronger clarity in preference selection
Higher interaction depth on city feeds
Better structured engagement across regional categories

However, post-launch clarity recordings revealed something important: 20–30% of existing users initially found it slightly confusing. But after first interaction, adaptation was smooth. New users navigated it naturally. This was a critical learning moment.