Children's Clothing App

Kid Size Mobile App: Helping Parents with Growth Prediction & Smart Shopping

My Role:

I was responsible for the end-to-end design process including user research, persona development, information architecture, wireframing, prototyping, and usability testing.

Outcome:

An app that helps parents make confident clothing purchase decisions through personalized size recommendations and smart shopping features.

Research:
Understanding Parents' Needs

To develop an effective solution, I conducted research to understand the problem space:

5 interviews with parents of children ages 2-7
Competitive analysis of 7 direct and indirect competitors
Secondary research on children's growth patterns and parental shopping behaviors

The Challenge:
Ever Bought Clothes That Were Never Worn?

Imagine this scenario:

A parent spends time carefully selecting a seasonal wardrobe for their child online, only to discover weeks later that a sudden growth spurt has rendered these new clothes unwearable. This common occurrence leads to wasted money, unnecessary environmental impact, and frustration for busy parents already juggling multiple responsibilities.

This was the central challenge I aimed to solve: How might we help parents navigate the unpredictability of children's growth when purchasing clothing?

Key Research Insights

My research revealed four critical user pain points:

Growth Unpredictability & Cost Management

Sudden growth spurts disrupt planning and purchasing cycles
Frequent size changes strain family budgets
"I want to reduce any mistakes when ordering" —Interviewed Parent

Time & Convenience Constraints

Busy schedules severely limit available shopping time
Need for immediate solutions when clothes suddenly don't fit
"If my child doesn’t have the appropriate clothes, I will have to go get them." —Interviewed Parent

Trust & Quality Verification

Uncertainty about fit when shopping online
Concerns about durability for frequently replaced items
"If it’s not to my liking, I won’t buy it." —Interviewed Parent

Control vs. Automation Balance

Parents want flexibility in purchase timing
Subscription boxes often don't align with real needs
"I must stay on top of chilid’s development and remain flexible and adaptable." —Interviewed Parent

When Research Challenges Implicit Bias

When I began this project, I assumed parents would prioritize eco-friendly options and embrace subscription models. The research painted a different picture.

What parents actually needed was much more practical: tools to predict growth patterns, efficient shopping experiences that respected their limited time, and features that helped them manage their budgets effectively.

This insight shifted the product’s direction from sustainability-focused to growth prediction and smart shopping tools.

Competitive Analysis: Identifying the Opportunity

My analysis of the competitive landscape revealed a significant gap:

Key Finding: Most competitors collected child data during onboarding (height, weight, age) but failed to meaningfully use it in the shopping experience. None effectively combined measurement technology with growth trajectory prediction.

This analysis highlighted an opportunity: creating an app that puts the child at the center of the experience with AI-driven size prediction that actually leverages parent-provided data to deliver real value.

Defining the Problem

Based on the research insights, I crafted a problem statement that captured both the emotional and practical challenges parents face:

"Neelam is a mother and teacher who feels overwhelmed and anxious about keeping up with her child's clothing needs because her child's development is rapid, seasons constantly change, and she has limited time in her busy schedule to stay organized and ahead of these changes."

This problem statement helped keep the design focused on addressing both the emotional burden and practical challenges of children's clothing management.

Design Journey:
Key Challenges & Solutions

How to reduce skepticism when it comes to predicting something as variable as a child's growth? Early concepts featuring size predictions needed to be explored.
Design Exploration:
I explored several approaches to communicating prediction confidence.
Solution: I designed a "Size Confidence" system with clear visual indicators showing prediction confidence based on measurement recency and data completeness. Rather than hiding uncertainty, the design embraced transparency to build trust.
Research revealed that parents were concerned about managing clothing expenses, be it worrying about buying too much or wasting money on wrong sizes.
Design Process: I explored different approaches to budget visualization, from detailed spending breakdowns to simplified progress indicators.
Solution: I created a budget management system that:

Provided clear data showing monthly spending against budget

Integrated into the shopping flow rather than requiring separate management

Used neutral language and visuals that informed without judgment
For families with multiple children, parents need to efficiently manage different growth patterns, sizes, and preferences without constantly re-navigating.
Design Process: I explored various approaches to multi-child management, including:

Hamburger menu selection

Drop-down selectors

Home screen dashboard
Solution: I designed a child-switching system that:

Maintained context when switching between children (keeping you on the home screen)

Provided clear visual indicators of which child profile was active

Leveraging AI in the Design Process

Throughout the project, I used AI as a design thinking partner in several key ways:

Research synthesis: I used AI to help identify patterns across interview transcripts, which surfaced emotional aspects of shopping that might have been overlooked
Competitive analysis: I structured a systematic evaluation of competitor apps with AI assistance, revealing critical insights about collected-but-unused child data
Design exploration: I generated multiple layout variations to expand design possibilities beyond my initial concepts

The key was using AI to enhance my design process while maintaining human judgment for all critical decisions.

The Final Solution: Key Features

The home screen directly addresses the key research insights:

At-a-glance growth status with clear confidence metrics

Predictive timeline for upcoming size changes

Personalized sale alerts for current and upcoming sizes
This dashboard puts the child at the center of the experience, immediately addressing parents' primary concerns about current fit and future needs.
The shopping experience builds on research insights about time constraints and decision confidence:

Size-specific product recommendations filtered for relevance

Growth prediction integration in product details

Streamlined browsing based on current and predicted sizes
This experience saves time by showing the most relevant products first and building confidence with integrated size prediction data.
The cart system addresses the budget concerns and emotional aspects uncovered in research:

Visual budget management tools

Separate sections for committed vs. considered items
Throughout the design, AI capabilities enhance the user experience in meaningful ways:

Growth prediction algorithms that become more accurate with user-provided measurement data

Smart recommendations that consider both style preferences and growth patterns

Virtual try-on capabilities that visualize how clothing might fit
The key was implementing these features in ways that felt helpful rather than intrusive, keeping the technology in service of user needs rather than as a flashy feature.

Usability Testing & Iteration

Key Findings:

Users valued the budget planning features but wanted more visual feedback
The growth hub concept needed clearer explanation and purpose
Size confidence indicators were well-received but required more context
Some users were confused by the separation between current and future size shopping

"I like the idea of seeing my budget while shopping!"
—Usability test participant

Before / After Usability Study

Simplified the growth hub interface with clearer labels and information hierarchy
Enhanced size confidence indicators with measurement recency context
Improved navigation between current and future size shopping sections

Impact & Next Steps

Project Outcomes

Created a unique solution focused on growth prediction and personalization
Developed an AI-powered system that meaningfully utilizes child data
Designed a holistic experience that addresses emotional and practical needs identified in research
Established clear differentiation from competitors based on competitive analysis

Metrics for Success

Reduce shopping time by 50% through predictive recommendations
Increase purchase confidence through size prediction features
Reduce return rates by improving size accuracy
Improve customer retention through long-term growth tracking

Next Steps

Develop a responsive web version while maintaining the focused experience
Create solutions for non-parent shoppers (gift-givers, grandparents, etc.)
Explore integration with retailer inventory systems for real-time availability
Implement more extensive usability testing with a broader demographic range

Lessons Learned

Research-driven design yields unexpected insights. My initial assumptions about what parents wanted were challenged by the research, leading to a more focused and valuable solution.

Balance feature depth with simplicity. Finding the right balance between powerful features and straightforward experiences was crucial for busy parents with limited time.

Address emotional needs alongside practical ones. The guilt and anxiety parents felt about wasted clothing was just as important to address as the practical challenges of finding the right sizes.

AI can enhance the design process. Using AI thoughtfully as a design partner expanded my thinking while maintaining human judgment for key decisions.

Most importantly, I learned that translating complex data (like children's growth patterns) into intuitive interfaces requires both deep research understanding and thoughtful design execution—skills I continue to develop as a UX designer.