Introduction
‍
I developed comprehensive design guidelines for Alunar, an AI-powered investing app, by synthesizing interactive feedback from stakeholders and aligning it with user-centered research principles. These guidelines provided a framework to ensure a seamless and intuitive user experience, balancing accessibility with the app's advanced AI-driven portfolio management features.

The guidelines emphasized personalized risk assessment, transparent AI communication, and streamlined interaction flows, enabling Alunar to meet diverse user expectations across varying levels of investing and AI familiarity. This work empowered the team to create a scalable, user-centric platform that simplifies investing for all users.

Introduction
‍
In September 2023, we embarked on a UX research journey to evaluate Alunar, an AI-powered investing app designed to empower users with tailored investment strategies. Alunar leverages language models to craft personalized plans aligned with individual risk tolerances and financial goals.Our objective was to understand how a diverse group of users interacted with the app, uncover their expectations, and refine the user experience. Over a four-month period, we observed twelve participants — evenly split by gender and varying in their familiarity with investing and AI — as they navigated and engaged with the platform.This study offered invaluable insights into user preferences for financial apps and shaped Alunar's iterative design process.

Project Brief
‍
Problem
‍
Investing can feel inaccessible, especially for individuals new to financial planning or wary of market risks. Apps like Alunar aim to democratize investing, but there’s a fine balance between offering sophisticated AI features and ensuring an intuitive user experience.

Opportunity
‍
By observing real users interact with Alunar, we could identify pain points, enhance user trust, and ensure the app met both novice and experienced investors’ needs. The study also aimed to explore the effectiveness of AI-driven suggestions and gauge user comfort with delegating investment decisions to technology.

Proposed Solution
Through qualitative and task-based testing, we sought to uncover actionable insights.

The research focused on:
‍
- Understanding user behavior, expectations, and preferences in investment apps.
- Assessing how participants navigated key features, such as goal-setting and personalized risk management.
- Refining communication of AI-driven insights to balance simplicity and trust.
‍
Methodology
‍
Participants
‍
Sample Size: 12 participants.
‍
Demographics: Equal gender split; participants ranged from complete beginners to seasoned investors.
‍
AI Familiarity: Varied, from minimal exposure to advanced knowledge.
Research Setup
‍
Study Timeline: September 2023 – December 2023.
‍
Tools Used: Remote usability testing, screen recordings, and follow-up interviews.Tasks and Scenarios:
We designed goal-based scenarios reflecting real-world investment goals.

For example:

"Imagine you're a beginner looking to save for a down payment in five years. How would you use Alunar to create a plan and assess your risk?"
‍
"You’re a seasoned investor curious about diversifying your portfolio with AI recommendations. Explore how Alunar can assist you."
‍
"You want to understand the risks associated with an AI-recommended strategy. Walk us through your steps to evaluate this."
‍
Key Findings and Insights
‍
1. Ease of Onboarding
‍
Participants appreciated Alunar’s onboarding process, which offered a quick questionnaire to identify financial goals and risk tolerance. However, some novices found financial jargon intimidating.
‍
Recommendation: Simplify terminology and provide tooltips for complex concepts (e.g., “risk-adjusted returns”).

2. AI Transparency and Trust
‍
Many participants expressed initial skepticism about AI recommendations but were reassured by clear explanations of how decisions were made.
‍
Quote: "I want to know why the AI thinks this is the best option — not just follow blindly."
‍
Recommendation: Include "explainability" features, such as visual breakdowns of risk assessments or decision pathways.

3. Tailored Risk Management
‍
Users praised the customizable risk sliders but wanted more examples illustrating real-world scenarios (e.g., “low risk” vs. “high risk” outcomes).
‍
Recommendation:

Recommendation: Add interactive simulations showing potential returns and losses for different risk profiles.

4. Confidence Boost for Novices
‍
Beginner investors valued the app’s step-by-step guidance but sought additional hand-holding, such as video tutorials or beginner-friendly modes.
‍
Quote: "I need to feel more confident before making big decisions. Some guidance here would be great."
‍
Recommendation: Introduce an “AI Coach” feature with dynamic prompts and real-time tips.

5. Advanced Users’ Expectations

Experienced investors found the app insightful but wanted more granular controls, like custom asset allocation options.
‍
Recommendation: Add advanced settings for experienced users while keeping the default interface simple for beginners.