Intro
Industrial project: Ada Analytics.
Project duration: 1month and 1 week.
Team member: Tina, Sam(me),Dhruv.
Year: 2023.
Role: UI UX designer.
Responsibilities:
Project background:
Ada Analytics is a data analytics company dedicated to empowering individuals and organizations with advanced analytical tools for informed decision-making. As an easy-to-use application, Ada Analytics aims to comprehend the investment requirements and objectives of traders, leverage AI techniques to assist customers in examining market patterns and scrutinizing trading visuals, and subsequently provide customized investment strategies in order to establish enduring user trust.
Target audience:
Age: Between 24 to 60 years old’s .
User interested in investment.
Problem statement:
The existing analysis platform lacks a good user experience, a user-friendly interface, and auxiliary functions for decision-making. Additionally, it cannot provide investment advice.
Project goal:
Our objective is to create an intuitive, user-friendly, visually appealing user interface, and AI function that enhances the overall user experience.
Design process:
Discover
Research:
Survey collects (34 responses)
Trading Platforms Used:
Robinhood was the most commonly used trading platform among the respondents, followed by Charles Schwab, Fidelity Investments, first trade, and Webull.
Financial Markets Traded In:
Stocks were the most commonly traded financial market among the respondents, followed by ETFs, funds, derivatives, and cryptocurrencies.
Frequency of Platform Use:
Respondents reported using trading platforms anywhere from once a week to multiple times per day.
Challenges Faced When Using Trading Platforms:
The most significant challenges faced by respondents when using trading platforms were lack of proper knowledge and expertise, market volatility, and inadequate risk management.
Features or Tools Used Most Frequently When Trading:
The most frequently used features or tools when trading were charting and analysis tools, news and articles, live quotes and watchlists, and customer recommendations.
How Investment Decisions Are Made:
Respondents reported making investment decisions by looking at stock price data and trends, reading market news and analysis, looking at industry news and trends, and taking advice from peers or friends.
Where AI-Powered Trading Recommendations Would Be Considered:
Respondents reported that they would consider using AI-powered trading recommendations for greater accuracy in predicting market trends and profitable trades, expedite preliminary research before investments, personalized recommendations based on their trading habits and goals, simplifying complex market analysis, and learning and adapting to their trading patterns over time.
User interview:
User interview summary
AI on platform:
All interviewees believe AI can enhance information retrieval and analysis.
AI insight and analysis:
Most of the interviewees desire an AI feature for investment insights and news organizations.
Third party analysis tool:
All interviewees make use of third-party analysis tools to obtain more comprehensive information.
Security issue:
Some interviewees think that the platform should be user-friendly with strong authentication.
Competitor analysis:
Discover
Comparison of functionality within competitors:
Discover
Competitor analysis summary:
The following online retailers capture a large chunk of market share due to their popularity in this space and overall ease of use.
Discover
Chatbot competitor analysis:
Discover
Comparison of functionality within chatbot competitors:
Discover
Persona:
Creating persona help us to focus on finding the best possible solution and ensure that our efforts are aligned towards achieving goal.
Discover
User journey map:
Better to understand how the user interacts with the current product and what’s the problem they face in each stage.
Ideate
Information architecture:
Concept of the website structure.
Ideate
Sketch:
Home page
Company's ticker's page
Adabot response
Ideate
User flow:
Concept of the website structure.
Adabot analysis the company
Adabot generate the suggestion of portfolio
Design
Wireframe:
Adabot analysis the company
News page
Community
AI generate solution (expand and not expand)
Design
Design system:
Design
UI mock up:
Homepage
User's portfolio
Company ticker's page
Adabot page
Adabot finding solution page
Adabot finding solution page
Adabot response page
Outcome and future
Outcome:
Throughout the project process, I gained valuable experience on how to effectively collaborate with a team, which differs greatly from my previous experiences in school. Although I had no prior knowledge of the investment field, this project taught me that it is possible to succeed even without any prior experience. I gain knowledge about investment fields through conducting research, participating in discussions, and gathering user feedback.
Future:
My team and I have a few tasks left to complete. These include usability testing and refining the High-fidelity of our product. To move forward, I plan on conducting usability testing to gather feedback on the current design and then use this feedback to refine the entire design and make our product more valuable. Moreover, if the design trend changes in the future, I will use the latest design methods to discuss with the team and improve the entire architecture.