Onboarding Questionnaire Design for Financial Strategy App

Harshith K Nayak

Completed work

UX Designer

Figma

Investment & Asset Management

Designing onboarding questionnaire for a personal finance strategy app — UX case study

Harshith K Nayak

10 min read

Nov 14, 2024

This design challenge or problem statement was given to me as a part of a hiring assignment from an organisation. but unfortunately, I couldn’t take part or complete the assignment due to a family emergency which I couldn’t avoid.

So thought of taking the brief and doing a personal case study.

Timeline: 7 days

Design brief (Problem statement)

Design a streamlined onboarding questionnaire flow for personalisation in a financial strategy planner mobile app. The goal is to gather only the most essential information to create personalised financial strategies, ensuring the questionnaire is intuitive and engaging. The flow should minimise drop-offs by avoiding overwhelming the user, while still collecting the necessary data to craft effective and personalised financial strategies.

Constraints: 1. The number of screens shouldn’t exceed 06. 2. Don’t include questions on confidential documents such as bank, PAN, debit or credit card details 3. Use DM sans as font 4. Choose your preferred layout style but use #E46B4 as the accent colour.

My design journey went like this

Defining the Financial Strategy Planner app

A financial strategy planner app is a digital tool designed to assist individuals in managing their finances by creating tailored strategies based on personal financial data. It aims to provide insights on savings, investments, and other financial planning according to provided data and goals.

Setting success metrics for the onboarding questionnaire.

Reducing drop-off rates or funnelling

Reducing overwhelm during the questionnaire

Collecting required data as accurate as possible

Increasing user trust

Reducing time consumed to complete the process

Check prototype here

Competitor analysis

I conducted a competitive analysis including fintech and other products which involves onboarding personalisation questionnaires, to identify how others have approached this flow and to understand their measures to reduce drop-offs and increase trust. This research allowed me to differentiate our questionnaire and provided a base for the design approach.

Divided into two parts: 1. Before user research: To understand the basic approach and steps to follow, 2. After user research: After finalising questions and grouping, for design and placement reference, and for insights on what to use and what not to use.

Desk research

Based on all desk research, I gathered a base understanding of the onboarding questionnaire approach and necessary questions to plan and strategize wealth management through an app.

7 out of 12 referred article links are shared here: Hedgehog lab — Click here to read Clever tip — Click here to read Userpilot — Click here to read Apiko — Click ere to read Plat AI — Click here to read Defour Analytics — Click here to read Leeway Hertz — Click here to read

User research to understand their mindset

1. Card sorting to shortlist questions 2. Card sorting to understand questionnaire order an grouping 3. User interview to understand their perspective and requirements

1. Card sorting to shortlist questions

Had two Options regarding collecting user opinions on the questions I finalised based on desk research. Either create and circulate a Google survey form or go to users and do card sorting with all questions.

Chose the second one because of time constraints, alongside can conduct the other two activities simultaneously with the same people (better understanding) and, I’m living in an area that is surrounded by PGs, so it is easy to reach people quickly.

Provided users with three options for each question, Needed, Not needed, and Don’t know. And also additionally, asked them to suggest any questions they felt should be added.

2. Card sorting to understand questionnaire order and grouping

To get to know the user's take on grouping and ordering the questions, I asked the same 5 users to group the questions into as many categories as they thought appropriate and arrange them in the order they felt made sense. After grouping, users were asked to name the groups.

3. User interviews to understand their perspective and requirements.

Along with the second card sorting I also conducted user interviews with the same people. Here the questions were designed both directly and indirectly to understand user thinking and their approach toward disclosing financial information and completing a sign-up or onboarding questionnaire. You can find the questions blueprint list through this link

Major insights from user research

Found out a common trait: whenever I explained some insights regarding why a specific question is required based on my research and understanding, for a few questions, users reconsidered or changed their decisions.

People prefer to give out their salary and income figures in terms of ranges rather than exact numbers.

While talking randomly with someone, people prefer to tell exact figures (no fear of remembrance) of their income and savings, but when it involves documenting or a sense of remembrance, they prefer ranges over exact figures.

The answers users give to the first question, particularly those in the front row, influence how they consider and respond to subsequent questions. (Ordering plays an important role.)

Once users gained trust, they were ready to share all documents and exact figures.

A progress indicator helps users avoid abandoning the answering process midway.

Users prefer answering questions they see as directly contributing to their financial strategy and which require less effort. Questions that seem unrelated or require more thought tend to be skipped or answered inaccurately.

Included one question regarding ‘Retirement age’ based on user suggestions.

Ratings to finalise questions

Developed a rating framework based on insights from user research (card sorting and interviews) and desk research. This approach enabled me to prioritise questions and strike a balance between user expectations and system requirements.

Finalised questions, order and categories

Avoided asking user’s name, as it should be asked along with e-mail or phone number while initial registration or sign up.

Low-fidelity paper wireframes to set a base for design.

Design elements and structure for input fields and buttons

High-fidelity visual design.

Initial screen

Used a concise heading copy, “Finance is personalised, so should be the strategies to manage and guide,” to encourage users to engage with the questionnaire by emphasizing the value of tailored financial advice.

Chose, ‘personalise’, over, ‘personal’, in copy to avoid evoking a subconscious feeling of privacy concerns, steering the narrative toward customisation and strategy refinement.

Displayed the estimated time to complete the questionnaire to help users commit to the process. Opted for an exact figure, ‘160 seconds’, as it feels quicker than, ‘2 minutes 40 seconds’, using perception bias for a smoother experience.

Included a copy on data protection and user control to address privacy concerns, to increase trust and reduce hesitation.

Personal details screen

Displaying user progression as a percentage provides clarity on the process and reduces cognitive load by offering a sense of control and understanding of completion.

Adding a faded illustration at the top of each questionnaire page introduces a playful, friendly tone without distracting from the main questionnaire, while the user’s focus remains on answering questions.

Framed most questions as “choose an option” rather than free-text input, making the process feel quicker and less mentally taxing, as selecting predefined options requires minimal effort compared to manual entry.

Family details screen

Adding “including you” in the family members and dependents section leads an emotional connection and inclusiveness, making the question more relatable and less formal.

Added a concise copy below specific questions to explain their relevance, showing how responses contribute to financial planning. This addresses doubts about the necessity of certain questions, a key insight from the card sorting exercise.

Implemented a back icon for user control and freedom, allowing users to revisit and adjust their answers, enhancing the sense of control and reducing potential frustration.

Core finance screen

Instead of using manual input or range-based options for income, savings, and spending data, I designed an indicator bar to collect approximate figures. This leads to accurate data critical for financial decision-making.

User interviews revealed that asking for exact income figures upfront could deter new users due to privacy concerns. Many preferred starting with a range and providing exact figures once trust in the app was established.

While range inputs offer ease, they lack precision, leading to more generic advice. The indicator bar bridges this gap, offering near-accurate inputs while assuring users they aren’t forced to disclose exact figures. This method balances user comfort and the app’s need for precise data.

Assets and liabilities screen

Initially, asking for an overview of investments, debts, and insurance details helps avoid overwhelming the user. This approach prioritises user comfort while collecting essential data.

As users build trust with the app and seek deeper personalisation, more detailed information, like specific investment types, exact debt amounts, and comprehensive insurance details can be gathered in later stages.

A similar approach applies to income, savings, and spending data. General ranges are asked upfront, with more accurate figures requested once the user feels secure, ensuring a balance between data accuracy and user easiness.

Shifted insurance question to from last page this page, to add, “Where did you hear about us”, the question on last page and balance placing across the pages.

Financial goal screen

Asking users to manually input their goals ensures that the system captures highly personalised and specific objectives, which are critical for creating tailored financial strategies.

Since users know this is the final step, they are less likely to abandon the process. They recognise that skipping this step could render their previous effort meaningless, reducing drop-off rates at this stage.

Providing clear examples and a brief guide within the input field based on the help and documentation heuristic. This reduces confusion and directs users in framing their goals effectively.

Adding a question like, “Where did you hear about us?”, along with this questionnaire row at the end has a higher chance of being answered compared to placing it somewhere else since it aligns with the user’s completion mindset.

Web layout.

Changed illustrations and their colour combinations on the web layout for a better visual appearance

User testing & iteration

I tested with 3 users and did an iteration based on user behaviour, reactions and feedback.

Users raised a concern about going back and changing the already answered questions. This led to the addition of a Back button for more flexibility.

Added a stepper indicator (ref: X-1/X) with a progress bar for better visual identification of the number of steps and which page the user is currently on.

Changed the selected state from the filled colour to the present state for better identification and differentiation.

Changed the default state text from grey to primary text colour for better visual hierarchy. Initially, users confused it as a non-clickable element.

Learning

Clear communication increases completion rate: Clearly articulating the value or necessity of a task significantly increases the chances of users completing it. When users understand why their input is important, they are more motivated to engage fully.

Optimising user effort: Designing input fields and onboarding experiences should have an approach in such a way that it meets all requirements while demanding minimal user effort. This balance reduces cognitive load and drop-off rates.

Impact of variation in communication: Using variations in language and visual elements can influence user decisions. Subtle shifts in wording or imagery can reshape how users perceive and interact with a task, enhancing engagement and completion rates.