Preparing a User Research Plan on Users’ Micropayments (for Melli Bank)

Project Overview 

In order to improve the digital experience of Melli Bank’s users (the largest bank in Iran) while doing online micropayments, we needed to find out the users’ needs and extract their current pain points.

Team members

Project Details:

CustomerBMI.ir

Company: Sadad.co.ir

Date: Jun 2020 – Dec 2020

Step 1: Who are our users?

The first step in starting user research is to know our users and to know who our product is used by. For this purpose, we faced two categories of users: 

– One is our current user group

– The other is the potential users’ group.

We asked our in-house data team to give us demographic data about our users so we could identify current users. Our product is used by 5 million users, and we needed some information like: 

  • Gender
  • Age 
  • Education
  • Marital Status
  • Annual income
  • Race/Ethnicity
  • Location (which states they live in)
  • Preferred online banking platform (Web/Mobile app)
demographic data in ux

Demographic survey

To identify new potential users, I designed a demographic survey to collect information from those without an account at Melli Bank.

demographic survey

Categorizing Users to start the research

After gathering enough information about different user categories, it’s a good time to create a user research plan.

Step 2: User Research Planning

After obtaining demographic information about our users, I had to prepare a comprehensive plan for user research. This plan includes detailed information about:

  • Research Goals and Success Metrics
  • User Research Methods
  • Research Cost and Time
  • Recruit Users

Research Goals and Success Metrics:

1- Finding Statistics of Categories of Expenses Less than $10:​​​​​​​

– Frequency of Low-Value Transactions: Measure the number of transactions with values less than $10 in various expense categories.

– Average Transaction Value: Calculate the average value of transactions in these categories.

2- Finding User Pain Points When Dealing with Digital Wallets:

– Pain Point Severity Ratings: Collect user feedback and ratings on the severity of pain points they encounter (e.g., on a Likert scale).

– Frequency of Pain Points: Track how often specific pain points are mentioned by users.

3- Finding Motivation of Charging Wallets by Users:

– Top Motivations: Identify and rank the most commonly mentioned motivations for charging wallets.

– Frequency of Charging: Measure how frequently users add funds to their digital wallets.

4- Finding the Reasons for Not Using Digital Wallets by Some Users:

– Top Reasons for Non-Usage: Identify and rank the primary reasons cited by users for not using digital wallets.

– Demographic Insights: Analyze if there are demographic patterns among users who opt not to use digital wallets.

User Research Methods:

Using different research methods, such as surveys, interviews, etc., in user research offers several advantages that complement each other and provide a more comprehensive understanding of user needs, behaviours, and preferences. I decided to use these methods in this user research project:

  • Brainstorming
  • In-person and phone interview
  • Survey
  • Diary study
  • Focus group
  • Statistical information (analytics)
  • Competitors analysis

Research Cost and Timeline:

After several meetings with product managers and stakeholders, the costs of this user research project were determined (due to the confidentiality of financial resources, it is not possible to mention this information) and a period of three months was considered for the entire research project to be implemented in 3 phases. In each phase, some parts of the research methods will be used and according to the results found in the first phase, the second and third phases can be enhanced.

Phase 1: Two weeks. (One week for research and one week for data analysis and preparation to present and review the results in team meetings) including:

  • Brainstorming: 3 sessions with topics suggested by this document
  • Phone interviews with 20 users
  • In-person interviews with 15 users
  • Online survey: receiving around 50 answers
  • Analytics: digital wallet usage data in the last month (in-house data team)
  • Competitor analysis: preparation of the list of features of competitors wallets

Phase 2: Three weeks. (Two weeks for research and one week for data analysis) including:

  • Brainstorming: 4 sessions with suggested topics
  • Phone interviews with 40 users
  • In-person interviews with 30 users
  • Online survey: receiving around 50 answers
  • Diaries study: 20 people must be employed for this research.
  • Competitor analysis: extract users’ insights on our competitors on social networks (Twitter and Instagram)
  • Focus group: conducting 2 focus group sessions to provide micropayment solutions in urban areas

Phase 3: Three weeks. (Two weeks for research and one week for data analysis) including:

  • Brainstorming: 3 sessions with suggested topics 
  • Phone interviews with 20 users
  • In-person interviews with 15 users
  • Online survey: receiving around 100 answers
  • Diaries study: 10 people must be employed for this research
  • Competitor analysis: Examining the strengths and weaknesses of each competitor / SWOT analysis and estimating the strategy of each company.
  • Focus group: Conduct 2 focus group sessions to provide solutions to get new users.

Conclusion phase: 

One week to summarize the results of the research and data analysis
One week to prepare the research findings as a document

Step 3: User Research Guidelines

In order to align user researchers with the guidelines and principles in this research, I had to define all the detailed steps to conduct user research. In the planning stage, I’ve defined 7 research methods and here I am going to explain how each method will be conducted.​​​​​​​

3.1 Brainstorming

The purpose of brainstorming is to encourage divergent thinking. Brainstorming encourages people to come up with ideas that may seem silly at first. However, some of these ideas can become innovative solutions with a little manipulation. Some of them may spark further ideas. In this way, people’s minds are opened, and they are freed from the prison of conventional thinking. 

To achieve this goal:

  • In brainstorming sessions, no one should criticize or encourage an idea. Judgment and analysis prevent the production of ideas and do not let creativity grow.
  • It is important that no one claims that this idea is mine or his/hers. (Because others prefer to propose a new idea, rather than correcting someone else’s idea. And correcting or completing an idea may cause resistance).
  • Avoid limiting the issue. Because by being lmited, we eliminate part of the possible answers even before the discussion begins. At the same time, people’s sensitivity and mental judgment about their ideas increase.
  • Briefly define the problem. The longer you define the problem statement, the more likely it is that the ideation will be limited.

Best usage of brainstorming method:

When the basic needs of users are outlined in interviews and questionnaires, these needs are raised in brainstorming sessions and ideas are developed on them to find suitable solutions.

  • Number of people: between 6 and 10 people.
  • Participants: Colleagues, Team members, Product managers and stakeholders.
  • Length of each session: 1 to 2 hours
  • Meeting place: a room with space for about 10 people. With a whiteboard and other necessary equipment for writing and taking notes

Suggested topics for brainstorming

  • Examining ways to increase the attractiveness of the wallet
  • Creating solutions for the use of wallets in micropayments
  • Functionality of small money among young people and solutions to replace the wallet
  • Creating new uses for a payment application
  • Investigating new user attraction methods for a new payment application

3.2 User Interview

One of the advantages of in-person interviews is that you not only hear their words, but you can also interact with users by showing your feelings, and they understand your tone better, and you get your information not only by talking, but by seeing users’ body language.  
Some users do not like their voice to be recorded. In these cases, it is better to have another team member with you as a note taker, because when you are busy with the interview, he will take notes and this person must be from the UX research team and know about user research.

Number of interviews: 40 people in-person and 60 people by phone
Length of interview: Around 10 minutes

Purpose of the interview: The purpose of these interviews is to find out why some users are unwilling to use a wallet instead of a bank card or they keep very little amount of money in their wallets. 

Guidelines:

  • Write down your questions prior to the interview, so that you”ll follow the same process with everyone. Keep in mind that in the middle of the interview, you may need to ask questions out of the list. This is useful and helps your findings.
  • Create a friendly atmosphere. Make sure participants feel comfortable before the interview begins and emphasize that their answers will not be judged (say there are no right or wrong answers).
  • Start your session with simple, lightweight questions before delving into the topics you want to explore. You may ask questions like, “What do you do for a living?” or “Can you tell me about your daily hobbies?” to start the interview.
  • Write down the responses details. (or record the voice) You never know what details will be important during data analysis, but you can be pretty sure that you won’t be able to recall enough details from your memory. Even better, ask permission to videotape the interviewees, which you can share with your team for analysis later.

Create a friendly atmosphere. Make sure participants feel comfortable before the interview begins and emphasize that their answers will not be judged (say there are no right or wrong answers).
– Start your session with simple, lightweight questions before delving into the topics you want to explore. You may ask questions like, “What do you do for a living?” or “Can you tell me about your daily hobbies?” to start the interview.
– Write down the responses details. (or record the voice) You never know what details will be important during data analysis, but you can be pretty sure that you won’t be able to recall enough details from your memory. Even better, ask permission to videotape the interviewees, which you can share with your team for analysis later.

Suggested questions about micropayments:

How do you make payments (taxi, bus, shoppings, inexpensive online and offline services that are under $10)?
What is your biggest payment challenge in these places?

Suggested questions about using digital wallets

– Do you use any of these applications mentioned in the list?
– What reasons do you have for choosing your current payment app over competitors?
– Which of the aforementioned apps do you not use at all? Why?
– Do you prefer to get all the services in one app or use several separate apps?
– How much do you trust these apps?
– What makes you feel insecure about these apps?

Suggested questions about digital wallets:
  • Do you keep money deposited in the wallet?
  • What is the reason that makes you keep money in the mentioned wallet?
  • Do you have a limit in your mind to deposit in the mentioned wallet?
  • Does the mentioned wallet have the possibility of withdrawing the money you have deposited?
  • Why do you deposit money in some applications and make your payment using a card in others?

3.3 Survey

Surveys are designed to find specific questions, and if we do not have descriptive questions, they are referred to as quantitative research methods.
For many of us, it is vital to have the demographic information of users to check their responses. However research has shown that users do not feel good about providing their personal information (even if they are asked completely anonymously). In addition, many people are willing to talk about their marital status or income only after establishing a relationship. Therefore, postponing the demographic questions to the end of the questionnaire is a better approach.

To attract users, be sure to inform your audience of your reasons for requesting such information and clearly explain in what context this information will be used.
For more sensitive questions, instead of asking for data or numbers, use numerical intervals so that the respondent can complete the questionnaire more easily and honestly. For example, stating the exact amount of monthly salary is not pleasant or acceptable for many people. But if you use a numerical range in your answers, the response rate and accuracy of the received answers will increase.

Only ask the questions you need to be answered. In many cases, you don’t need to include all demographic questions in your questionnaire or online survey form.  

Survey time: 2-5 minutes.

  • 80% of the questions should be multiple-choice questions
  • At the beginning, tell the user the total number of questions.
  • Put descriptive questions after multiple-choice questions
  • Avoid asking demographic questions without a reason
  • Maximum allowed questions in a survey: 15 questions

Suggested questions for this Survey

  • What is your age range? (multiple-choice range question)
  • Which of these payment apps do you use? (name 5 competitors)
  • What are the reasons that made you use this mobile app?
  • What is the maximum amount of money you transfer to/from these apps?
  • Which of these in-app services do you not use and prefer to visit an alternative?
  • What made you stop using a payment app?
  • For which payments do you use cash that can be paid by a digital wallet?
  • Name some of your repetitive micropayments (less than $10)

3.4 Diary Study

This method is used to collect behavioral information about the user, his activities and his experience (of using a product) over a long period of time (e.g. one month). During the reporting period, participants are asked to keep a diary and record specific information related to the study activities. In order to remember to fill in their diaries, the participants are sometimes prompted periodically (e.g. through a daily notification or at certain times of the day).

Diary studies are useful for understanding long-term behaviors such as:

  • Habits (e.g. the times and places they use the app)
  • Usage scenarios (how much the user engages with the product and what he does)
  • Attitudes and motivations: What motivates people to do certain things? How do users feel and think?
  • Changes in behaviors and perceptions: How learnable is the system? How loyal are customers over time?
  • Study the customer journey in cross-channel products
  • Understanding all interactions within a site/app during the time period
  • Behavior: Collect general information about user behavior

Number of participants: 30 users (10 users in each category)

  • We must create specific and precise instructions for writing in the diary notebook. Be as specific and detailed as possible about the information we ask participants to enter.
  • Remind the participants about filling their daily diary. e.g. through daily notification using SMS or email.
  • If possible, we should print a notebook with details and provide it to the users.
  • Adding images (screenshots) is sometimes helpful and we can ask users to send us a photo of the steps they encountered a problem in their online notebooks.

A diary study usually consists of 5 steps:

1. Planning and preparation: Determine the objectives of the study and the long-term behaviors you need to understand. Specify a timeline, select tools for participants to report data, recruit participants, and prepare instructions or support materials.

2. Short pre-study: Dedicate some time before starting the research for participants to get familiar with the system. Conduct an in-person meeting or phone call with each participant to talk about study details. Show them the schedule or calendar for the reporting period and explain the expectations. Teach them how to use the tools that will be used, be sure that every participant is familiar with this technology.

3. Journaling Period: Provide a simple framework for effective journaling. (Discovery is one of the main reasons for conducting user research, and we will present solutions below to record all events.) Prepare clear and detailed instructions for entering user memories and mention how much details to enter.
There are two common methods that researchers use to collect memory data from participants.
    3.1. Immediate journaling: This is the easiest method to collect data. The participants are asked to record information about the activities in the situation where it happens immediately. (Using an audio or video file of themselves or writing in a notebook or mobile phone)
    3.2. Snippet technique: Using this technique, participants only record brief information about activities as they occur. Then, at the end of the day, they describe the details of each activity. This 2-step method ensures that relevant information is captured before it is forgotten on the situation, without providing too much detail at the time of initial recording.

4. Post-study interview: Evaluate all information provided by each participant. Schedule a follow-up interview to discuss the diary in detail. Ask probing questions to discover specific details needed to complete the story. Ask the participant for feedback about their experience participating in this study.

5. Data analysis. Because diary studies are long, they generate a large amount of qualitative data. Evaluate user behaviors during the study. How do they evolve and change over time? What influences these behaviors? As the focus of your study is on a specific product or service, look at the entire customer journey. Create a customer journey map to help you understand the user experience from your customer’s perspective.

3.5 Analytics

Analytics data can validate or challenge hypotheses generated during user research. For example, if user interviews suggest that users frequently abandon a particular task, analytics can confirm the dropout rates for that task. We will use analytics to learn about

microtransactions our users make during a period of time which is determined as one month in this research.

We have an in-house data analytics team that collects and analyzes data and we’ve asked them to provide us with the following information about user payments:

Transaction Frequency:

  • Number of transactions made by each user during the last month.
  • Average number of transactions per user per week or month.
  • Breakdown of transaction types (e.g., transfers, payments, purchases).

Transaction Amounts:

  • Average transaction amount for transfers and digital wallet payments.
  • Total transaction volume (sum of transaction amounts) for each user.
  • Distribution of transaction amounts (e.g., percentage of small transactions, large transactions).

Transfer Destination and Source:

  • Most common destination accounts for transfers (e.g., other bank accounts, external services).
  • Source of funds for transfers (e.g., linked bank accounts, wallet balances).

Payment Methods:

  • Breakdown of payment methods used for digital wallet transactions (e.g., credit card, linked bank account, balance).
  • Trends in preferred payment methods over time.

Transaction Timing:

  • Peak transaction hours or days during the week.
  • Monthly trends in transaction activity (e.g., any seasonality or patterns).

User Retention:

  • Retention rate of users over time (e.g., percentage of users who continue using the platform for six months or more).
  • Churn rate (percentage of users who stopped using the platform).

Error Rates:

  • Frequency of transaction errors or failures (e.g., insufficient funds, technical issues).
  • Types of errors encountered by users. 

3.6 Focus Groups

A focus group is an interactive guided conversation with a carefully selected (usually demographically diverse) group of users used to obtain feedback about a product, service, or concept. 

In the focus group, open questions are asked to the group members and the participants are encouraged to answer and interact freely with other group members. As you guide the conversation, a writer takes notes, and video recordings may also be made for further analysis. Focus group sessions usually last 1 to 2 hours. Both the preparation and facilitation phases are important to effectively conduct a focus group, but more effort should go into the preparation phase.

Focus Group Execution Details: 

  • Usually 6 to 12 people participate in each group.
  • A focus group covers only four to eight high-level questions. Questions should be open-ended and move from general to more detailed ones.
  • Specify a moderator to organize the meetings.
  • Record the meeting session, or assign someone to take notes.
  • Participants can be a combination of designers and users of the app.
Suggested topics
  • Ways to increase the attractiveness of the wallet for young users
  • Solutions for increasing the speed of online payments

3.7 Competitor Analysis

Competitor analysis is a strategic practice that involves evaluating the actions, strategies, strengths, and weaknesses of rivals in a given market. It provides several benefits, including identifying market trends and opportunities, understanding customer behavior, enhancing market positioning and guiding product and service innovation.

In this research, several apps are considered for the first phase of analysis. In the coming months, this research can be continued to follow the progress of each app. 

Main competitors:

Things to consider:

  • Periodically and regularly, hold meetings to review competitors and analyze their behavior.
  • Determine the size of each app’s user base and its market share in the payment app industry. This provides insights into their reach and popularity.
  • Analyze the demographics of their user base, including age, gender and location to identify their target audience and potential gaps in user segments.
  • Evaluate the features and functionality offered by each app, such as peer-to-peer payments, mobile wallet integration, bill splitting, and international money transfers. Compare the range and effectiveness of these features.
  • Assess the user interface and overall user experience of each app, considering factors like ease of use, navigation, and mobile responsiveness.
  • Analyze the fee structure for using the payment app, including transaction fees, currency conversion fees, and any other charges. Compare these costs with competitors.
  • Evaluate the speed and reliability of transactions processed through each app. Consider factors like processing times and uptime.
  • Determine which other apps, platforms, or services each payment app integrates with, such as e-commerce websites, mobile apps, and banking services.
  • Assess the quality and responsiveness of customer support provided by each app.
  • Review user ratings and feedback on app stores to gauge user satisfaction and identify common pain points and strengths.
  • Analyze the marketing tactics and branding strategies employed by each app, including advertising campaigns, partnerships, and brand messaging.
  • Ensure that each app complies with relevant financial regulations and data privacy laws in the regions it operates. Identify any legal or compliance issues.
  • Explore how each app acquires and retains customers, including referral programs, loyalty rewards, and onboarding processes.
  • If available, analyze financial data such as revenue and profit margins to assess the financial health and sustainability of each payment app.
  • Identify any strategic partnerships or collaborations that each payment app has formed with banks, businesses, or other entities.

Step 4: Pattern Identification and Insight Generation

In this step we should:

  • Look for patterns, trends, and correlations within the data.
  • Identify key themes and commonalities in qualitative data.
  • Calculate summary statistics for quantitative data.
  • Extract actionable insights from the data. 

These insights will answer research questions, address user pain points, and provide guidance for design decisions.

Key actions to take during this step:

– Familiarize with the data by reading or reviewing the transcripts, survey responses, or quantitative datasets. Get a sense of what the data contains.

– For qualitative data (interview transcripts, open-ended survey responses, etc.), start by coding the data. Coding involves tagging or categorizing sections of text that relate to specific topics, themes, or concepts.

– Use descriptive codes to label segments of text that capture meaningful information. Be open to creating new codes as you encounter unique insights.

– Once you’ve coded a substantial portion of the data, begin to identify overarching themes or patterns. Themes represent recurring concepts or ideas across multiple data points.

– Group similar codes together to form higher-level themes. These themes should be data-driven and emerge from the content rather than being preconceived.

– For quantitative data (e.g., survey responses, usage metrics), use statistical analysis tools and techniques to identify trends and patterns. This may involve calculating averages, percentages, correlations, or conducting regression analysis, depending on your research questions.

– Create data visualizations such as charts, graphs, and histograms to help you spot trends and patterns more easily. Visual representations can reveal insights that might not be apparent in raw numbers.

– For both qualitative and quantitative data, compare findings from these sources to validate or enhance your understanding of patterns. Are the qualitative insights consistent with quantitative trends?

– Understand the context surrounding the identified patterns. Ask yourself why these patterns exist and what they mean for the user experience or your research objectives.

– Consider using data analysis software and tools to aid in pattern identification. Tools like Excel can be valuable for qualitative and quantitative data analysis, respectively.

– Keep detailed notes and documentation of the patterns you identify. Document the frequency and significance of each pattern and its potential implications for your research objectives.

– Invite colleagues to review your analysis and patterns. Conduct peer debriefing or member checking, where others examine your findings to ensure objectivity and accuracy.

– Be open to revisiting the data analysis if you discover new patterns or insights during the research process. Data analysis is often iterative, and patterns may become clearer over time.

– Synthesize the patterns and insights into actionable findings that address the research objectives. These findings will inform recommendations for the product design process.

– Begin by summarizing the key patterns and trends that emerged from data analysis. This serves as the foundation for generating insights.

– Explore the implications of the identified patterns on user behavior and interactions with the product. Understand how these patterns relate to the user experience.

– Focus on how the identified patterns impact users’ experiences, satisfaction, and outcomes.

– If you’ve segmented the user base, explore how different user groups are affected by the identified patterns. Are there distinct insights for each segment?

– Investigate any anomalies in the data. Sometimes, these exceptions can lead to valuable insights about edge cases or unmet user needs.

– Balance quantitative insights (surveys, statistics) with qualitative insights (user feedback from interviews, diary studies) to provide a comprehensive view. Quantify where possible, but also capture the human aspect of the insights. 

– Identify pain points and unmet needs that users are experiencing based on the patterns. These pain points can be opportunities for improvement or innovation.

– Pinpoint opportunities for enhancing the user experience based on the identified insights. Consider how changes or optimizations can address user pain points or capitalize on positive trends.

– Prioritize the generated insights based on their impact and relevance to the research objectives and product goals. Not all insights may be equally critical.

– Translate insights into actionable recommendations. Provide clear and specific guidance on what steps should be taken to leverage the insights for product improvement.

– Ensure that the generated insights align with our research goals and objectives. This helps maintain a clear connection between the analysis and the research’s purpose.

– Consider seeking validation and peer review of the insights from colleagues or stakeholders. This can help ensure the accuracy and objectivity of the findings.

– Document the insights in a structured format, such as a report or presentation. Include supporting evidence and examples to illustrate each insight.

Step 5: Reporting and Documentation

The “Documentation” step is crucial for preserving and communicating the findings, insights, and recommendations derived from the research efforts. Clear and organized documentation ensures that the research results can be effectively shared with stakeholders, referenced in the future, and used as a basis for decision-making and action. 

In this step we should:

  • Gather all relevant research findings, insights, and recommendations in one place.
  • Create a well-organized research report or document with clear sections and headings.
  • Include evidence from the data, such as statistics, and examples, to back up insights.
  • Outline actionable recommendations based on the insights to guide decision-making.
  • Share the document with the design team, stakeholders, and encourage discussions to ensure understanding and application of the research insights.

User Research Findings: 

Usability Issues: Users reported difficulties in navigating through the payment options and completing transactions. Some found the process confusing and prone to errors.

Error Rates: Analytics data revealed a higher-than-desired rate of payment-related errors, including failed transactions and incorrect recipient information.

User Preferences: Qualitative interviews and surveys indicated that users preferred a more intuitive and streamlined payment process that minimized steps and provided clearer instructions.

Creating User Persona

The results of this user research also helped us create a better persona of our users.

Conclusion

This research was done in 2020 and the findings helped us redesign the payment section of MelliBank’s app to help users do more with the app in their daily small transactions.

Due to the NDA and data confidentiality, it is not possible to share the whole results of this research in this article.