Lean UX Method Overview
CompanionX: A Human-Centered Platform Connecting Overseas Families with Trusted Companions for Kerala's Elderly using the Lean UX Method with Think-Make-Check phases. This systematic approach ensured user-centered design decisions backed by research and validation at every step.
The Challenge
Kerala has the greatest number of residents above the age of 60. With mass migration to overseas countries for work, elderly individuals are left alone, struggling with loneliness and lack of trusted support. The project aims to create a CompanionX application for those over the age of 60 in Kerala, providing emotional and physical care through verified companions.
Understanding the Problem
The need for developing CompanionX stems from a desire to solve the unique challenges faced by elderly individuals, especially those who live alone due to migration and demographic shifts. CompanionX utilizes technology to address challenges faced by older citizens, particularly those in Kerala.
Research Foundation
Desk research explored regional demographics, caregiver-to-elder ratios, emotional wellbeing studies, and technology adoption rates. This insight supported persona development, accessibility strategies, and the business case for building a platform like CompanionX.
Literature & Technology Research
Research covered topics like geriatric mental health, mobile health services, loneliness studies, and technology adoption among elderly. Emerging technologies such as AI-powered companion matchmaking, geolocation, and health record tracking were explored to assess feasibility, risks, and adoption barriers.
Competitive Landscape
Competitor review covered Indian and global solutions like Papa Pals, Seniority, and UrbanClap. Gaps identified: limited emotional support focus, no verified assistant model, and low trust-building mechanisms. Key insights show most apps focus on task management with minimal emotional care.
Primary Research
Research was designed around semi-structured interviews targeting overseas children and elderly individuals. Participants included 5 real users—two NRIs, one assistant, and two elderly locals. Sessions captured context, digital behaviour, emotional triggers, and trust perceptions around caregiving.
Insights Synthesis
Key quotes from all interviews were coded into themes such as loneliness, verification concerns, recurring caregiver absence, and confusion with multi-app usage. Insights were synthesised into Six themes: Trust and safety, Cultural & Communication Fit, Emotional & Companionship needs, Family peace of mind (Remote care), Functional and Daily needs, Assistant's Voice.
Strategic Framework
Based on early research, assumptions were made around user fears, motivations, and expected features. From a value proposition angle, assumptions included willingness to pay for verified service, interest in real-time tracking, and trust in a Kerala-branded platform. The canvas provided a consolidated view of business vision, user pain points, high-value tasks, and solution hypotheses.
User Journey Mapping
This diagram illustrates the core tasks, thoughts, and emotions experienced by users across the caregiving journey. Emotional resonance, trust gaps, and task frequency were mapped to identify friction points and opportunity zones for design interventions.
Feature Prioritization
Participatory design input and internal synthesis were used to categorise feature ideas into: Must-haves (core MVP features like verified companion matching and emergency alerts), Nice-to-haves (social features, AI mood detection), Low-priority items (smartwatch integration, multilingual chatbot). Feature ideas were assessed for development feasibility vs user value impact.
Ideation & Concepts
Sketch-based ideation was used to rapidly explore layout options for: Home dashboard, Companion profiles, Mood tracking, Rewards/loyalty for usage. This process helped generate multiple solutions before converging on the most promising concepts.
User Personas - Elderly Citizen
Joseph Mathew is a 64-year-old farmer from Wayanad in Kerala. He owns a couple of cows and delivers milk daily at the local milk society. His frustrations include difficulty finding trustworthy local support, loneliness from children and grandchildren living overseas, and lack of trusted companions. He struggles with technology but is eager to connect with reliable helpers who understand his cultural context and language preferences.
User Personas - Overseas Daughter
Anita Mathew is a 31-year-old IT professional from Manchester, UK. She relocated from Kerala after her husband decided to relocate overseas. As an overseas daughter, she constantly worries about her elderly parents back home and struggles to find reliable, verified care support from abroad while managing her busy professional life. She needs peace of mind through real-time updates and trusted companion services for her parents.
Journey Mapping
This journey map highlights key user actions, pain points, emotional states, and service touchpoints for overseas caregivers from app discovery to post-companion feedback. The journey directly informed the onboarding flow, reminder logic, and language tone of the UI.
Hypothesis Development
Four Lean UX hypotheses were developed based on risk-prioritised assumptions: 1. Users will feel more confident with real-time check-ins. 2. Verified companion profiles will increase first-time bookings. 3. Users prefer 1-click SOS over filling emergency forms. 4. Families want language and cultural filters when selecting a caregiver.
Product Strategy
This canvas summarises the project's vision, early adopters, value proposition, unique features, and key metrics. It ensured design alignment with business goals while staying user-centred.
Design System
The visual design direction was built around: Calm, trustworthy colours (blue, lavender), Rounded typography for friendliness, Iconography prioritising clarity over stylistic flair. The system ensured UI consistency across screens while remaining accessible for elderly users.
Mid-Fidelity Wireframes
Wireframes showing the basic structure and layout of key screens including onboarding, dashboard, companion selection, and emergency features.
High Fidelity Wireframes - Part 1
Detailed wireframes with final design elements, showing the complete user interface for onboarding screens and home navigation.
High Fidelity Wireframes - Part 2
Additional high-fidelity wireframes showing companion booking, settings, and other core user flows with final design elements.
Usability Testing
A round of formative usability testing was conducted with 5 participants across two user groups: Overseas caregivers (Anita-type persona) and Elderly or semi-digital local users (Bindu-type persona). Test sessions used a 5-act interview format with scenarios: Booking a companion, Triggering an emergency alert, Navigating the home screen, Completing onboarding.
Hypothesis Validation
Testing and validation of the four key hypotheses developed earlier in the design process. Each hypothesis was measured against specific success criteria through user testing, analytics, and feedback collection to determine the effectiveness of our design decisions.
Hypothesis Validation – Success Score
Final validation results showed high success rates: 100% for emotional wellbeing and GPS location tracking, 85% for companion safety/trust and Malayalam language support. What worked: MVP addressed emotional, task-based, and safety needs. What needs scaling: Companion vetting system, offline service extensions, family dashboard with multi-user access.
