Comfort map

Lun misto comfort map is a map that helps users to find their dream neighbourhood for living, based on personalised criteria. Lun misto is an R&D project focused on researching urban comfort criteria and displaying them on the map, like price statistics, noise level, heat maps, level of greenery, air quality, kindergarten queues.

Goals

to raise acquisition and engagement, amount of read articles and build community.

My role

growth design, ux Research, ui design, design system, product strategy

barrier-free design

Universal Design is a priority in the field of architecture in Ukraine. Lun Misto team created the map City without barriers.

+60%

in csat

first lady initiative

Lun also joined the initiative of First Lady Olena Zelenska "Business without barriers".

+17%

in conversion rates

Discovery

As Kyiv ranked first in global air pollution in 2020, our aim was to provide clear, accessible air quality data to help residents protect their health.

Research

We conducted a series of Product Strategy workshops to align product growth with marketing. As a result, I defined key Personas, created a Value Proposition Canvas, mapped the User Journey and analyzed User Flows and Mental Models from well-known services to design an intuitive and friction-free interface.

Hypothesis

Creating an interactive, minimalistic map that highlights areas of urban comfort based on universal design, health, safety, transportation, and education criteria will help residents of Kyiv to make confident decisions of neighbourhood of their dream. Displaying only positively rated comfort indicators will increase user engagement, since people tend to ignore poorly rated areas. Allowing users to search by specific streets will improve discoverability and relevance of comfort information.

Development

Design System: I developed new dark design system (UI components and OSM map styles) to improve experience during prolonged neighborhood comparison and article reading. Comfort scale: we created a comfort gradient for personalized maps, based on user-selected criteria. Users can also explore individual layers and research behind them. Onboarding: we simplified the user's experience by guiding them through complex data within the interface and providing clear instructions for sensor installation.

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