01.

Digital Neighborhoods
Digital Neighborhoods
Digital Neighborhoods

I designed a data-driven platform for municipalities, translating complex financial and consumption data into intuitive dashboards, visualizations, and user flows.

SIBS manages a vast amount of transactional and consumption data across its financial network. The challenge was to turn this complex dataset into meaningful insights that could help municipalities and businesses better understand local economic activity.

Digital Neighborhoods project preview
3D close up detail
Mobile app design

02.

Context

Context
Context

Digital Neighborhoods was created as a data-visualization platform that brings together indicators such as consumption, transactions, visitor activity, and geographic trends. The main goal was to make complex information easier to explore, compare, and use for real time decision making.

01.

Client

SIBS

01.

Client

SIBS

02.

Services

App design

02.

Services

App design

03.

Date

2022

03.

Date

2022

04.

Industry

Fintech

04.

Industry

Fintech

03.

Project Goal

Project Goal
Project Goal

What stood out most was his ability to bring structure to ambiguity. Even when the scope was messy, he created a thoughtful UX direction that helped the team move faster and with more confidence.

Solution

Solution
Solution

Transform SIBS’ extensive data into a product that makes local economic activity easier to understand, explore, and act upon. Digital Neighborhoods brings together economic indicators, geographic data, and consumer insights to help municipalities identify patterns and make informed decisions.

My role

My role
My role

Product Designer & UX / UI

Team

Team

Product manager, product owner, key users, dev team and tester.

  1. Framing the

    problem

  1. Framing
    the problem
  1. Framing the
    problem

Starting by research

I began by exploring how different types of data can be visualized within a digital product. I researched chart types, their purposes, and the kinds of information they can communicate effectively.

The goal was to understand which visualizations best fit the data, the user’s needs, and the decisions they needed to make.

Framing the problem illustration
Framing the problem illustration

Understanding user needs.


Alongside the product owner, I conducted workshops and interviews to understand how users would use the platform and what information they needed to make better decisions.


Key needs identified:

  • Understand the evolution of a municipality’s economic profile and consumption patterns, including where consumers come from.

  • Monitor consumer loyalty by comparing local consumption with activity in other areas.

  • Identify the main local economic sectors and understand consumers’ shopping behaviour.

  • Track the evolution of different sales channels, including digital channels and marketplaces.


Defining the target.

  1. Age: 25–60

  2. Occupation: City hall professionals

  3. Area: Financial management

  4. Experience: Familiar with data visualization

  5. Primary goal: Monitor the local economy

  6. Key focus: Analyze consumption within the municipality

  7. Additional need: Measure the economic impact and regional return of events, such as Christmas.

Defining the target case study image

2. Deciding what to build

2. Deciding what to build
2. Deciding what to build

Turning insights into a clear product direction. Based on the insights gathered from users, we defined the product specifications, key screens, and the role of each dashboard. I mapped the user flow to understand how users would navigate between dashboards and how each one could tell a clear data story, helping them interpret complex information and make data-driven decisions. With the structure defined, I moved into wireframing to explore and validate the solution with key users.

Building the interface.

Defining the interactions behind the dashboard.

A key part of the design was defining the filters for each screen, allowing users to explore the data by time period, day of the week, metrics, sector, geography, and specific cards. These filters directly shape the dashboard and dynamically update the charts based on the user’s selection.

KPIs provide the next layer of information, giving users an immediate view of key business indicators such as total transactions and visitor numbers. They help users quickly understand performance before exploring the data in greater detail.

Building the interface.


Defining the interactions behind the dashboard.

A key part of the design was defining the filters for each screen, allowing users to explore the data by time period, day of the week, metrics, sector, geography, and specific cards. These filters directly shape the dashboard and dynamically update the charts based on the user’s selection.

KPIs provide the next layer of information, giving users an immediate view of key business indicators such as total transactions and visitor numbers. They help users quickly understand performance before exploring the data in greater detail.

Building the interface.


Defining the interactions behind the dashboard.

A key part of the design was defining the filters for each screen, allowing users to explore the data by time period, day of the week, metrics, sector, geography, and specific cards. These filters directly shape the dashboard and dynamically update the charts based on the user’s selection.

KPIs provide the next layer of information, giving users an immediate view of key business indicators such as total transactions and visitor numbers. They help users quickly understand performance before exploring the data in greater detail.

  1. Visua Identity

  1. Visua Identity
  1. Visua Identity

Design system.


After reviewing the wireframes with users, I moved into the visual design phase and defined the product’s design system.

The direction was intentionally clean and restrained, keeping the interface focused on the data rather than competing with it. The visual language needed to make complex information easy to scan, interpret, and compare.

The existing brand guidelines established a palette of blues and neutrals, which provided the foundation for the interface. However, data visualization required a broader range of colors to clearly differentiate datasets and communicate meaning. I extended the palette with carefully selected beige and green tones, keeping the visual language cohesive while giving the charts enough contrast and flexibility.

Logo design.


As part of the project, I was also responsible for creating the product name and visual identity. I explored existing visual references combining geographical elements, data, and analytics, looking for a direction that could represent both sides of the product.

The concept evolved around the ideas of “neighborhoods” and “digital”, translating the purpose of the platform into a simple and recognisable visual mark. As the product was powered by SIBS Analytics, I also kept the identity aligned with its clean visual language, lines, and colour palette.

The final logo brings together the two core ideas behind the product: geography and financial data. The location pin represents the geographical dimension, while the chart inside it reflects the platform’s role in turning financial data into clear, actionable insights for local economies. Turning local data into clear insights.

  1. Prototype

  1. Prototype
  1. Prototype

I created a high-fidelity prototype in Figma to bring the proposed product to life and demonstrate the complete user experience and interface.

The prototype focused on validating the navigation, interactions, and overall flow, ensuring users could move through the platform intuitively and understand how the different dashboards and data visualizations work together.

  1. Learnings

  1. Learnings
  1. Learnings

This project deepened my understanding of the financial sector and the complexity of working with large volumes of data.

I learned that data visualization is not simply about presenting information, it is about making complex data easier to understand and turning it into actionable insights. Effective visualizations can help users track KPIs, identify trends, compare performance, and ultimately make more data driven decisions.

The project also strengthened my research process and my ability to translate user needs into clear product and visualization decisions.

Understanding the data is only the beginning. The real value comes from making it meaningful to the people who use it.