Lightbulb is a concept for a business insights platform that uses machine learning to generate business suggestions based on sales data and customer history.
I tasked myself with designing the pages of the dashboard and creating a high-fidelity, interactive prototype.
Product Design
Me
Figma
August 2023
Product Design
Me
Figma
August 2023
Today, machine learning models are used by major companies to understand data trends and generate business insights. Existing platforms are expensive and take significant time to customize and understand. Small business owners currently don't have the time or resources to use these new tools to benefit their businesses.
I set out to design a responsive web application that allows business owners to easily view and comprehend business insights using their existing sales and customer data. The application is meant to provide access to technology that can help businesses improve their operations without requiring significant time or capital.
I began by writing a high-level overview of the product. Next, I identified key objectives, user scenarios, and feature requirements.
1. Generate suggestions based on business data
2. Allow businesses to track key success metrics
3. Allow businesses to view and manage customers
1. View key success metrics on a dashboard
2. View customer history and preferences
3. View suggestions based on machine learning
From the user scenario identified in the product requirements document, I developed the user persona for a small business owner.
Mia Chambers is the owner of a retail clothing store in Chicago, IL. Mia is passionate about growing her business. She wants to find solutions to increase revenue, but doesn't have time to learn complex tools or resources to purchase high-cost products.
Next I sketched a wireframe of the web application, identifying key page content and navigation based on the requirements.
I then took the completed wireframe and began designing the flows in Figma. Once I established the key components on each page, I created a fully interactive prototype.
While designing the initial layouts, I established essential page elements and created repeatable components. I also selected a series of colors to use across the application.
The home dashboard highlights key information including top insights, key metrics and recent customers.
The insights page provides all of the suggestions generated by the machine learning model. Viewing the details of each insight shows the key metrics impacting the model.
The key metrics page shows the most important metrics for the business and provides feedback based on trends in the data.
The customers page shows aggregate data as well as customers with recent purchases. You can view the customer details to see specific information about each customer to allow for improved targeting and experiences.
The result is a fully responsive prototype of the web application which met all of the identified requirements. The application allows users to receive business suggestions generated by the machine learning model, track key metrics impacting the suggestions, and view helpful customer data.
This project was a great end-to-end skill-building activity from identifying requirements to creating a high-fidelity prototype. The result was a viable product concept with the primary .
