Le Fleuriste

Flower catalogue & flower shopping app

Le Fleuriste project main image

BedtimeStories is an iOS app that lets parents easily create personalized bedtime stories for their children. Using OpenAI's API for story content and DALL-E for illustrations, the app offers a simple prompt or detailed template for story creation. All stories are saved within the app, making bedtime a magical storytelling adventure.

Project status: In progress

- UI/UX Design: In Figma.

Wireframes finished, Mockups in second round of improvements.

- Development: Xcode with SwiftUI.

The prototype is finished, it includes a successful network connection to the OpenAI API to get the story text and image. The stories are persisted using CoreData and displayed on their dedicated view, where users access , favourite and delete their stories.

Project details

Le Fleuriste is a project created as part of the Google UX Design Certificate. This app allows users to search through the catalog of a flower shop. Users can also select their favorite bouquet and place it in an order for pick-up at the store.

Project type
UI/UX design | Google certificate
My role
UX researcher & UI/UX designer
Tools
Figma
Date
January 2022

Project prompt

Design a flower catalogue for a florist in Paris.

I received this project prompt as the first project of the Google UX Designer certificate. I designed a catalog app and included a flower shopping functionality.
I included that functionality because, during the first round of interviews, most users mentioned they wanted a catalog app that also allowed them to buy flowers. I decided to use their feedback as a design exercise and also design a flow for flower shopping.

The problem

The flower shop has a voluminous binder with bouquet photos that they use as a flower catalog. Clients feel overwhelmed by the size of the binder and frustrated because they cannot easily see all the bouquets.

The goal

Catalog: Design a mobile app that allows users easily search for a bouquet in the catalog and filter by their preferences.
Flower shopping: Design a flow that allows clients to place an order for pick-up in-store.

Understanding the user

First, I conducted a round of remote interviews. The main goal of these interviews was to understand how, when, and why users search for a bouquet. I also asked them about their experience buying flower bouquets online/mobile and in-store.

User personas

1. Aniya

1. Émilie

1. Ryan

Problem statement: Émilie is a retired person who needs a catalog app where she can easily find new bouquets because she feels frustrated when she cannot easily find a flower bouquet in the physical catalog.

User persona 1 image

2. Ansel

2. Megan

Problem statement: Ansel is a busy IT engineer who needs an app that allows him to easily find and buy bouquets because he has not enough time to look at the physical catalog in the flower shop.

User persona 2 image

User journey map

Through Émilie’s journey map I found out that when a design takes users with disabilities into account, other users can also benefit.

User journey map image

Starting design

Paper wireframes

No items found.

Low-fidelity prototype

The main flow allows users to search or select a suggested bouquet, see its information and details, add to bag, pay and place it for pick up at the flower shop.

Lo-Fi prototype
No items found.


Usability studies: findings

I performed remotely two rounds of moderated usability studies. The first round was with the low-fidelity prototype that most participants found difficult to use since most elements were not interactive. Then a second round with the high-fidelity prototype where users found the app intuitive and liked the design.

Round 1 findings
Round 2 findings
One
Participants found the prototype not interactive enough.
One
Participants found the prototype intuitive.
Two
Text size was too small for the participant with low vision.
Two
Participants need a help/support option.
Three
Payment process confusing for all participants.
Three
CTA button hidden behind nav. bar in some screens.
Round 1 findings
Round 2 findings
One
Participants found the note-taking flow easy to use.
One
Participants mentioned they see themselves using the note-taking system.
Two
Toolbar icons were too small to identify and participants felt confused.
Two
Toolbar improved from feedback, and participants understood clearly the functionality of the icons.
Round 1 findings
Round 2 findings
One
Participants found the note-taking flow easy to use.
One
Participants mentioned they see themselves using the note-taking system.
Two
Toolbar icons were too small to identify and participants felt confused.
Two
Toolbar improved from feedback, and participants understood clearly the functionality of the icons.
Round 1 findings
Round 2 findings
One
Most participants found that a weekly meal planner is needed.
One
Participants found useful that they now can alternate planners.
Two
Participants had a hard time adding recipes to the shopping list
Two
Add to shopping list button added, now it's clear for users how to create a shopping list.
Round 1 findings
Round 2 findings
One
Participants found the note-taking flow easy to use.
One
Participants mentioned they see themselves using the note-taking system.
Two
Toolbar icons were too small to identify and participants felt confused.
Two
Toolbar improved from feedback, and participants understood clearly the functionality of the icons.

Prototype

Development status

The demo presented below has been developed using SwiftUI. Currently, I am focusing on enhancing error handling and improving user notifications. The UI will be updated once the mockups are finalized.

Functionality:
The app offers two distinct modes for creating a story:

1. Template Mode: In this guided mode, users fill in the fields and select buttons to create a story that is more specific to what children might enjoy.
2. Quick  Mode: Users can enter a quick prompt to generate a story on the fly.

Powered by AI technology, this app crafts unique bedtime stories, complete with illustrations, specifically tailored for each child.

App back-end process:

1. Network Call: Upon receiving user input, a network call is made to OpenAI’s API.
2. Story Generation: The API response includes a detailed bedtime story text and an accompanying image generated using the DALL-E model.
3. Data Persistence: The  story is saved using CoreData and the image is stored in the Documents Directory.
4. Stories Management: Users can view, favorite, or delete their stories as needed.

Refining the design

Mockups

No items found.
No items found.
No items found.

High-fidelity prototype

Hi-Fi prototype


Accesibility considerations

One
Contrast
Two
Headings
Three
Typefaces
I used contrast checking tools to make sure that the contrast between background, font and images was high.
Different font sizes were used to for main heading and sub-headings.
Only two basic typefaces were use in all the designs, being Helvetica regular and bold the main font.
One
CTA Buttons
Two
Element Labels
Three
On boarding
Call to action buttons have a high contrast color.
Meal plans and onboarding include images and text..
A detailed onboarding process with images and text

Going Forward

Impact

Participants of the research study described their User Experience with Le Fleuriste app as intuitive and easy to use. They liked the UI design and praised that the touch of color in the app is through the bouquets and not in the app elements.

What I learned

During this project, I learned the design process of a mobile app. I learned how to use Figma and the basics of UI design. I also learned the importance of user feedback through usability studies during the design process.