Welcome to 1Search!
Project by: Vidit Patel, Jeffrey Chan, Meenal Saxena, Nimeesha Nidadavolu, Jinyang LI, and Litong Lu
How to use the product: *IMPORTANT: Checkout jeff branch on GitHub.
1. Download all files from GitHub: https://github.com/nnidadavolu4/1Search.git
2. Download Node.js and select the compaDble version: https://nodejs.org/en/download/
3. Click on the downloaded file to install. The following screen will pop up:
4. Continue with the installaDon wizard
5. Make sure /usr/local/bin is in your $PATH.
6. Open the server folder in the terminal and run the command: node install (windows) or npm install (mac)
7. Use the Git command: git checkout jeff
8. Run index.js in the server file using the command: node index.js
9. Find index.html and open on live server
10. Enjoy!
Introduction to our project
What problem are we solving?
The advancements in direct-to-consumer (DTC) technology have resulted in the women’s fashion market to increase at an exponential rate. Based on the findings presented by Statista, the compound annual growth rate in women’s clothing is tipped to reach 3.43% between 2022 and 2026. Currently, the revenue in the Women's Apparel segment amounts to US$888,578m, which per person equates to revenues of US$116.73 (Statista, 2022). Furthermore, the volume in the Women's Apparel segment is approximately 81,203.74m pcs, with a predicated volume growth of 3.8% in 2023. Hence, this study clearly indicates that the women’s clothing sector is heavily saturated, and consumers have millions of options to choose for. Consequently, the time spent searching for clothing items which fit the correct body size and details of clothing also increases significantly. Online shopping for women’s clothing is a simple process with one major drawback – finding a desired clothing item which is the correct size. On average, women spend 2.05 hours online looking for a fashion item which is the matches their needs and is the correct size (Statista, 2022). As the volume of supply in the fashion industry increases, so will the time spent searching online. This is a problem which can be solved by using automated algorithms and web scraping, however, no major action has been taken till now.
What is our solution?
1Search is a cost-effective and scalable system which seeks to minimise the time spent by women searching for fashion items online. By independently srcaping data from thousands of clothing websites, the 1Search algorithm can generate a plethora of options which meet the requirements of the consumer, ie, body size, colour, price, etc. This in-turn will prevent the consumer from having to go through each website individually and trying to find a particular item which fits perfectly.
The technology we used?
The technology used to develop the algorithms and web structure of 1Search include: JavaScript, HTML, CSS, and Node.js. The libraries used are: Selenium (Node.js) Express (web server) Body-parser (middleware)
Challenges we ran into?
The foremost challenge this iteration of our product is the payment integration system. Currently, there is no method in place which will allow the consumer to purchase all the clothing items directly from our website and ensure that they arrive at the same time. This is due to the fact that different business have different protocols and methods for delivery, hence, the shipment from across all brands is not guaranteed to arrive at the same time.
What's next for 1Search?
We will be looking to collaborate with the different brands and create a model which will ensure that the consumer can order all the products from our website, and the shipment from all brands are collected and processed together from a shipment facility. Furthermore, we will be looking to integrate more brands into our system, and thereby, scale rapidly.
Checkout out 1Search in action!