First, run the development server:
bash npm run dev
yarn dev
npm dev
markdown
- Mohd Dilshad (Leader)
- Mohd Aftab
- Prakash Singh Rawat
- Aman Singh
The ShopSmart Analyzer is a groundbreaking project designed to revolutionize the e-commerce experience by addressing common challenges faced by both buyers and sellers. With a focus on catalog quality assessment, this innovative solution employs a sophisticated scoring mechanism to evaluate products objectively.
The ShopSmart Analyzer solves several key challenges in the e-commerce landscape, enhancing user experiences and making various tasks more efficient:
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Streamlined Product Evaluation:
- Problem: Buyers often face challenges in assessing the quality of products due to incomplete information or inaccurate details in catalogs.
- Solution: ShopSmart Analyzer streamlines product evaluation by providing a comprehensive rating-based system, empowering users to make informed purchasing decisions.
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Trustworthy Catalogs:
- Problem: Buyers encounter issues with untrustworthy catalogs, including missing images, pricing discrepancies, and inaccurate product details.
- Solution: The project ensures catalog transparency by evaluating compliance, correctness, and completeness, fostering trust in the displayed product information.
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Time-Saving Decision-Making:
- Problem: The sheer volume of items in e-commerce catalogs makes manual examination impractical, consuming time and effort.
- Solution: ShopSmart Analyzer automates the catalog quality assessment process, saving users valuable time and ensuring a quicker decision-making process.
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Objective Standardization:
- Problem: Existing solutions are often limited, and manual examination remains the primary recourse for catalog evaluation.
- Solution: The project introduces an objective scoring mechanism, setting a standardized and granular assessment for catalog quality, reducing reliance on manual methods.
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Diverse Requirement Fulfillment:
- Problem: In an open network, buyers have varied requirements concerning catalog quality, such as compliance with laws, branding correctness, and completeness in conveying product features.
- Solution: ShopSmart Analyzer accommodates diverse requirements by considering various parameters and weights, ensuring catalogs align with specific user expectations.
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Enhanced Seller Accountability:
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Problem: Sellers may lack direct connections with buyers for due diligence, and traditional assessment methods become unfeasible.
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Solution: The project promotes seller accountability by providing an objective standard, encouraging sellers to maintain high-quality catalogs for a positive buyer experience.
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Overall, ShopSmart Analyzer makes the process of evaluating and selecting products online more transparent, efficient, and user-friendly, contributing to a trustworthy and enjoyable e-commerce experience.
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For a detailed overview of our project, please check out our PowerPoint Presentation
We have built ShopSmart Analyser using a diverse tech stack, including:
- HTML
- Tailwind CSS
- JavaScript
- Node.js
- Next.js
- Flask API
- Machine Learning
- Artificial intelligence
- Python
- Firestore
ShopSmart Analyser:
Table:
Charts:
Open http://localhost:3000 with your browser to see the result.
You can start editing the page by modifying pages/index.js. The page auto-updates as you edit the file.
API routes can be accessed on http://localhost:3000/api/hello. This endpoint can be edited in pages/api/hello.js.
The pages/api directory is mapped to /api/*. Files in this directory are treated as API routes instead of React pages.
This project uses next/font to automatically optimize and load Inter, a custom Google Font.
To learn more about Next.js, take a look at the following resources:
- Next.js Documentation - learn about Next.js features and API.
- Learn Next.js - an interactive Next.js tutorial.