Page 553 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
1. User Registration and Profiles
The system starts with a seamless onboarding process, allowing users to create accounts and manage profiles. It stores user
preferences and purchase histories for better customization.
2. Product Search and Aggregation
Users can browse a wide range of products from multiple online retailers. The system consolidates product specifications,
reviews, ratings, and prices, enabling a side-by-side comparison.
3. Real-Time Price Monitoring
The system continuously tracks price updates and notifies users of discounts, price drops, and flash sales. This ensures that
users get the best deals without spending excessive time searching.
4. Historical Price Analysis
Graphical representations of price trends help users make better decisions by identifying the most cost-effective time to
purchase. This feature forecasts seasonal price patterns to aid planning.
5. User-Friendly Interface
The intuitive design provides filtering options for price range, product category, and brand preferences. Whether accessed via
desktop or mobile, the system ensures smooth navigation.
6. Secure Payment Gateway
Multiple payment methods, including digital wallets and UPI, make transactions secure and hassle-free.
7. Personalized Recommendations
By using machine learning algorithms, the system delivers tailored product s suggestions based on user behavior, preferences,
and browsing history.
4. METHODOLOGY:
1. The first step of price tracking involves scanning a website for product details such as title, price, and stock information.
Some price trackers also gather additional information like reviews and photos.
2. In the second stage, web scraping is used to find the best prices. The price tracker keeps track of product information while
scraping prices and ranking websites accordingly.
3. The necessary operations, including obtaining HTML, locating the price element, and extracting the price from the beautiful
soup object, are performed.
4. The user is notified via email when the price is extracted with the help of the price-parser library. The user can view this
data on a dashboard or in a list format.
5. Although dynamically generated websites, which rely on JavaScript, are more challenging to scan than static HTML pages,
some price trackers still struggle with this task.
The implementation focuses on developing a robust, efficient, and scalable price comparison system. Below are the core
components of the system:
· Data Collection:
 Product data is aggregated using APIs and web scraping techniques from trusted online retailers.
 The collected information includes details such as price, stock availability, and user reviews.
· Data Storage and Management:
 A centralized database is utilized to ensure secure and efficient handling of product details.
 Optimized storage solutions enable quick data retrieval for large-scale comparisons.
· Price Comparison Algorithm:
 The algorithm matches identical products across retailers using unique identifiers and specifications.
 Advanced techniques ensure accurate comparisons even for varying product descriptions.
· User Interface Design:
 An intuitive and user-friendly interface is created with advanced filtering options.
 Consumers can easily search, sort, and compare products based on their preferences.
5. EVALUATION AND RESULTS:
The proposed system is a Real-Time Search Engine where users will find best products among multiple ecommerce websites. It
will reduce time and money wasted in manual filtering and will provide customers a better shopping experience. Moreover, it
will also help ecommerce companies to identify price errors on their website and help provide better service to customer.
It will be automated, user-friendly and easy to use. The system uses highly efficient and focused dynamic web crawlers which
will filter out products at first level based on the predefined set of parameters integrated into the system. The scraped products
will pass through dynamic pricing algorithm where each product will be ranked accordingly. Filtration process during these
stages will be highly rigorous and this will result in availability of best products to the customers.
Initial testing of the platform yielded promising results:
 User Satisfaction: Over 90% of participants reported improved shopping experiences due to accurate price comparisons
and relevant recommendations.

IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 543