Page 420 - 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
price drops was particularly praised. Customers 6. Content Representation
reported feeling more empowered in their purchasing  Clarity and Detail: The content representation in the
decisions. app, including product details, specifications, and
price history, was generally well-received. Users
 Negative Feedback: Some users faced issues with price
appreciated the clear, concise comparison charts and the
discrepancies between different platforms. These
ability to view different offers side by side.
discrepancies were primarily due to delays in data
scraping or retailer-specific policies, which led to  Visual Appeal: The visual presentation of products was
occasional inaccuracies in the real-time price updates. crucial for engagement. Users preferred clear, high-
resolution images and videos over simple text-based
 User Experience: Feedback indicated that the app's content. Additionally, a visually appealing price history
user interface (UI) was intuitive, though certain users graph helped users easily identify trends.
suggested improvements in filtering and sorting
options for product searches.  Transparency: The app’s emphasis on transparency
regarding product specifications and retailer ratings
3. Improvement Areas earned positive feedback. However, some users
 Price Accuracy: Users recommended improving the suggested clearer information on shipping fees and
accuracy and speed of price updates, particularly for return policies.
products with frequent price fluctuations. Enhancing the
algorithm to account for region-specific differences 7. User Demographics
could help.  Age Group: The majority of users (60%) fell within the
18-35 age group, a demographic highly engaged in
 Feature Expansion: Adding features such as price
online shopping and more tech-savvy. This group also
forecasting, where users could predict future price
displayed a high level of comfort with AI-driven
trends based on historical data, would further enrich the
personalization features.
user experience.
 Gender: Both male and female users showed significant
 Retailer Integration: Some users suggested broader
engagement, though there was a higher engagement rate
integration with more e-commerce platforms to widen
from males in electronics and females in fashion and
the scope of comparison options.
beauty categories.
 Notification Settings: The notification system could be  Location: Urban dwellers (accounting for 75% of the
refined to ensure users receive timely alerts without user base) were more likely to adopt and engage with
being overwhelmed by too many notifications.
the system, reflecting the higher prevalence of online
4. Usage shopping in cities. Users from smaller towns and rural
 Frequency of Use: Users typically engaged with the app areas showed slower adoption, potentially due to limited
2-3 times a week, primarily for price comparisons or e-commerce access.
setting price drop alerts. However, high-involvement  Income Level: Users with a middle to high-income
products (like electronics) saw higher engagement level were more frequent users of the app. The system
rates compared to low-involvement products (like attracted users who had greater disposable income to
clothing).
spend on products and were more likely to benefit from
 Session Duration: On average, users spent around 5-7 price savings.
minutes per session. Users who set up personalized
Future Scope
alerts had longer engagement times, suggesting that
The Smart Comparison System (SCS) has shown significant
features that enhance personalization encourage more
promise in transforming the online shopping experience by
active use.
providing users with real-time price insights and
 Popular Categories: Electronics, mobile phones, and empowering them to make more informed decisions.
home appliances were the most searched and compared However, there are several areas for future growth,
categories, followed by fashion and beauty products. innovation, and development that could further enhance its
capabilities and expand its reach. Below are key avenues for
5. Impact the future scope:
 Consumer Empowerment: The system's most
significant impact was on consumer empowerment. 1. Enhanced Price Prediction and Forecasting
Users reported feeling more confident in their  Price Trend Analysis: One of the most promising future
purchasing decisions due to increased transparency in advancements would be to integrate price forecasting
pricing and access to comprehensive price histories. algorithms that predict future price trends based on
historical data, seasonality, demand fluctuations, and
 Price Sensitivity: There was a noticeable increase in sales patterns. This will allow users to plan their
price sensitivity among users. Consumers became more
purchases more strategically, potentially saving even
aware of price fluctuations, and many shifted their
more money.
purchasing decisions based on the insights gained
through the app.  AI-Driven Predictive Insights: By employing machine
learning models, the app could not only compare
 Retailer Response: E-commerce platforms began
current prices but also suggest the best time to purchase
adapting to the increased competition brought about by
based on historical price drops, upcoming sales, and
real-time price comparisons. Some retailers began to
predicted future trends.
lower prices or introduce new discounts to stay
competitive.
IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 410