FingeRate Whitepaper v4.0
  • 🇹🇻FingeRate Whitepaper v4
  • 1. ABSTRACT
  • 2. Project Background
    • 2.1 Market Overview
    • 2.2 Limitations of current consumer satisfaction survey systems
    • 2.3 Solution
  • 3. FingeRate Services
    • 3.1 Vision
    • 3.2 FingeRate Bot (Touchless survey kiosk)
    • 3.3 FingeRate App
      • 3.3.1 What is FingeRate App?
      • 3.3.2 What is S2E?
      • 3.3.3 Potential Users
      • 3.3.4 App User Flow
    • 3.4 Offline to Online
    • 3.6 Other Services
      • 3.6.1 Pass&Go
      • 3.6.2 PCL FREE PASS
      • 3.6.3 2022 Seoul SIGNIS World Congress in Metaverse
  • 4. Tokenomy & Ecosystem
    • 4.1 FingeRate Ecosystem
    • 4.2 Tokens and Mileage unit
      • 4.2.1 MSOT ERC-20 Token
      • 4.2.2 SoM (SoT Mileage) App Mileage
      • 4.2.3 SOT NFT ERC-721 Token
  • 5. Technology
    • 5.1 Smart Contract based FingeRate Protocol
      • 5.1.1 ERC-721 VIRTUAL BOT NFT Smart Contract
      • 5.1.2 ERC-20 MSOT Smart Contract
      • 5.1.3 Profit Distribution Smart Contract
    • 5.2 FingeRate Server Nodes
    • 5.3 Real-Time User Interface (FingeRate App)
  • 6. Roadmap
  • 7. FingeRate Team
    • 7.1 Founders & Lead Team
    • 7.2 International Advisory Board
    • 7.3 Local Advisors
  • 8. Disclaimer
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  1. 2. Project Background

2.1 Market Overview

With rapid development of e-commerce, online shopping & services has become an established part of consumers’ daily routines. The impacts of the growth of online market are no longer limited to the online commerce industry, but also having a massive impact on offline market as well. Consumers now can purchase almost any goods or services from online, leading more and more consumers to generate and rely on reviews and ratings.

Ratings and reviews have become increasingly available and influential in consumers purchasing decisions. As businesses have recognized the power of consumer reviews to shape consumer purchasing behavior, they are more vigorously engaging in developing marketing practices based on consumer reviews. For instance, Amazon, the world’s largest online retailer, introduced “Amazon 4-star”—an offline store including products that are rated 4 stars and above on its online platform, and many Korean companies are also actively utilizing consumer ratings and reviews to optimize their marketing strategies. Consumer reviews and ratings have positive impacts for businesses, allowing them to continuously develop and improve their products.

While both consumers and sellers are benefiting from consumer reviews and ratings, a range of risks and challenges are also voiced. The prevalence of misleading and deceptive practices such as fake and incentivized reviews have significantly damaged the authenticity and impartiality of consumer rating system. With disparate systems and applications for data collection, the challenges arise in accessing and collecting a wide range of data on random individuals as well as creating a uniform consumer data set and conducting comprehensive data analyses. Furthermore, the development of platforms to share the offline experiences is far behind than those for online reviews.

Due to the current influx of interest and massive developments happening around the concept of metaverse, this debates over data collection and security get more intense than before. With the transition towards the web 3.0 era of the internet, we will see a wider variety of goods or services that never existed before. Therefore, there are increasing needs for developing an integrated platform to conduct on and offline consumer satisfaction surveys, collect and share actual consumption information, construct reliable consumer dataset, carry out comprehensive data analyses and ensure security of the personal data of the users by using cutting-edge blockchain technology.

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Last updated 2 years ago