F3 dApp

The web 3.0 landscape is growing at a lightning speed and has already started creating an influence with some innovative products in categories including GameFi, DeFi, NFT, Metaverse, and many more. The table below provides a high-level understanding of some incredibly successful web 3.0 projects.

Projects	Category	Success Parameters
Axie Infinity	GameFi	Total Sales Volume Exceeding $4.07 Billion as of April 30, 2022.
Aave	DeFi	Total Value Locked in the protocol is $5.26 Billion as of June 28, 2022.
PancakeSwap	DeFi	Total Value Locked in the protocol is $2.3 Billion as of July 3, 2022.
Bored Ape Yacht Club (BAYC)	NFT	Total Volume Traded is 623.3K ETH (OpenSea) as of June 30, 2022.
Decentraland	Metaverse	Monthly Active User Base of 300,000 people (approx.) and 18,000 daily users (approx.)
Sandbox	Metaverse	More than 2 million Registered Users as of March 23, 2022.

While the web 3.0 landscape is rapidly growing with more and more products adopting decentralized architecture in the business model driven by cryptocurrency, there is still an important element missing in this landscape- establishing trust and confidence amongst the consumers who desire to interact with the web 3.0 products.

Consumers currently immerse themselves into NFT projects or DAO without knowing much about the experiences of the users who have already made a transaction with the project. As a result, many consumers making a fresh entry in the project end up having a bad experience, sometimes even losing funds by incurring losses.

The best probable solution, in this case, is checking out the reviews shared by consumers to know about the product before getting involved with it. However, there is a significant problem associated with the reviews- “Most of them are fake”.

Have a look at some key findings from the renowned publications in the table below to understand the situation better:

Publications	Key Findings	Reference
Fake online reviews cost $152 billion a year. Here's how e-commerce sites can stop them	“Fake online reviews influence $791 billion of e-commerce spending annually in the US, $6.4 billion in Japan, $5 billion in the UK, $2.3 billion in Canada and $900 million in Australia.”	World Economic Forum
Almost 4% of all online reviews are fake. Their impact is costing us $152 billion	“Using official figures and self-reporting by the world’s leading e-commerce sites (including Trip Advisor, Yelp, TrustPilot and Amazon) on average we find that 4% of all online reviews are fake.”	ThePrint
Fake reviews problem is much worse than people know	“The scale of the fake reviews problem is not precisely documented, but it’s “in the millions” across sites, according to Curtis Boyd”	Search Engine Land
FTC Fines Company $12.8 Million for Fake Amazon Reviews	“A recent $12.8 million suit the FTC brought against an Amazon retailer is a reminder than fake reviews cost more than they are worth in the long run.”	Inc.

In the year 2019, Amazon spent more than $500 million and hired 8000+ workers to remove the fake reviews and protect the platform from abuse. As a matter of fact, the eCommerce giant was able to remove 40% of counterfeit reviews but it would take more than 100 days to scrub off the fake review once posted. This timeframe is sufficient for the sellers to benefit from the short-term sales pump and is also long enough for the customers to get tricked.

Not only this operation turned out to be expensive but also was not effective enough to kill the problem.

Why fake reviews are so common? It is because there is no way to verify or authenticate whether the individual sharing the feedback actually bought the product or used the service.

For this purpose, the team at Feed3 will be developing an F3 dAPP (Decentralized Application) to allow hosting reviews exclusively for web 3.0-based games, applications, brands, and experiences that will be verified by Freeda and authenticated by blockchain technology.

Since all the transactions executed on top of a blockchain network are public and immutable, it will be easy for dApp to verify a wallet’s web 3.0 purchases. Once a user will connect his or her decentralized wallet to the dApp, the system will scan the transactions executed through it.

After authenticating the purchase transaction, then only the user will be able to drop the review or feedback in favor of goods and services bought. Unlike traditional markets, dApp will be able to confirm if the transaction actually happened or not.

Also, it doesn’t matter whether the transaction was executed over a public dApp like OpenSea or LooksRare or through a private DM Exchange because the dApp will be able to scan the wallet in either of these circumstances.

In this way, the reviews from only those individuals will float on the platform who have made a purchase transaction in the web 3.0 economy. On top of that, the F3 dApp will also observe adding a limitation that will prevent immediate posting of the review. The individuals will have to fulfill the minimum waiting period before their evaluation is made live on the platform.

We felt the need to build this decentralized application because the existing platforms hosting reviews and customer feedback do not promise authenticity and don’t have a solid infrastructure that prevents review bombing. Building this platform is an important initiative to help the users make informed and confident decisions before executing a purchase transaction in the web 3.0 economy.

F3 dApp will also eliminate the second problem in the review industry- Bias. According to Harvard Business Review, "research shows many of today's most popular online review platforms — including Yelp business reviews, and Amazon product reviews — have a distribution of opinion that is highly polarized, with many extreme positive and/or negative reviews, and few moderate opinions."

Those with in-between experiences do not have an incentive to share their thoughts. The product has not changed their life, nor has it massively troubled them. Feed3 aims to reward users who provide quality analysis of their experiences. The FD3 tokens will allow us to do so, allocating tokens to those who voice or write thought-out reviews and bonuses for videos or pictures explaining their thoughts.