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Review.Network Market Research and User Reviews Case Studies

Review.Network Market Research and User Reviews Case Studies

Review.Network’s goal is to improve the communication between brands and consumers. Our goal is to help people improve the products they use and love, and reward them for expressing their opinions. At the same time, companies are always looking for ways of tapping into their customers’ minds, be it to research a new market or to learn how people perceive the existing offerings.

Review.Network will be bringing change to two industries ­ Market Research & Reviews.

Market Research

Market research is an essential component for companies all over the globe to develop business strategies. They gather information about target markets or customers in order to detect market trends, choose better pricing of goods and services and conduct risk and opportunity analysis. Review.Network focuses on primary market research, which does not use any information already available on existing sources. This kind of field research is usually designed from scratch, is tailor made and aims to answer both quantitative and qualitative questions.

The market research industry exceeded 44 billion U.S. dollars in revenues in 2015 ( link ), and is expected to grow to 65 billion U.S. dollars by
2020 ( link ).

There are many challenges that currently exist for market research companies, specifically, slow adoption in utilization of the latest technologies, which hampers targeting, gathering and analysis of information. This often results in low response rates and hurdles in maintaining data privacy and security.

Review.Network focuses on creating a high quality, global mechanism for market research in a completely new way ­ by decentralizing the research process, as well as employing tools such as AI analysis to offer better insights to companies. This means empowering both business and people to participate in a secure and private exchange of information, while relying on blockchain’s transparency and guaranteed validity of implemented processes. A very important part of Review.Network’s solution is the token economy, which allows us to design such a system where businesses directly reward people for their answers. This increases the response rates and makes the system fair to both sides, establishing a community always looking to participate and provide precious data.

In order to implement its solutions in the real world, Review.Network partnered up with a global payment processing company, PayXpert. PayXpert provides its customers with a payment gateway, used by online and offline retailers alike. The goal of this partnership is to bring a new, revolutionary type of shopping experience that will help both brands and consumers.

Imagine completing a purchase of an amazing pair of jeans, and upon checkout, getting prompted to fill out a short survey about your purchase. By filling out the survey, you are helping the brand improve the products you love. But this nice feeling is not the only reward ­ you will also get REW tokens, directly from the brand, rewarding you for your opinions, to ultimately improve your overall experience with the brand’s offering.

On the company side of things, this mechanism gives them unprecedented insight into what customers think and how they feel about their products. This valuable information can help them create and tweak products and services to fit their customers’ needs, making the market truly customer­centric.

B2C is not the only side of our business. Review.Network’s market research protocol also allows for C2C research. Going back to the example of shopping for those perfect jeans, imagine you’re also trying other outfits, and can’t decide which combination looks best on you. What you could do is fire up the an app, snap pictures of each outfit, and create a “live survey” to get some answers. You’d choose who you want to answer your questions, by using the demographic filtering option. You might choose to target people that live in your country, that are in your age group, and drill down even further if wanted. To run the live survey, you would also choose the payout in REW that will be rewarded to everyone who answers, and limit the total number of answers you want to receive. Then, based on the parameters you choose, it could be just seconds until you get your responses, telling you that the pink sweater just doesn’t match the outfit as much as the blue one.

This way, we create a connected ecosystem of people sharing opinions, and those opinions get real value, as represented through REW tokens. Tokens circulate from brands to people, to other people, creating a new kind of social shopping experience.

User Reviews

With the rapid growth of the Internet and mobile phone applications, almost every business, product or service can now be reviewed or rated, and the masses regard this ability as essential to their rights as empowered consumers. As a result, almost everyone may be influenced by online reviews before buying a product or using a service. However, what can be considered a good rating? Online reviews vary so widely from website to website, not to mention the epidemic of fake reviews.

Reviews and ratings have a massive economic impact on both businesses and consumers. Professor Michael Luca reports in a Harvard Business School research paper ( 2015 ), that a one­star increase in Yelp ratings translates into a 5% to 9% increase in revenues for restaurants. A Center for Hospitality Research Publications, Cornell University ( 2010 ), found out that travel­related websites such as TripAdvisor, Priceline or Expedia are used by more than 40% of leisure travelers to make purchase decisions. This number is surely to have increased since.

Some of the most popular consumer review websites include Amazon, Google+ Local / Google Places, TripAdvisor, Yellow Pages and Yelp! (complete list). TripAdvisor claims to have 455 million active users and over 600 million online reviews. The company reported 1.56 billion USD in revenue for 2017. Yelp reports 145 million monthly users and a total of 155 million online reviews, while their reported revenue was 847 million USD in 2017.

It is a fact that review hubs of the Internet both big and small do their best to combat fake and paid reviews. They employ a wide range of tools, from AI to lawsuits. But what is really missing from the picture in all of these centralized systems, is transparency and decentralized governance.

Reviews on Yelp, Trip Advisor and even ICO Bench are keeping the raw review data behind closed doors, they have unlimited control over it and can present them as they see fit. While that is completely understandable for centralized systems whose business models depend on keeping the raw data secret, we can do better.

Review.Network believes in making all review data transparent and publicly accessible for everyone by using decentralized technologies. This puts the power in the hands of the people and communities, however, making the data public and censorship­proof is just one piece of the puzzle.

What really makes Review.Network different is the introduction of a layer of community governance. The idea behind it is that no one party may hold the power of deciding if a review is good or bad, but it has to be a community effort. In Review.Network’s model, members of the community with a proven positive track record (validators) vote on each review that comes in, acting as a first line filter against malevolent review writers. To do this, they act upon a set of formal, objective guidelines on what constitutes a valid review (which are also presented to review writers, so they are aware of them). The consensus that the validators reach is written onto the blockchain, and the whole process is transparent and auditable. An integral part of what makes this system efficient are token incentives. Token incentives are designed in such a way that they reward good players and punish bad ones (through a staking mechanism).

After a review is approved by the validators, the community gets a say in evaluating it through voting, based on if it’s been helpful/useful or not. This affects the overall rating of a review, also allowing anyone to open a challenge for a certain period of time, if they believe it should be removed for just cause. In this case, the staking of tokens plays a role, and the review goes through another round of validation.

Another feature that we seldom see on popular review sites is the information on who wrote a review. Sure, you can see their username, but what about knowing if it was written by a tourist or a local, if it was someone similar to your age or different? When it comes to restaurant ratings for example, tourists can rate a certain Paella place in Barcelona much differently than locals would, simply because they might not have tried the popular local dish in many different places, and don’t have a point of reference on what a good Paella is. A person that wants to try a really good Paella would want to look at reviews of locals. Same goes for looking at club reviews, you might prefer to know the opinions of people similar to you in terms of age and interests, since there is a higher chance that their opinions would match your own.

Review.Network’s protocol will allow this kind of advanced review filtering. It will be a premium feature, paid for in REW tokens, since it requires other users disclosing some anonymized information about themselves. The tokens you pay for the service will go directly to the users that share their data with you and allow for better information so you could make a more informed decision.

Building on top of Review.Network

Review.Network will be more than an “app” ­ at the core, it is a decentralized market feedback protocol, on top of which the Review.Network platform itself will be built. This means that other developers will be able to build apps implementing our protocol, allowing them to easily plug­in the market feedback mechanisms that define Review.Network.

Let’s explore one such possible use case ­ a health care app.

Imagine if asking a real doctor was as easy as typing a query into WebMD. A developer might create an application that will grow a network of medical doctors ready to answer people’s questions. Doctors would have data about their qualifications verified through the protocol (e.g. how many years of practice they have, their specialties, which hospitals they work at etc.). This data can then be used by people who want a quick answer from a verified doctor to a medical question. Such an application would allow users to target doctors based on their privately verified data and ask questions regarding their health, while paying for the answers with REW tokens.

An application like this would use Review.Network’s protocol to facilitate communication between doctors and people. A developer would create a nice looking interface for users and doctors, and allow medical institutions to verify a doctor’s’ credentials and qualifications. Then, it’s a matter of categorizing doctors, so that people could target them based on their level of experience, speciality, and overall need, in order to ask a question or two.

In addition, the app could integrate the review functionality. This would allow patients to review doctors and vice versa, with all reviews being validated by the application’s community.

Conclusion

The use­cases discussed above are just scratching the surface of what’s possible in applying decentralized solutions to the market research and user review fields. Review.Network’s decentralized market feedback protocol will allow anyone to build new apps tackling specific niches on top of it, which in turn will help make the use of Review.Network more widespread. The market research industry hasn’t changed very much in the last couple decades, and blockchain is a perfect foundation to tackle the issues that are hampering the industries, and expanding the status quo. In the spirit of decentralization, it’s time to empower people with a stronger voice in the global marketplace.

Review Network Pre­Sale is now live and we are among their advisers.

You can participate by following this link. If you want to join us in the discussion, please follow the link to Review Network Telegram group.

For more information about the project, visit Review.Network.


Review.Network Market Research and User Reviews Case Studies was originally published in MVP Workshop on Medium, where people are continuing the conversation by highlighting and responding to this story.

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