How does the revenue model of RedCab work?
As the Pre-ICO is getting closer and the RedCab community grows larger, our team receives more questions about the ICO and the project itself. Many questions we receive, are concerning the revenue model of RedCab and this is not a surprise as the project goal is to reduce the fare commission to 0%. In the following, we will explain you how and why the revenue model will work and sustain the market conditions.
The main goal of RedCab is to make profit not as a cut from the driver’s revenue, but from ads that will be displayed within the App. Digital advertising is a promising market, growing with an impressive rate year by year and expected to reach more than 335 Billion USD by year 2020 (Source: statista.com). To achieve a high conversion rate, it is required to study the users and offer them the necessary good at the right time. RedCab is planning to collect user data by analyzing their routes and preferences.
Location-Targeting: How it works?
Location-targeting is a simple concept analyzing the users route while using the service. The users get located by the GPS-Location or simply by adding their point of departure and destination into the App. The application will collect the data and draw conclusions according to different locations.
Location-Targeting: Why it works?
The targeting of a user through geo-location will be facilitated through the fact, that the user will be motivated to have a switched-on GPS throughout the ride as it is necessary to generate the REDC-Tokens for Proof-of-Marketing.
An example: Your friend will recommend you the App and inform you, that if you are following his recommendation and use the App, he will receive tokens for each kilometer you have ridden with the RedCab service. If you know that your friend will benefit from your rides, you will switch on your GPS so he can receive his benefits.
The drivers will have a motivation to keep their GPS locator as it is a condition for earning REDC tokens through Proof-of-Driving. For each ridden kilometer, the driver will be rewarded.
The collected data will be analyzed and user to define user preferences. Ideally, a user who is taking many rides to a Chinese restaurant will see an ad, suggesting him to try out another restaurant with a far-east cuisine.
Location-Targeting: Restriction
As our world is much more complex, we cannot simply rely on the geo-locations to make sure that the ads displayed are really relevant. If the user is taking a ride to a mall, there is no way to find out whether he prefers far-east or middle-east cuisine by analyzing his route.
The solution: Cabbi the smart Bot
To find out more about user preferences, RedCab is introducing Cabbi. Cabbi is a smart road assistant inside the App, that will enhance and personalize the user experience throughout the ride. Cabbi’s look can be modified according to the user preferences. During the ride Cabbi will ask questions and make suggestions. By using AI and Natural Language Processing (NLP) technologies, Cabbi will involve the customer in a chat as if it was a chat with a friend or family member. With Cabbi, the user will not get the impression that he is answering boring survey questions. What will be the motivation of the user to respond to Cabbi’s messages? By responding, user can expect an enhanced and more personalized experience next time. Let’s imagine a dialogue with Cabbi:
Cabbi: Hey Jack, how are you doing? Going home from work?
Jack: No, I’m going to pick up my son from the kindergarten
Cabbi: Did you know that there is an offer at café XYZ for the kids?
Jack: Okay, give me a ride to that café after we reach the kindergarten.
On the way home:
Cabbi: Hey Jack, how was the food at café XYZ? Did your son enjoy it?
Jack: It was good but too fatty. Not a healthy meal for kids.
From this dialogue Cabbi will learn, that Jack has a son, the location of the kindergarten, and he will conclude that Jack is a supporter of healthy lifestyle. For the next ride he will suggest to Jack a café that is concentrated on healthy food.
Of course this dialogue is a very simplified version of Cabbi’s capabilities. Today data science is progressing in huge steps and RedCab is planning to acquire a team of data scientists to ensure, that Cabbi will contain the most progressive technologies at the current market.
Cabbi is planned to be implemented by Q4–2019 along with the REDC-wallet integration.
Visit us on:
RedCab Website: https://redcab.io/
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LinkedIn: https://www.linkedin.com/company/redcab/
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