The whole chain of thought cues is very long, and it takes a lot of rides to get enough virtual coins, and the feedback cycle is very long. However, many users do not have a complete thinking thread when they see ofo's yellow bikes, which means they do not realize that many rides can earn enough points to exchange for a relatively valuable product in the Achievement Pavilion. This chain of thought cues is too long to be useful in helping users make fast thinking decisions. In other words, when a user comes out of a subway station and sees both a yellow bike and a Mobike at the same time, it is hard for them to think of exchanging goods at ofo Achievement Hall, so they have to accumulate virtual coins by riding the yellow bike.

Moreover, it is not clear to the user exactly what goods to change and how many rides to get the goods. Therefore, the above decision-making process is actually very difficult to make. If the user can't make the decision to choose the yellow car in scenario C, then the project will not achieve our goal. According to this deduction, I resisted the pressure and did not do the integral mall project. It turned out that I had made the right decision. At that time, I also asked the team members a question: Is there anything you like in Mobike Achievement Hall? How many rides do you have to take to get the goods you like? No one could answer correctly. Our team members are all in the industry, and if they don't know it, how can we expect the average user to research it and build a clear decision bias? !

The whole chain of thought cues is very long, and it takes a lot of rides to get enough virtual coins, and the feedback cycle is very long. However, many users do not have a complete thinking thread when they see ofo's yellow bikes, which means they do not realize that many rides can earn enough points to exchange for a relatively valuable product in the Achievement Pavilion. This chain of thought cues is too long to be useful in helping users make fast thinking decisions. In other words, when a user comes out of a subway station and sees both a yellow bike and a Mobike at the same time, it is hard for them to think of exchanging goods at ofo Achievement Hall, so they have to accumulate virtual coins by riding the yellow bike. Moreover, it is not clear to the user exactly what goods to change and how many rides to get the goods. Therefore, the above decision-making process is actually very difficult to make. If the user can't make the decision to choose the yellow car in scenario C, then the project will not achieve our goal. According to this deduction, I resisted the pressure and did not do the integral mall project. It turned out that I had made the right decision. At that time, I also asked the team members a question: Is there anything you like in Mobike Achievement Hall? How many rides do you have to take to get the goods you like? No one could answer correctly. Our team members are all in the industry, and if they don't know it, how can we expect the average user to research it and build a clear decision bias? !

The whole chain of thought cues is very long, and it takes a lot of rides to get enough virtual coins, and the feedback cycle is very long. However, many users do not have a complete thinking thread when they see ofo's yellow bikes, which means they do not realize that many rides can earn enough points to exchange for a relatively valuable product in the Achievement Pavilion. This chain of thought cues is too long to be useful in helping users make fast thinking decisions. In other words, when a user comes out of a subway station and sees both a yellow bike and a Mobike at the same time, it is hard for them to think of exchanging goods at ofo Achievement Hall, so they have to accumulate virtual coins by riding the yellow bike.

Moreover, it is not clear to the user exactly what goods to change and how many rides to get the goods. Therefore, the above decision-making process is actually very difficult to make. If the user can't make the decision to choose the yellow car in scenario C, then the project will not achieve our goal. According to this deduction, I resisted the pressure and did not do the integral mall project. It turned out that I had made the right decision. At that time, I also asked the team members a question: Is there anything you like in Mobike Achievement Hall? How many rides do you have to take to get the goods you like? No one could answer correctly. Our team members are all in the industry, and if they don't know it, how can we expect the average user to research it and build a clear decision bias? !

The whole chain of thought cues is very long, and it takes a lot of rides to get enough virtual coins, and the feedback cycle is very long. However, many users do not have a complete thinking thread when they see ofo's yellow bikes, which means they do not realize that many rides can earn enough points to exchange for a relatively valuable product in the Achievement Pavilion. This chain of thought cues is too long to be useful in helping users make fast thinking decisions. In other words, when a user comes out of a subway station and sees both a yellow bike and a Mobike at the same time, it is hard for them to think of exchanging goods at ofo Achievement Hall, so they have to accumulate virtual coins by riding the yellow bike. Moreover, it is not clear to the user exactly what goods to change and how many rides to get the goods. Therefore, the above decision-making process is actually very difficult to make. If the user can't make the decision to choose the yellow car in scenario C, then the project will not achieve our goal. According to this deduction, I resisted the pressure and did not do the integral mall project. It turned out that I had made the right decision. At that time, I also asked the team members a question: Is there anything you like in Mobike Achievement Hall? How many rides do you have to take to get the goods you like? No one could answer correctly. Our team members are all in the industry, and if they don't know it, how can we expect the average user to research it and build a clear decision bias? !