Can you feel that sometimes when you open your mobile phone to view takeout order, you find that the expected delivery time is 12:00, but when you open it again, you find that the expected time has changed to 12:30 and the rider delivered in advance at 12:29. Why does this happen? If the delivery time always fluctuates dynamically, is it necessary to show it?
1. How to calculate the estimated delivery time of takeout?
The previous delivery platform did not show the expected time. Users can only estimate a time period based on previous experience to determine when they can get the delivery. Now the delivery platform provides this service, which also helps users reduce the fatigue of calculation to a certain extent.
So, how does the platform calculate time?
1. Calculation method
The reason for the change in the estimated delivery time is the calculation method. In the takeaway scenario, the estimated time is generally calculated by combining the current time, progress, distance, and production time of the merchant to calculate the time to reach the destination. Therefore, under changing conditions Expected times also vary.
Presentation of estimated time to customers: before customers place an order, the reservation time can prompt customers to help them arrange what they can do during the time waiting for takeout. The estimated time after placing an order can help customers understand the comprehensive progress.
If you only see the delivery distance and key time, in fact, the customer does not know the rider's mission and traffic conditions, and the evaluated time will be slightly biased than the official estimated time.
3. How to deal with it
What is more appropriate to deal with the estimated time in a changing scenario? The following processing can be done in combination with the change scenario:
- Display the estimated completed time period or time point when placing an order.
- When the order is completed, the order information is displayed and the updated estimated time is displayed.
In the process of contract performance, the estimated time is updated by taking key nodes, such as merchants receiving orders, merchants shipping, riders receiving orders, riders arriving at the restaurant, riders picking up foods, and users actively querying, etc.
When updating the estimated time, compare the current estimated time with the historical time (estimated time after placing an order). If it is a certain time later than the historical time (such as half an hour or more than 30% ), it will prompt the customer that the delivery may be late due to busy traffic and other reasons, and the new time is expected to arrive.
The expected time that will change shows that the platform has the ability to improve the performance ability. If the estimated time remains unchanged from before the order is placed to the time of delivery, but each time there is a difference between the actual time and the estimated time, That is not a good result for both the platform and the users. The platform has lost trust, and the users have to wait in confusion.
2. Look at the problem from the perspective of users
By understanding how to calculate the time of takeout, I believe many people have a certain understanding of why the estimated time fluctuates. Then, from the perspective of users, what are the advantages of the platform displaying such fluctuating estimated time?
1. The display is to meet the anchoring psychology of users
Unknowns will surprise and upset users. Users always like to be in control of everything. In this way, the overall control will have a general cognitive range, so that they can make their own arrangements, so as not to wait for a takeout without knowing when it can be delivered.
The process of waiting for takeout, if there is no time to display, is unknown to users. They do not know when the takeout will be delivered. In this way, users will be very passive and consume more time and cost to wait.
For example, users probably know that the takeout is delivered at 19:30, so the waiting time cost is about 19:30, with an error time of 10 minutes, a total of 20 minutes.
However, if the user doesn't know the time of display, after ordering the takeout from 19:00, the user has fallen into unknown passivity. The next thing is to wait for the takeout to come.
On the contrary, the platform has given an approximate time. Although there are dynamic fluctuations affected by multiple factors, there is an approximate expected time here. Users can roughly know when they can receive takeaways, which can meet users’ expectations, giving users a sense of control.
2. Good user experience
In fact, the takeout platform will also monitor and test the relationship between the delivery time and user complaints through big data, and put the expected delivery time within the limit accepted by users, so as to minimize refunds, complaints and other behaviors caused by the time.
The estimated delivery time is a part of the general consumption scenario. If it is not displayed, the scenario will be incomplete and the cost will be increased.
In general transaction scenarios, both parties will make an agreement on the transaction object, amount, time, place and other information. In the takeout scenario, users use the platform, consume money and get services. They also need to make an agreement on the information just mentioned.
If the estimated time is not displayed, consumers will repeatedly confirm the missing information, which will increase the communication cost. If the data can not fluctuate, it will also make the user experience better to a certain extent.
3. Consider the problem from the perspective of the platform
The takeout platform needs to consider three roles: shopping user, takeout worker and merchant. These three are very important. Without one, the whole process will not work.
This estimated time is a comprehensive consideration of the 3 roles experience. After the user buys something, they need to wait for the merchant to complete the order, and then the delivery person will deliver the item. The estimated time is predicted according to the order data of the previous orders.
There are two possibilities. The first one is to deliver it perfectly according to the scheduled time or even in advance. The whole process is perfectly. This is an excellent user experience.
The other is that there are some special circumstances, such as the new delivery man, the slow production of foods, and other special circumstances that are not taken into account, which may increase the estimated time.
The platform needs to be compatible with these situations and reduce the negative experience of users as much as possible. Each change of expected time is a "candy" for users to delay satisfaction. It gives users a psychological expectation, which can reduce anxiety about unknowns.
The thinking mode of the platform can also be considered from the following two perspectives.1. Performance perspective
An indicator of improving customer experience and constraining merchants and riders to achieve the quality of contract performance.
The takeaway platform knows that this dynamic time adjustment will affect the quality of service for users, but after all, it affects a small number of users. Compared with meeting the expectations of most users, time changes are actually acceptable and understandable.
Moreover, there will be some fluctuations in the actual calculation. Rather than leaving users at a loss, providing some data can make users feel at ease to do something during the waiting time, which can make the user experience better.
2. Commercialization perspective
Once consumers buy this product, merchants will give consumers a lot of information (traceability, logistics update, etc.), which also meets the expectations of most users.
From most people's point of view, in fact, most users want to know the expected delivery time. Even if the data will fluctuate to some extent, it will not prevent users from using this feature.
However, it is expected that the problem of time fluctuation still exists. While meeting the psychology of users, it will also cause a certain loss of trust. The takeout platform can also focus on the solution to this problem in the future optimization, so as to satisfy more users.
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