Editor’s introduction: Many small partners do Latvia Phone Number not understand what the product manager’s downgrade thinking is. What aspects can reflect this thinking? The author investigates several classic. Product cases and deeply explores the downgrade thinking of product managers to ensure the availability of functions. Hoping to help you understand the downgrade thinking.So the author investigated several classic. Product cases to talk about downgrading thinking in depth.

What is downgrade thinking. Degraded thinking refers to the idea of ​​extracting core functions and implementing secondary functions in other ways. When the resources that a function depends on are insufficient to maintain its normal operation.

Case 1: Didi Taxi

In the past, when taking a taxi on Didi, it would display. The detailed location of the taxi driver in real time, as well as the exact location of nearby taxis, as well as intelligent and complex order dispatching logic.

 

This leads to the delay of displaying taxis and taxi locations, and the slowing down of successful taxis, which seriously affects the user experience.

In order to improve the user experience, we need to adjust the strategy, extract core functions, and implement secondary functions in other ways.

The core function of Didi Taxi is to allow users to get taxis as quickly as possible.

Later, Didi Taxi did the following downgrade processing:

  • Accurately show my current location Adjust to: Show my detailed location during off-peak hours. Detailed text display is cancel during peak periods.
  • Display of nearby taxis is adjust to: cancel the real-time display of taxi locations during peak hours, and only display some taxis that have appeared nearby in the recent time.
  • The intelligent and complex order dispatching adjustment is: downgraded to random allocation order dispatching logic during peak periods.

Case 2: Tencent Map Point Aggregation

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However, if there are more and more stores, the display of dots will be very dense, affecting readability, and rendering so many dots at the same time is also a challenge in performance.

The downgrade strategy of Tencent Maps is: automatically aggregate markers with similar distances together and present them in the corresponding position in the map in a statistical way. This can not only reduce the number of points, but also achieve clear and easy-to-read scene requirements

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