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Uber: Applying Machine Learning to Improve the Customer Pickup Experience Case Solution & Answer

 Uber: Applying Machine Learning to Improve the Customer Pickup Experience Case Study Solution 

                                                           Define the Problem:

The company aimed at offering easy travel services in the market. The company since it was created, targeted the US market through strong value proposition of offering easy car rides where cab services were much expensive when compared to the fares charged by Tuber. It considered passengers as its customers and focused towards offering easy rides and convenient travelling to them. The ride sharing services had expanded across the globe, growing at faster pace in Europe, India, China, US and Southeast Asia. Pickups became complex by the crowded pickup venues, faulty GPS signals and traffic congestion. The flawed pickups resulted in the dissatisfaction of rider and lost its revenues. The pickup experience was identified by Tuber as a top strategic priority and the team at Uber, led by Birju Shah – group product manager, was tasked with designing an automated solutions to enhance the pickup experience of the customers.

List any outside concepts that can be applied:

The theory of innovation in terms of an advanced mobility with artificial intelligence (AI) could be applied to the case. Additionally, the SWOT framework could be applied to assess the internal strengths and weakness of the company and to explore the market opportunities as well as threats, in order to identify the core competencies, support brainstorming sessions and to foster the strategic planning process to effectively assess where the company stands before managing the limitation or moving forward with opportunities or market trend.

Furthermore, the Customer Process Management is another framework to be used for the improvement of the customers’ satisfaction and overall experience, and it also supports constant change as well as business agility.(Conchie Lin, 2019). Also, the company could use the porter’s five forces model in order to understand the factors influencing the profitability, and helping in making an informed decisions related to whether or not to develop the competitive strategies, increase capacity and enter into specific market.

List relevant qualitative data:

There are various challenges in pickups, including: cultural differences as people in India prefer to call rider to give precise direction to them and to make sure that driver is on the way;whereas in the US; customers prefer to interact with rider through text messaging or Uber app. Another challenge is to ensure that riders are matched with appropriate type of ride sharing modalities, proper and effective communication between rider and driver related to the pickup location, provision of safe traveling experience to the customer and getting prepared to assist in case any accident occurs, meeting the diverse expectations of riders and fostering the safe and compliant environment.

The usage of Machine learning, helps Uber in optimizing its maps and improving its pickup experience for all the drivers and riders. Additionally, the company collects masses of data to makes predictions related to the market demand, coming up with the best routes to drivers as well as responding to address the concerns in quickly manner, keeping itself updated of the changing routes and so forth.(SHARMA, 2019)………….

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