Cyclistic Case Study

				    
Published on 14th june, 202115 min read

			    

			    
			    

				    

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As the part of Capstone project in Google Data Analytics program, a case study was done on a bike-share company, to analyse their data and to derive meaningful conclusions

				    
				    
OVERVIEW

				    
Cyclistic is a bike-share company that have 5,800+ bicycles and 600+ docking stations. There are two type of riders, Annual members who take a year long membership , Casual riders who either choose for 1 ride or for the entire day. The director of the company believes comapny's futire success depends on maximizing the number of annual membership. Lily Moreno who is the director of marketing and my manager assigned me the following business task.  

				 
				    
APPROACH

				    
In this Case-Study we follow a structured 6 steps of Data Analysis as follows :

            

           
            
ASK

            
  • From 12 months of bike-sharing data, find out How do annual members and
              casual riders use cyclistic bikes differently; To Cyclistic executive team and Lily
              Moreno who are my primary and secondary stakeholders respectively
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    PREPARE
    
          
  • 12 months Cyclistic's historical trip data - 1st party data.
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  •  The data has been made available by Motivate International Inc.
            License is available here
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  • It is structured data which is organized into rows and columns
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    PROCESS
    
					
  •  Tools I used for this case study is Rstudio
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  • Data integrity is ensured by going through any possible error, accuracy and consistency of data
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  • Whole Data cleaning and analysing was documentedby a RMD file. Explore RMD file!
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    ANALYZE
    
          
  • The data was organized by week day
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  • By the chart given below, A trend was found that during weekend there is more number of casual riders. We can call it Weekend effect. 
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  • whereas we can see constant number of annual riders during weekdays, so it may be working class who are maximum utilizing Annual membership
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  • By the column chart given below, We can see that casual riders spend more time on ride, which gives a confirm that either they use for long distance commutation or for tourim activities such as sightseeing. 
         
     

				
    SHARE
    
        
  •  Finally, A presentation was made inorder to communicate our findings with stakeholders. It is presented below.
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    ACT
    
        
  • So our recommendation to the stakeholders is that including a weekend plan in annual membership and also discounted rates after few distance or time will attract more casual riders to choose annual membership
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