Casual riders are more leisure-oriented usage the bikes although member riders use the bikes for routine activities like commuting to work or school.In this analysis, we found the patterns which indicate that: The columns in the MySQL table need to match the data from the CSV file. I created a database called divvy_tripdataand a table named divvy_2021 in MySQL Workbench. In the end, I typed “ copy *.csv combined-CSV-files.csv” and Enter.Ĭreate database and table for Importing CSV into MySQL
Chicago divvy windows#
I open the Windows Command prompt and I typed “ cd and press Space and paste of folder path”. I tried different methods, but in the end, I found combination data through the “Windows Command prompt” the fastest and easiest way to do so.įirst, I created a folder to house all CSVs files and I browse the folder. My first challenge was appending the 12 CVSs files in the best method. in fact, we did not have access to any kind of demographic variables such as gender, age, ethnicity, income, etc.ĭata appending of 12 CSVs files into one database The data set had limitations for having a comprehensive knowledge of riders. The tools that I used in the analysis are MySQL, Microsoft Excel, Tableau Public, Power BI, and Google Sheet How can Divvy use digital media to influence casual riders to become members? What kind of campaign do you recommend encouraging casual riders to buy annual membership?Ĥ. What can pursue casual riders to convert to annual subscribers?ģ.
How do annual members and casual riders use Divvy bikes differently?Ģ. To maximize the number of annual memberships by converting casual riders to annual members.Īnalyze how annual members and casual riders use Cyclistic bikes differently in order to determine the best marketing strategies that would convert casual riders to annual members.ĭivvy executive team, Director of marketingġ. Step1- Understanding business tasks and making questions Riders’ personally identifiable information has been removed from the data due to data privacy. csv file contained data for a whole month. The dataset can be downloaded from here in. In this case study, I used the one-year period of Divvy trip data (from January to December 2021) provided by Motivate International Inc, under this license. In the end, I will provide recommendations based on insights that can help the marketing team to create a campaign to boost casual users’ conversion into member users. In this case study, I will try to analyze various trends based on user types and bike types to find similarities and differences between the riders. To do that, the marketing analyst team needs to have a better understanding of members’ and casual riders’ usage behaviors. Although the pricing flexibility helps Divvy attract more customers, the director of marketing believes that annual members are much more profitable than casual riders, and maximizing the number of annual members will be key to future growth. Users of Divvy operation can be broken down into two main groups: those users who purchase single-ride or full-day passes are referred to as casual riders and users who purchase annual memberships are considered member riders. Divvy is a bike share system across Chicago and Evanston that features more than 5,800 bicycles and 600 docking stations.
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