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Goal

Moreno(director of marketing and manager.) Design marketing strategies aimed at converting casual riders into annual members. In order to do that, however, the marketing analyst team needs to better understand how annual members and casual riders differ, why casual riders would buy a membership, and how digital media could affect their marketing tactics. her team and her are interested in analyzing the Cyclistic historical bike trip data to identify trends. Ask

  • Three questions will guide the future marketing program:
    1. How do annual members and casual riders use Cyclistic bikes differently?
    1. Why would casual riders buy Cyclistic annual memberships?
    1. How can Cyclistic use digital media to influence casual riders to become members?

-** IDEAS TO EXPLORE ** What do they use it for? where do they go? how's the commute situation at a certain time of the day? why taking the bike instead of the bus ? How many bikes are available per station? busiest time, day, weed-day or week-ends?

NEED MORE DATA!!!

You will produce a report with the following deliverables:

  1. A clear statement of the business task

Business Task Statement

My business task is to analyze and compare the usage patterns of casual riders and annual members of Cyclistic bikes. By understanding how these two groups differ in their usage, I can develop a marketing strategy to convert casual riders into annual members. The marketing strategy should be supported by data insights and professional data visualizations to gain approval from Cyclistic executives. My ultimate goal is to maximize the number of annual memberships and ensure the future success of the company.

  1. A description of all data sources used

  2. Documentation of any cleaning or manipulation of data

  3. A summary of your analysis

  4. Supporting visualizations and key findings

  5. Your top three recommendations based on your analysis

Guiding questions ● What is the problem you are trying to solve? ● How can your insights drive business decisions?

Guiding questions ● Where is your data located? ● How is the data organized? ● Are there issues with bias or credibility in this data? Does your data ROCCC? ● How are you addressing licensing, privacy, security, and accessibility? ● How did you verify the data’s integrity? ● How does it help you answer your question? ● Are there any problems with the data?

Key tasks

  1. Download data and store it appropriately.
  2. Identify how it’s organized.
  3. Sort and filter the data.
  4. Determine the credibility of the data.

● What tools are you choosing and why? ● Have you ensured your data’s integrity? ● What steps have you taken to ensure that your data is clean? ● How can you verify that your data is clean and ready to analyze? ● Have you documented your cleaning process so you can review and share those results?

Business Task Statement We will analyze and compare the usage patterns of casual riders and annual members of Cyclistic bikes. By understanding how these two groups differ in their usage, we can develop a marketing strategy to convert casual riders into annual members. The marketing strategy should be supported by data insights and professional data visualizations to gain approval from Cyclistic executives. Our ultimate goal is to maximize the number of annual memberships and ensure the future success of the company

The analysis is based on the data provided by Cyclistic, a bike-sharing company. The data consists of historical trip data for the years 2019 and 2020. The data includes information about the rides taken by both casual riders and annual members.

The data sources used for this analysis are as follows:

  1. Cyclistic trip data for 2019: This dataset contains information about the rides taken by both casual riders and annual members in the year 2019. It includes details such as trip duration, start and end time, start and end station, and user type.

  2. Cyclistic trip data for 2020: This dataset contains information about the rides taken by both casual riders and annual members in the year 2020. It includes similar details as the 2019 dataset.

Both datasets are provided in CSV format and will be loaded into the Jupyter notebook for further analysis and visualization.

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DataFrameas
df
variable
Run cancelled
--Let's first SELECT all of the columns from the divvy-tripdata table. Also, we'll limit the output to the first ten rows to keep the output clean.

SELECT * 
FROM 'divvy-tripdata.csv'
LIMIT 10;

 How is the data organized?