CASE STUDY
Cyclistic Bike Share
- Scenario
Cyclistic is a fictional bike share
company from Chicago. Lily Moreno is the Director of marketing who believes
that the company's future success resides on the company's abilities to
maximize the number of annual memberships. Your team of Data analysts want to
understand how casual riders and annual riders use Cyclistic bikes
differently. From these insights, your team will
design a new marketing strategy to convert casual riders into annual members.
But first, Cyclistic executives must approve your recommendations, so they must
be backed up with compelling data insights and professional data
visualizations.
One approach that helped make these
things possible was the flexibility of its pricing plans: single-ride passes,
full-day passes, and annual memberships. Customers who purchase single-ride or
full-day passes are referred to as casual riders. Customers who purchase annual
memberships are Cyclistic members. Cyclistic’s finance analysts have
concluded that annual members are much more profitable than casual
riders.
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. Moreno and her team are interested in analyzing the
Cyclistic historical bike trip data to identify trends.
-APPROACH-
1- Ask
Moreno has assigned you the first
question to answer: How do annual members and casual riders use Cyclistic
bikes differently?
At this point we know what
management and stakeholders need. What the data analyst should do is deliver a
clear statement of the business task.
2- Prepare
The dataset provided for this task
will downloaded from https://divvy-tripdata.s3.amazonaws.com/index.html
This is a public dataset offered by
a motivated international, Inc. The issues of privacy, security, and licensing
are addressed ahead of the study. The dataset is securely downloaded and stored
safely. The excel files are filtered and cleared. The Reliability, Originality,
comprehensiveness, time stamp and the citation is well established.
3- Process
All .CSV files are uploaded to the
Excel and the data is ready for cleaning and transformation. The tool of choice
in this case is Microsoft excel for data manipulation. First, we unzip all the
files. Next step is to check for errors and nulls. Remove rows we don't need
such as: ride_id. The columns started _at and ended_at are duplicated in order
to separate the time and the date. In both rows, the date is formatted as
HH:MM:SS and date is formatted as MM/DD/YYYY. New column is created with the
title of "trip_duration_minutes" using the formula
= Table.RenameColumns(#"Removed
Columns",{{"tip_abs", "trip_duration_minutes"},
{"ended_hour", "end_your"}, {"ended_date",
"end_date"}, {"started_hour", "start_hour"},
{"started_date", "start_date"}})
Created a column called
“day_of_week,” and calculated the day of the week that each ride started using
the “WEEKDAY” command (for example, =WEEKDAY(C2,1)) in each file. Format as General
or as a number with no decimals, noting that 1 = Sunday and 7 = Saturday.
4- Analyze
In order to understand the data,
some calculations and new columns are needed.
Column mean of
"ride_length" = AVG (total _ride length/total ride). Max ride_length=
longest ride. The mode day of the week is the commonly reoccurring value
in a dataset.
During the year period, we notice
that the MAX ride length by a casual member is 2,924,156 minutes compared to
3,145,444 minutes of use by an annual member. During that same period, the MIN
ride length for a casual member is 65,033; compared to 26,439 minutes by an
annual member.
This graph shows the numbers and
length of rides by both casual and annual members.
Users with annual membership to more
rides that those who have a casual membership.
Overall
the data show also that both annual members and casual members preferred the
electric bike over the classic bike. Furthermore, it is very important to take
into consideration the number of docked bikes. More bikes on the dock represent
a significant loss in revenue for the company.
The
Third and Fourth quarter were the busiest amongst both types of riders.
Nevertheless,
annual members still had the highest number of rides regardless of quarter.
5- Share
Considering our previous analysis, the data shows that the
annual members took more trips and for a longer duration than casual members.
However, casual members took more trips than annual members on the weekends. We
also notice the preference in the electric bike compared to the classic bikes.
Nevertheless, we have seen the staggering amount of docked bike at any given
time of the year.
Recommendations
We have seen how casual members and annual members of
Cyclistic user bike differently. Because the first quarter of the year is very
slow in service for both casual and annual members, Cyclistic could offer
promotional discounts and coupons in order to encourage casual members to
upgrade to annual members.
The number of docked bikes is a loss of revenue to
Cyclistic. A collection of data must be done to identify those starting points
that are most used and increase the number of bikes there. Furthermore, studying
the routes of those users will be very beneficial to Cyclistic in the
future.
CASE STUDY
by Sinclair Allen
11/04/2022
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