Capston Project: A case study to convert temporary customers into permanent c...Curtin University
I have completed this project to complete the final step of the google analytics program which is a capston project. This case study is about a fictional company called Cyclistic which has a potential to increase profitability by converting casual users to members. As a data analyst, my role was to dive more into the behaviors of the casual riders to understand if there are any potential opportunities for the company. The dataset used in this case study are licensed by Motivate International Inc (https://ride.divvybikes.com/data-license-agreement).
A junior data analyst working in the marketing analytics team at Cyclistic -a bike-share company in Chicago- The marketing team wants to design a new marketing strategy to convert casual riders into annual members. • Data has been cleaned, organized and visualized using R. And recommendations were given based on the key findings.
Cyclent | Rent your miles | Android App Marketing PlanSaurabh Yadav
Cyclent is an app that lets you quickly rent bicycles depending on your requirement & location.
The presentation is about the proposed mobile app & its marketing plan.
Bike Sharing Market 2022: Size, Growth, Demand and Forecast till 2027IMARC Group
According to the latest report by IMARC Group, the global bike sharing market reached a value of US$ 3.28 Billion in 2021. Bike sharing refers to a micro-mobility service that generally enables individuals to hire or borrow bicycles on a short-term basis. It is based on a self-service model that allows users to utilize the rental bike service using membership cards, credit or debit cards, and a smartphone. It offers electric or conventional bicycles on rent that are widely available at docking stations.
Capston Project: A case study to convert temporary customers into permanent c...Curtin University
I have completed this project to complete the final step of the google analytics program which is a capston project. This case study is about a fictional company called Cyclistic which has a potential to increase profitability by converting casual users to members. As a data analyst, my role was to dive more into the behaviors of the casual riders to understand if there are any potential opportunities for the company. The dataset used in this case study are licensed by Motivate International Inc (https://ride.divvybikes.com/data-license-agreement).
A junior data analyst working in the marketing analytics team at Cyclistic -a bike-share company in Chicago- The marketing team wants to design a new marketing strategy to convert casual riders into annual members. • Data has been cleaned, organized and visualized using R. And recommendations were given based on the key findings.
Cyclent | Rent your miles | Android App Marketing PlanSaurabh Yadav
Cyclent is an app that lets you quickly rent bicycles depending on your requirement & location.
The presentation is about the proposed mobile app & its marketing plan.
Bike Sharing Market 2022: Size, Growth, Demand and Forecast till 2027IMARC Group
According to the latest report by IMARC Group, the global bike sharing market reached a value of US$ 3.28 Billion in 2021. Bike sharing refers to a micro-mobility service that generally enables individuals to hire or borrow bicycles on a short-term basis. It is based on a self-service model that allows users to utilize the rental bike service using membership cards, credit or debit cards, and a smartphone. It offers electric or conventional bicycles on rent that are widely available at docking stations.
MARKETING & BUSINESS PLAN PRESENTATION.pptxPankaj Rajput
tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments acting on the tire from the
ground. Tractive force (or longitudinal force) F, is the component in the X
direction of the resultant force exerted on the tire by the road. Lateral force
F, is the component in the Y direction, and normal force F, is the component
in the Z direction. Overturning moment M, is the moment about the X axis
exerted on the tire by the road. Rolling resistance moment My is the moment
about the Y axis, and aligning torque M, is the moment about the Z axis.
With this axis system, many performance parameters of the tire can be
conveniently defined. For instance, the longitudinal shift of the center of normal pressure is determined by tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments acting on the tire from the
ground. Tractive force (or longitudinal force) F, is the component in the X
direction of the resultant force exerted on the tire by the road. Lateral force
F, is the component in the Y direction, and normal force F, is the component
in the Z direction. Overturning moment M, is the moment about the X axis
exerted on the tire by the road. Rolling resistance moment My is the moment
about the Y axis, and aligning torque M, is the moment about the Z axis.
With this axis system, many performance parameters of the tire can be
conveniently defined. For instance, the longitudinal shift of the center of normal pressure is determined by tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments acting on the tire from the
ground. Tractive force (or longitudinal force) F, is the component in the X
direction of the resultant force exerted on the tire by the road. Lateral force
F, is the component in the Y direction, and normal force F, is the component
in the Z direction. Overturning moment M, is the moment about the X axis
exerted on the tire by the road. Rolling resistance moment My is the moment
about the Y axis, and aligning torque M, is the moment about the Z axis.
With this axis system, many performance parameters of the tire can be
conveniently defined. For instance, the longitudinal shift of the center of normal pressure is determined by tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments .
India E-Bike Market by Product Type, Distribution Channel, End User 2024-2032IMARC Group
The India E-bike market size reached US$ 1,178.0 Million in 2023. Looking forward, IMARC Group expects the market to reach US$ 2,917.4 Million by 2032, exhibiting a growth rate (CAGR) of 10.6% during 2024-2032.
More Info:- https://www.imarcgroup.com/india-e-bike-market
Developing traction for startups by Society3, Axel Schultze CEO, Society3 Grp.
Traction development #Startups
Bold Ideas - It's all about the story
Market Born - share early - know the needs
Speed - Beta in less than 6 month
Connected - walk the walk, talk the talk - conversations
Bike share stations are generally spaced in a dense grid pattern to create convenient origins and destinations for riders. Bike share is oriented to short-term, point-to-point use: most US operators record the average ride at 15 to 20 minutes and between one to three miles long. The bicycle can be returned to any number of self-serve bike sharing stations, including the original check out location. Generally, the bicycles are one style and easy to operate with simple components and adjustable seats. The rental transaction is fully automated and there is no need for on-site staff.
MARKETING MANAGEMENT
Atlas Honda Limited is a public listed company which was incorporated on October 16, 1962. It is a joint collaboration between Honda Motor Company Limited Japan, the largest and most reputed motorcycle brand in the world, and Atlas Group, one of Pakistan’s most renowned business conglomerates. The Company is principally engaged in progressive manufacturing and marketing of motorcycles and spare parts.
SNS Insider is a market research company that delivers evidence-based strategies for clients seeking growth & also provides business consulting services ...
Marketing Plan for Metro Bikes Company to increase sales revenue and profit margin. Also tap the US market and generate the sales of 50000-100000 bikes in 3 years.
E-Bike Market is estimated to grow from USD 36.18 Billion in 2019 to reach USD 68.49 Billion by 2027, at a CAGR of 8.3% during the forecast period from 2020-2027.
• As the captain, leading the whole team on designing an integrated social strategy plan for the direct marketing company, Valassis, to reach high value markets to increase social awareness.
• Used statistics resources like InfoUSA, and social analysis tools like Radian6, to determine the target markets and did the real-time social monitoring.
• Applied the Social IMC Marketing Strategy to create the empowering concept and total community concept for Valassis in the two target markets, passion market and trigger event market.
• Created the detailed marketing budgets and calculated the ROI for each market.
MARKETING & BUSINESS PLAN PRESENTATION.pptxPankaj Rajput
tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments acting on the tire from the
ground. Tractive force (or longitudinal force) F, is the component in the X
direction of the resultant force exerted on the tire by the road. Lateral force
F, is the component in the Y direction, and normal force F, is the component
in the Z direction. Overturning moment M, is the moment about the X axis
exerted on the tire by the road. Rolling resistance moment My is the moment
about the Y axis, and aligning torque M, is the moment about the Z axis.
With this axis system, many performance parameters of the tire can be
conveniently defined. For instance, the longitudinal shift of the center of normal pressure is determined by tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments acting on the tire from the
ground. Tractive force (or longitudinal force) F, is the component in the X
direction of the resultant force exerted on the tire by the road. Lateral force
F, is the component in the Y direction, and normal force F, is the component
in the Z direction. Overturning moment M, is the moment about the X axis
exerted on the tire by the road. Rolling resistance moment My is the moment
about the Y axis, and aligning torque M, is the moment about the Z axis.
With this axis system, many performance parameters of the tire can be
conveniently defined. For instance, the longitudinal shift of the center of normal pressure is determined by tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments acting on the tire from the
ground. Tractive force (or longitudinal force) F, is the component in the X
direction of the resultant force exerted on the tire by the road. Lateral force
F, is the component in the Y direction, and normal force F, is the component
in the Z direction. Overturning moment M, is the moment about the X axis
exerted on the tire by the road. Rolling resistance moment My is the moment
about the Y axis, and aligning torque M, is the moment about the Z axis.
With this axis system, many performance parameters of the tire can be
conveniently defined. For instance, the longitudinal shift of the center of normal pressure is determined by tion forward. The Z axis is perpendicular to the ground plane with a
positive direction downward. The Y axis is in the ground plane, and its direction is chosen to make the axis system orthogonal and right hand.
There are three forces and three moments .
India E-Bike Market by Product Type, Distribution Channel, End User 2024-2032IMARC Group
The India E-bike market size reached US$ 1,178.0 Million in 2023. Looking forward, IMARC Group expects the market to reach US$ 2,917.4 Million by 2032, exhibiting a growth rate (CAGR) of 10.6% during 2024-2032.
More Info:- https://www.imarcgroup.com/india-e-bike-market
Developing traction for startups by Society3, Axel Schultze CEO, Society3 Grp.
Traction development #Startups
Bold Ideas - It's all about the story
Market Born - share early - know the needs
Speed - Beta in less than 6 month
Connected - walk the walk, talk the talk - conversations
Bike share stations are generally spaced in a dense grid pattern to create convenient origins and destinations for riders. Bike share is oriented to short-term, point-to-point use: most US operators record the average ride at 15 to 20 minutes and between one to three miles long. The bicycle can be returned to any number of self-serve bike sharing stations, including the original check out location. Generally, the bicycles are one style and easy to operate with simple components and adjustable seats. The rental transaction is fully automated and there is no need for on-site staff.
MARKETING MANAGEMENT
Atlas Honda Limited is a public listed company which was incorporated on October 16, 1962. It is a joint collaboration between Honda Motor Company Limited Japan, the largest and most reputed motorcycle brand in the world, and Atlas Group, one of Pakistan’s most renowned business conglomerates. The Company is principally engaged in progressive manufacturing and marketing of motorcycles and spare parts.
SNS Insider is a market research company that delivers evidence-based strategies for clients seeking growth & also provides business consulting services ...
Marketing Plan for Metro Bikes Company to increase sales revenue and profit margin. Also tap the US market and generate the sales of 50000-100000 bikes in 3 years.
E-Bike Market is estimated to grow from USD 36.18 Billion in 2019 to reach USD 68.49 Billion by 2027, at a CAGR of 8.3% during the forecast period from 2020-2027.
• As the captain, leading the whole team on designing an integrated social strategy plan for the direct marketing company, Valassis, to reach high value markets to increase social awareness.
• Used statistics resources like InfoUSA, and social analysis tools like Radian6, to determine the target markets and did the real-time social monitoring.
• Applied the Social IMC Marketing Strategy to create the empowering concept and total community concept for Valassis in the two target markets, passion market and trigger event market.
• Created the detailed marketing budgets and calculated the ROI for each market.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Show drafts
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
2. Background of the
Case Study
• Cyclistics Bike-share has a fleet of 5,824 bikes
over 982 stations in Chicago
• The company has a flexible pricing plan that
appeals to all types of consumers from those
who wants to subscribe annually to those
who just wants to use it occasionally
• Considering that annual memberships are
more profitable for the company, they want
to direct their marketing efforts from
converting casual users( those who use
single-ride and full-day pass) to members.
3. Executive Summary
• 47% of the total users of Cyclistic bike-share are casual
users, this means that converting these 47% casual
users to member will benefit the company
• Key Metrics from the latest 12 months Ride Usage
Data for Cyclistics:
• 68% of the ride usage constitutes to the use of
classic bikes, followed by 27% usage of electric
bikes and 5% usage of docked bike
• 38% or 1.2M of the total users of classic bikes are
casual users, this accounts to 60% of the total
casual users of Cyclistic bike-share
• Members and Casual users has opposite ride
usage trend during the week, Members use the
bike-share more during weekdays while Casual
users use the bike-share more during the
weekend
• Cyclistic’s marketing strategy on converting casual
users to members should focus on targeting Casual
Users of Classic Bikes on weekends, this segment
represents 26% of their current users and would
potentially increase their membership to 83%
4. With the casual
users accounting to
47% or 2,007,048 of
the total users of
Cyclistic’s bike-
share, converting
casual users to
members will be
impactful for
Cyclistic’s profit.
47%
53%
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
casual member
Number
of
Rides Rider Type
Table 1: Number of Rides as per Rider Type
5. Narrowing down
the usage of the
casual users, it is
worth considering
the bike type they
used the most.
Considering the
ride usage in the
past 12 months,
casual users have
opted more on
using the classic
bike
1213738
252014
541296
1968104
703623
0
500000
1000000
1500000
2000000
2500000
classic_bike docked_bike electric_bike
Table 2: User Type as per Bike Type
Casual Member
6. To achieve
maximum
penetration of the
target market,
knowing when and
where to launch the
marketing strategy
is an important
factor to consider.
Considering the
trend in the past 12
months, market
strategy should be
implemented
between the 2nd
and 3rd quarter of
the year
0
50000
100000
150000
200000
250000
300000
350000
400000
Jul-21 Aug-21 Sep-21 Oct-21 Nov-21 Dec-21 Jan-22 Feb-22 Mar-22 Apr-22 May-22 Jun-22
Table 3: Ride Usage by Rider Type by Month
casual member
7. The inverse
relationship of the
member’s and
casual user’s riding
usage shows that
casual users use the
bike-share more
during the weekend
while members use
it more during the
weekday 0
50000
100000
150000
200000
250000
300000
350000
400000
450000
500000
Sun Mon Tue Wed Thu Fri Sat
Table 5: Ride Usage by Rider Type by Weekday
casual member
8. Observation
What: Marketing Strategy to convert casual users to Annual
Members
Who: Target Market are the casual users using Classic Bike
When: During the 2nd and 3rd Quarter of the year with focus
on the weekend
Where: Digital Marketing and OOH Marketing
How: Digital Marketing (Social Media, Cyclistic App, Ads) and
OOH Marketing (Stations frequented by the target market)
Why: To increase Annual membership which equates to
increase in profit for the company
9. Recommendation
Introduction of a Weekend Annual Plan – to even increase usage on
weekend, we should introduce a weekend annual plan where consumers
can use the bike-hire as much as they want during the weekend
Digital Marketing campaign - Social Media (Facebook,
Instagram,Tiktok,Twitter), Ads on website, quick surveys
OOH Marketing -Billboard on high traffic areas and on the station of the
bike-hires as well
in-APP Marketing - Marketing on the app itself whenever used
Introduction of a special discount for Casual Users of Classic Bikes to
upgrate to Member – This will launched on the app whenever the user
starts using the app
10. Index: Codes
used in R
#Installing the necessary packages required
install.packages("tidyverse")
install.packages("lubridate")
install.packages("ggplot2")
install.packages("anytime")
#Uploading the library of functions that will be used
library("tidyverse")
library("lubridate")
library("ggplot2")
library("anytime")
#Uploading the 12 inidividual data frame
july_2021 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data Source/202107-
divvy-tripdata.csv")
august_2021 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data Source/202108-
divvy-tripdata.csv")
september_2021 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data
Source/202109-divvy-tripdata.csv")
october_2021 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data
Source/202110-divvy-tripdata.csv")
november_2021 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data
Source/202111-divvy-tripdata.csv")
december_2021 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data
Source/202112-divvy-tripdata.csv")
jan_2022 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data Source/202201-
divvy-tripdata.csv")
feb_2022 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data Source/202202-
divvy-tripdata.csv")
mar_2022 <- read_csv("C:/Users/Mark Ferrera/Desktop/Data Analysis Portfolio/Data Source/202203-
divvy-tripdata.csv")