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A.W. Lukens
and
Tony Cox, Jr.
"Time, Change, and Decisions for Marketing" shows how advanced analytics can be used to adapt and optimize marketing strategies in response to evolving market conditions. Unique to this course is the integration of advanced analytics into strategic marketing decision-making, equipping learners with the skills and knowledge to lead data-driven marketing initiatives and coordinate strategies across teams for maximum business impact.
Register for this course and see more details by visiting:
OpenCourser.com/course/1li8np/time
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What's inside
Syllabus
Bayesian Networks
Use Causal Bayesian Networks and Partial Dependence Plots to revolutionize your marketing strategies. This module shows you how to optimize decision-making, understand customer behavior, and visually interpret complex data for strategic marketing insights.
Read more
Syllabus
Bayesian Networks
Use Causal Bayesian Networks and Partial Dependence Plots to revolutionize your marketing strategies. This module shows you how to optimize decision-making, understand customer behavior, and visually interpret complex data for strategic marketing insights.
Read more
Time and Change
Clarify the dynamics of customer behavior and market trends with Dynamic Bayesian Networks. Master time series forecasting and change detection to stay ahead in the ever-evolving marketing landscape, ensuring your strategies remain relevant and effective.
Learning and Decision Optimization
Optimize marketing and business decision-making with the help of causal forecasting. Learn to model customer journeys, perform what-if analyses, and apply Bayesian inference, equipping you with cutting-edge tools for real-time, data-driven marketing strategies.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores marketing strategies from the lens of advanced analytics techniques
Imparts valuable skills and knowledge to steer data-driven marketing initiatives effectively
Covers crucial topics including Bayesian Networks, Time Series Forecasting, and Optimization for strategic decision-making
Suitable for marketing professionals, data analysts, and aspiring leaders seeking to enhance their understanding of data-driven marketing
Provides practical applications of advanced analytics in real-world marketing scenarios
Save this course
Save Time, Change, and Decisions for Marketing to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Time, Change, and Decisions for Marketing with these
activities:
Bayesian Statistics Review
Show steps
Review the fundamentals of Bayesian statistics to strengthen your understanding of advanced analytics concepts.
Browse courses on
Bayesian Statistics
Show steps
-
Review textbooks or online resources on Bayesian statistics.
-
Solve practice problems to test your understanding.
-
Attend a workshop or webinar on Bayesian statistics.
Advanced Analytics for Marketing
Show steps
Explore online tutorials to gain additional knowledge and skills in advanced analytics for marketing.
Browse courses on
Advanced Analytics
Show steps
-
Identify reputable online platforms for tutorials.
-
Search for tutorials on advanced analytics for marketing.
-
Review the tutorials and select those that align with your learning goals.
-
Follow the tutorials and complete the exercises.
Bayesian Networks Drills
Show steps
Practice using Causal Bayesian Networks and Partial Dependence Plots to improve marketing decision-making and gain insights.
Show steps
-
Review the basics of Bayesian networks.
-
Solve practice problems using Causal Bayesian Networks.
-
Interpret the results of your analysis.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Collaborative Time Series Forecasting
Show steps
Collaborate with peers to analyze time series data, make predictions, and improve forecasting accuracy.
Browse courses on
Time Series Forecasting
Show steps
-
Split into groups of 2-3 learners.
-
Select a time series dataset to analyze.
-
Use Dynamic Bayesian Networks to forecast the future values.
-
Present your findings to the group.
Marketing Data Visualization
Show steps
Develop a data visualization that effectively communicates marketing data and insights.
Browse courses on
Data Visualization
Show steps
-
Gather and analyze marketing data.
-
Choose appropriate visualization techniques to present the data.
-
Design and create the data visualization.
-
Present the visualization to stakeholders.
Causal Forecasting Report
Show steps
Create a detailed report that demonstrates your understanding of causal forecasting and its applications in marketing.
Show steps
-
Research causal forecasting techniques.
-
Identify a specific marketing problem that can be solved using causal forecasting.
-
Apply causal forecasting techniques to solve the problem.
-
Write a report on your findings.
Data Analytics Challenge
Show steps
Participate in a competition to apply your data analytics skills and gain hands-on experience in solving real-world marketing problems.
Browse courses on
Data Analytics
Show steps
-
Identify and register for a data analytics competition.
-
Gather and analyze data to develop a solution.
-
Build and evaluate a predictive model.
-
Submit your solution and compete against other participants.
Bayesian Statistics Review
Show steps
Review the fundamentals of Bayesian statistics to strengthen your understanding of advanced analytics concepts.
Browse courses on
Bayesian Statistics
Show steps
Show steps
Show steps
- Review textbooks or online resources on Bayesian statistics.
- Solve practice problems to test your understanding.
- Attend a workshop or webinar on Bayesian statistics.
Advanced Analytics for Marketing
Show steps
Explore online tutorials to gain additional knowledge and skills in advanced analytics for marketing.
Browse courses on
Advanced Analytics
Show steps
Show steps
Show steps
- Identify reputable online platforms for tutorials.
- Search for tutorials on advanced analytics for marketing.
- Review the tutorials and select those that align with your learning goals.
- Follow the tutorials and complete the exercises.
Bayesian Networks Drills
Show steps
Practice using Causal Bayesian Networks and Partial Dependence Plots to improve marketing decision-making and gain insights.
Show steps
Show steps
Show steps
- Review the basics of Bayesian networks.
- Solve practice problems using Causal Bayesian Networks.
- Interpret the results of your analysis.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Collaborative Time Series Forecasting
Show steps
Collaborate with peers to analyze time series data, make predictions, and improve forecasting accuracy.
Browse courses on
Time Series Forecasting
Show steps
Show steps
Show steps
- Split into groups of 2-3 learners.
- Select a time series dataset to analyze.
- Use Dynamic Bayesian Networks to forecast the future values.
- Present your findings to the group.
Marketing Data Visualization
Show steps
Develop a data visualization that effectively communicates marketing data and insights.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather and analyze marketing data.
- Choose appropriate visualization techniques to present the data.
- Design and create the data visualization.
- Present the visualization to stakeholders.
Causal Forecasting Report
Show steps
Create a detailed report that demonstrates your understanding of causal forecasting and its applications in marketing.
Show steps
Show steps
Show steps
- Research causal forecasting techniques.
- Identify a specific marketing problem that can be solved using causal forecasting.
- Apply causal forecasting techniques to solve the problem.
- Write a report on your findings.
Data Analytics Challenge
Show steps
Participate in a competition to apply your data analytics skills and gain hands-on experience in solving real-world marketing problems.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Identify and register for a data analytics competition.
- Gather and analyze data to develop a solution.
- Build and evaluate a predictive model.
- Submit your solution and compete against other participants.
Career center
Learners who complete Time, Change, and Decisions for Marketing will develop knowledge and skills
that may be useful to these careers:
Market Research Analyst
Market Research Analyst
Market Research Analysts help companies understand their customers and the overall market. They design and conduct surveys, analyze data, and provide recommendations to help companies make better decisions about their products, services, and marketing campaigns. This course provides a strong foundation in data analysis and interpretation, which are essential skills for Market Research Analysts. Additionally, the course covers topics such as customer behavior and market trends, which are important for understanding the changing needs of customers.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for planning and executing marketing campaigns. They develop marketing strategies, manage budgets, and track results. This course provides a comprehensive overview of marketing principles and practices, and it covers topics such as customer segmentation, targeting, and positioning. The course also provides training in data analysis and interpretation, which are essential skills for Marketing Managers.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. This course provides a strong foundation in product management principles and practices, and it covers topics such as product development, marketing, and customer feedback. The course also provides training in data analysis and interpretation, which are essential skills for Product Managers.
Marketing Consultant
Marketing Consultant
Marketing Consultants help businesses develop and execute marketing strategies. They provide advice on a variety of topics, such as market research, customer segmentation, and marketing campaigns. This course provides a comprehensive overview of marketing principles and practices, and it covers topics such as customer behavior, market trends, and data analysis. The course also provides training in consulting skills, which are essential for Marketing Consultants.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. This course provides a strong foundation in data analysis techniques, and it covers topics such as data mining, statistical analysis, and data visualization. The course also provides training in data management and interpretation, which are essential skills for Data Analysts.
Business Analyst
Business Analyst
Business Analysts help businesses improve their performance by identifying and solving problems. They use data analysis and other techniques to understand business processes and recommend solutions. This course provides a strong foundation in business analysis techniques, and it covers topics such as process mapping, data analysis, and systems analysis. The course also provides training in communication and presentation skills, which are essential for Business Analysts.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They work in a variety of industries, such as finance, insurance, and healthcare. This course provides a strong foundation in quantitative analysis techniques, and it covers topics such as regression analysis, time series analysis, and forecasting. The course also provides training in data management and interpretation, which are essential skills for Quantitative Analysts.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve complex business problems. They work in a variety of industries, such as manufacturing, transportation, and logistics. This course provides a strong foundation in operations research techniques, and it covers topics such as linear programming, simulation, and queuing theory. The course also provides training in data management and interpretation, which are essential skills for Operations Research Analysts.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks to businesses. They use data analysis and other techniques to understand the likelihood and impact of risks. This course provides a strong foundation in risk analysis techniques, and it covers topics such as risk assessment, risk management, and risk mitigation. The course also provides training in data management and interpretation, which are essential skills for Risk Analysts.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze the financial performance of companies. They make recommendations to investors and other stakeholders about whether to buy, sell, or hold stocks. This course provides a strong foundation in financial analysis techniques, and it covers topics such as financial statement analysis, valuation, and investment analysis. The course also provides training in data management and interpretation, which are essential skills for Financial Analysts.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risks and make financial decisions. They work in a variety of industries, such as insurance, pension funds, and healthcare. This course provides a strong foundation in actuarial science techniques, and it covers topics such as risk assessment, premium pricing, and investment analysis. The course also provides training in data management and interpretation, which are essential skills for Actuaries.
Statistician
Statistician
Statisticians use data to collect, analyze, and interpret data. They work in a variety of industries, such as research, healthcare, and government. This course provides a strong foundation in statistical techniques, and it covers topics such as data collection, data analysis, and data visualization. The course also provides training in data management and interpretation, which are essential skills for Statisticians.
Data Scientist
Data Scientist
Data Scientists use data to solve complex business problems. They use a variety of techniques, such as machine learning, artificial intelligence, and data mining. This course provides a strong foundation in data science techniques, and it covers topics such as data preprocessing, data mining, and machine learning. The course also provides training in data management and interpretation, which are essential skills for Data Scientists.
Software Engineer
Software Engineer
Software Engineers design, develop, and test software applications. They work in a variety of industries, such as technology, finance, and healthcare. This course may be helpful for Software Engineers who want to learn more about data analysis and interpretation. The course covers topics such as data mining, statistical analysis, and data visualization.
Web Developer
Web Developer
Web Developers design and develop websites. They work in a variety of industries, such as technology, marketing, and education. This course may be helpful for Web Developers who want to learn more about data analysis and interpretation. The course covers topics such as data mining, statistical analysis, and data visualization.
For more career information including salaries, visit:
OpenCourser.com/course/1li8np/time
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Time, Change, and Decisions for Marketing.
In this book, Kjærulff introduces you to Bayesian networks and decision graphs. This valuable resource to reference to provide you with deeper insight into the concepts presented in the course. It useful book to have for reference as you continue to develop your skills in this area.
Is an authoritative resource for those who want to learn more about reinforcement learning. As a reference, it would be a good addition to your library if you plan to delve deeper into this area.
Save
Provides a nice introduction to Markov chains. It valuable resource to have to continue to reference throughout your career. It is commonly used by students and professionals alike.
Is another good reference for you to have in the area of dynamic Bayesian networks. It gives a good overview of the topic and is commonly used in academic settings.
Neal's book provides a thorough review of Bayesian learning for neural networks. will provide you with additional background knowledge to support the concepts presented in the course.
Save
Good introduction to predictive analytics. Siegel provides a good overview of the field and the techniques used in practice.
Good overview of data analytics for those who are new to the field. It covers a wide range of topics and is easy to understand.
Provides a good overview of the concepts and technologies used in customer relationship management. It useful resource for anyone who wants to learn more about this topic.
Save
Classic textbook on marketing management. It provides a comprehensive overview of the field and valuable resource for marketing professionals and students alike.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1li8np/time
Share
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Effort
3 weeks with 3-5 hours per week.
Level
Intermediate
Via
Coursera
Institution
University of Colorado System
Instructors
A.W. Lukens
Tony Cox, Jr.
Language
English
This course belongs to a
collection
called
Data Science for Marketing. It's comprised of four courses:
- Machine Learning for Marketers
- Time, Change, and Decisions for Marketing (viewing)
- Regression Modeling for Marketers
- Customer Data Analytics for Marketers
Good to know
Explores marketing strategies from the lens of advanced analytics techniques
Imparts valuable skills and knowledge to steer data-driven marketing initiatives effectively
Covers crucial topics including Bayesian Networks, Time Series Forecasting, and Optimization for strategic decision-making
Suitable for marketing professionals, data analysts, and aspiring leaders seeking to enhance their understanding of data-driven marketing
Provides practical applications of advanced analytics in real-world marketing scenarios
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