Data has become an essential part of marketing. But with the increase in the data available, new analytics techniques are required to get the most out of it.
Recently, a new discipline, data science, has emerged which promises to help marketers leverage their data to improve results. But how does data science apply to marketing? And how can marketers use it to improve their results?
In this course, Data Science for Marketers, we will first explore what data science is and what it can do for marketers. Then, we will walk through each stage of the data science process, with plenty of hands-on exercises along the way.
WHO SHOULD ATTEND
This course would benefit anyone who is involved in marketing and wants to learn about innovations in analytics and how to apply them
While there is no specific math background required, the course will be covering statistics and spreadsheets will be used throughout the day.
HOW WILL I BENEFIT
By the end of the one-day course, you will
1. Understand the importance of data science and how it applies to marketing
2. Be able to plan a well-structured data science project and
3. Deliver new data-driven insights to your business.
WHAT WILL I LEARN
Why data science?
- The importance of using data to make business decisions
- The role of statistics and analytics
- The data science process
- Data science vs. data analytics
The goals of using data science for marketer
- Understanding customers
- Improving marketing strategies
- Enhancing marketing performance
Getting the data
- Identifying what data you need for marketing
- Statistical methods which are most useful for marketing
- The data scientist toolkit
Exploratory data analysis
- Summarizing marketing data
- Using data visualization to discover new relationships
- Describing the distributions of data
- Analyzing customer behaviour using linear regression
- Churn analysis using logistic regression
- Creating new segments with clustering
- Understanding A/B tests
Data science practical
In the final section, participants will complete a data science project including collecting, analyzing, modeling and presenting results.
- 22 Jan22 Jan
22 Jan - 22 Jan
Tuesday - Tuesday
- 05 Apr05 Apr
05 Apr - 05 Apr
Friday - Friday