inflearn logo

First Steps in Marketing Data Analysis: A Practical Routine for Turning Numbers into Conclusions with ChatGPT

We help marketing practitioners solve the "having data but being unable to reach a conclusion" problem through a practical routine—spanning problem definition, analysis, interpretation, and one-page reporting—combined with the use of ChatGPT.

7 learners are taking this course

Level Beginner

Course period Unlimited

Excel PowerQuery
Excel PowerQuery
EDA
EDA
Data literacy
Data literacy
ChatGPT
ChatGPT
Excel PowerQuery
Excel PowerQuery
EDA
EDA
Data literacy
Data literacy
ChatGPT
ChatGPT

What you will gain after the course

  • You can define data-driven marketing problems using ChatGPT.

  • You can collect web data with Listly AI.

  • Data preprocessing can be done with Excel Power Query.

  • Exploratory data analysis can be performed with ChatGPT.

  • Text data analysis can be performed with ChatGPT.

  • You can perform statistical hypothesis testing and A/B test analysis with ChatGPT.

  • You can create a 'one-page marketing analysis report' that is ready for immediate submission in a professional setting.

First Steps in Marketing Data Analysis: A Practical Routine for Turning Numbers into Conclusions with ChatGPT


  • This course is designed to help you move past the "daunting first steps" and reach a level where you can answer business questions with data and support decision-making with a "one-page marketing analysis report."

  • Upon completing the course, you will be able to personally draft a one-page report containing core insights and actionable proposals, and confidently present it to your team leader or management.

After taking this course, you will be able to create these types of outputs

Statistical hypothesis testing results

Analysis of mean score differences by gender using T-test

Text Data Analysis: Sentiment Analysis Results

Distribution of review counts for positive/negative sentiments

Exploratory Data Analysis: Boxplot Results

Score distribution by age

Text Data Analysis: Text Length Analysis

Distribution of text length

1-page result report

Text data analysis results based on bank app reviews

1-page executive summary report

Online Advertising-Based A/B Test Results

  • After completing this course, you will have a basic understanding of data analysis and be able to conduct your own analyses.


  • Your fear of data will disappear, and you will be able to solve problems based on data.

What you will learn

Section (1) Course Introduction

Understand the overall flow of the lecture and the roles of the tools (Excel and ChatGPT), and complete the preparations to start the hands-on practice immediately.


Section (2) Converting Problems into Analytical Tasks

Transform marketing issues into measurable analysis questions and hypotheses (from an A/B perspective) to design the analysis so that it leads to decision-making.


Section (3) Data Collection and Preprocessing

  • Select the data required for problem definition, collect web/VOC data, and secure it in an analyzable format.

  • Check and correct missing values, duplicates, and formatting errors to create a reliable analysis table, and automate repetitive preprocessing tasks.


Section (4) EDA

Explore distributions, characteristics, and patterns through visualization to quickly understand the data structure and refine core questions.


Section (5) Hypothesis Testing and A/B Testing

Interpret A/B test results and draw conclusions using statistical judgment to distinguish between coincidence and actual differences.


Section (6) Text Analysis

Extract keywords, sentiments, and topics from reviews/VOC to structure the voice of the customer and derive improvement tasks.


Section (7) Insights & Reports

Condense the analysis results into 'Situation → Discovery → Interpretation → Recommendation' to create a one-page report that leads directly to decision-making.


Notes before taking the course

Practice Environment

  • Operating System and Version (OS): Windows, macOS

  • Tools used: Excel 2016 or higher and ChatGPT Plus


Learning Materials

  • Format of provided learning materials (Excel, CSV, PDF, prompt text, etc.)

  • Download Practice Data: Google Drive

Prerequisite Knowledge and Precautions

  • Essential prerequisite knowledge considering the learning difficulty: Experience using Excel and ChatGPT


Recommended for
these people

Who is this course right for?

  • Marketing/Sales practitioners with 3 to 7 years of experience who look at data but are unable to draw conclusions.

  • Office workers who know how to use Excel but feel overwhelmed by "analysis" (Beginner analysts/Data practitioners)

  • A team leader/leader who feels frustrated because reports lack a "basis for judgment"

  • A practitioner who uses ChatGPT but is new to data analysis

Need to know before starting?

  • It is good if you have experience using generative AI.

  • In the class, we primarily use the ChatGPT Plus version (paid) as a data analysis tool.

  • Excel Power Query is used for the data preprocessing part of the class.

  • We use Listly AI for web data collection in class. (Free sign-up)

Hello
This is datamindcoach

He is the CEO of ValueVine, a specialized data-driven business consulting firm, and is active as a data analyst, marketing consultant, and columnist.

He holds a PhD in Business Administration with a major in Marketing and possesses certifications as a First-Class Information Processing Engineer and a First-Class Big Data Specialist.

Major publications include "AI Personal Branding" (2025), "Data Literacy Starting with ChatGPT" (2025), "AI Data Analysis" (2024), "Habits for Developing a Data Mindset" (2024), "Branding in the Age of No Jobs" (2022), "Study Marketing Right Now" (2019), "Marketing Research" (2017), and "Korean-style Positioning" (2003).

He has been lecturing on data literacy, data-driven problem solving, big data analysis, marketing, and branding at institutions such as the National Human Resources Development Institute, Korea Institute of Financial Telecommunications & Clearings, Korea Productivity Center, Samsung Electronics, NongHyup, BNK Financial Group, Koscom, and Korea Water Resources Corporation.

He is currently contributing columns on data literacy to ≪Statistics Window≫ and on local brands to ≪Brand News≫.

More

Curriculum

All

21 lectures ∙ (6hr 34min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

Not enough reviews.
Please write a valuable review that helps everyone!

Similar courses

Explore other courses in the same field!

Limited time deal ends in 8 days

$2,508.00

69%

$50.60