Customer Insights and Marketing with AI

Course contents (13 parts)

1. 1

   Pre-course assessment

   Check your starting knowledge before learning

2. 2

   What is Data Science?

   Lesson video

3. 3

   Start with a Decision

   Start with a decision, such as which group needs more information or where prospects drop off. Specify the group, timeframe, and next action. Distinguish behavior from motivation, since a click does not reveal feelings. AI can suggest questions, but check that wording is not leading. If no decision would change based on the answer, refine the question before investing in data collection…

4. 4

   Choose Sources and Check Quality

   Surveys, support records, campaigns, and transactions reflect different groups and time periods. Check collection methods, duplicates, missing values, and definitions before combining them. Note missing or unrepresentative groups. Use only necessary data and minimize identifiers before AI; respect rights and stated purpose. If data cannot answer the question, collect more or speak with customers…

5. 5

   Organize Customer Feedback

   AI can suggest feedback categories, but people must review them. Use samples with identifiers removed; request category names and definitions, then check examples across groups. Sarcasm or dialect may be lost…

6. 6

   Separate Insights from Hypotheses

   Separate observations, interpretations, and proposals. For example, checkout drop-off is an observation, while concern about shipping costs is a hypothesis. Check the metric, period, sample size, and source figures. Correlation does not establish cause. AI can suggest other perspectives, but analysts should state what is known, unknown, and what evidence is needed…

7. 7

   Experiment and Learn

   Turn a finding into an experiment with a hypothesis, comparison group, primary metric, and guardrail metric. Set the test period in advance and control other factors. Do not stop at an early positive result or generalize from a small sample…

8. 8

   Applied case study and evidence review

   Summarize a small feedback set before changing service

9. 9
   Document0 points1 min

   Course study guide

   A practical guide to the course lessons, with Thai and English editions.

10. 10
    Document0 points1 min

    Practical workbook

    Course-based exercises for review and planning a small real-world trial.

11. 11
    Document0 points1 min

    Quick reference

    A concise reference to course topics and review points for use while working.

12. 12
    Document0 points1 min

    Implementation planner

    A template for connecting course topics to goals, owners, and evidence of results.

13. 13

    Post-course assessment

    Eight scenario questions reviewing practical application.