05

Question 1

Front

Answer 1

Back

Question 2

Role of Data in Marketing

Answer 2

Data helps to create accountability in marketing by proving if strategies are effective and efficient. Data skills are essential for modern marketers.

Question 3

Importance of Data Skills

Answer 3

Today, data skills can make or break a marketing career. Data literacy enables faster insights and decision-making.

Question 4

Six Steps for Data-Informed Decision Making

Answer 4

• Ask: Start with a question
• Acquire: Collect relevant data
• Analyze: Process data
• Apply: Use insights
• Announce: Communicate findings
• Assess: Monitor outcomes

Question 5

Types of Marketing Data

Answer 5

• Zero-party data: Voluntarily shared by customers
• First-party data: Owned by company
• Second-party data: Partner data
• Third-party data: External sources

Question 6

Big Data vs Small Data

Answer 6

Both big and small data provide valuable insights but only if data quality (e.g., accuracy, timeliness) is ensured.

Question 7

Survivorship Bias Example

Answer 7

Observed in WWII: Armour planes where they’re not hit to avoid survivorship bias, relevant in avoiding selection bias in marketing data analysis.

Question 8

Qualitative vs Quantitative Research

Answer 8

Qualitative: Focus groups, interviews
Quantitative: Surveys, experiments
Use mixed methods to gain deeper insights.

Question 9

Statistical Methods in Marketing

Answer 9

• Data Simplification: Cluster analysis, segmentation
• Linking Variables: Predictive modelling
• Resource Optimisation: Linear programming for optimal resource use

Question 10

Generative Modelling in Marketing

Answer 10

Generative models like ChatGPT help generate new insights by discovering patterns and simulating data.

Question 11

Data-Driven Decision Options

Answer 11

• Support: Human makes decision
• Augmentation: System recommends options
• Automation: System decides without human intervention

Question 12

Data Storytelling Structure

Answer 12

Effective storytelling in data includes data, visuals, and narrative to drive change using a three-tier structure: setup, conflict, resolution.

Question 13

Pitfalls in Data-Driven Decision Making

Answer 13

• Ask: Wrong questions
• Acquire: Ignoring data quality
• Analyze: Wrong metrics
• Apply: Poor process definition
• Announce: Assumed acceptance
• Assess: Lack of timely updates