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3. Dividing a broader customer base into smaller groups based on similar traits.
4. Implementing measures to safeguard data from breaches and cyber-attacks.
6. Actionable, valuable information derived from data analysis.
9. A type of data source like social media or third-party providers.
10. Insight and understanding gained from information.
12. One of the 5Vs, referring to the different types of data.
14. Analytics used to assess performance and forecast outcomes in money matters.
17. Proper handling of sensitive data, especially PII, to protect from unauthorized access.
19. The type of analytics that examines causes of past outcomes.
23. The type of analytics that provides recommendations for future actions.
25. A type of data source like CRM or ERP systems.
27. Predicted net profit a company expects from a customer over their relationship.
28. Ethical consideration concerning openness about how data is used.
29. One of the 5Vs, referring to the speed of data generation and processing.
30. Using data and statistical methods to uncover insights and trends.

1. Processed, organized data that has meaning.
2. Planning, executing, and monitoring marketing efforts across channels.
5. Analysis to understand why customers are leaving and develop retention strategies.
7. Major regulation governing data privacy in the EU.
8. Selecting specific customer segments for tailored marketing efforts.
11. The type of analytics that summarizes past data.
12. One of the 5Vs, referring to the amount of data generated.
13. Raw, unprocessed facts and figures.
15. Analytics used to measure and optimize campaign performance.
16. Crafting a unique value proposition in the mind of the target audience.
18. Models that identify which marketing channels contributed to a conversion.
20. Scoring model used to evaluate the trustworthiness of individuals or businesses for loans.
21. The type of analytics that forecasts future events.
22. One of the 5Vs, referring to the worth of data in deriving insights.
24. One of the 5Vs, referring to the accuracy and trustworthiness of data.
26. A characteristic of high-quality data; correctness.