Machine learning in marketing: models and applications
Machine learning in marketing uses models developed from data to classify behaviour, identify groups and estimate outcomes. Understanding how they work helps assess which problems they can address and their limitations.
Supervised learning
Models are developed using examples associated with known outcomes.
Unsupervised learning
Techniques look for structures or relationships in data without necessarily using predefined labels.
Marketing applications
- Segmentation.
- Demand forecasting.
- Customer analysis.
- Classification.
- Campaign support.
How do I evaluate the results?
Use test data and metrics appropriate to the problem.
Where to go next
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You can connect this topic with predictive marketing, business intelligence for marketing, big data marketing.
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