Summary

In this chapter, we have laid a concrete foundation for building data and AI/ML-driven marketing models and strategies. We have discussed commonly used marketing KPIs that not only help the business measure the marketing performance but also provoke action items for improvements based on the strengths and weaknesses discovered through multilevel analyses. Using an insurance product marketing dataset as an example, we have seen how these KPIs can be measured and analyzed with Python for further improvements and optimizations in future marketing efforts.

We have also discussed how various dashboarding tools, such as Tableau, Power BI, and Looker, can be used for reusable real-time KPI tracking. As everyone emphasizes, AI/ML starts with data and deep exploratory analysis to decide what to train AI/ML models with and what to optimize for. The items and KPIs covered in this chapter will come in handy when designing and developing advanced AI/ML models for marketing in the future...