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Data Science in Marketing: Hands-on Uplift Modelling with Python
Learn how to use causal machine learning to maximise ROI for marketing campaigns
This is the second article in my series on Data Science in Marketing. The first article can be found below.
Offers and promotions are widely used in marketing campaigns. Discount vouchers, incentives, and giveaways are common interventions designed to generate actions, like purchasing or renewing a service subscription.
Marketing teams usually have a limited budget, and for that reason may not want to provide every customer with an offer. Typically marketing teams will identify segments of customers to target and this is often achieved using models like Churn Prediction or Customer Lifetime Value (CLV).
These techniques are all useful but none of them address the true challenge. A customer with a high churn propensity or high CLV may very well not respond to an offer, and in some cases, sending an incentive to these customers may trigger them to leave you. To ensure the highest rate of success, marketing teams should focus on sending offers to those customers who are most receptive to the promotion.
