Did you know that Uplift Modeling not only boosts marketing efficiency but also cuts costs? Today, let’s delve into Uplift Modeling with Senior Data Scientist J.J. Weerawan Sakdajivacharoen from SCB TechX, uncovering the following details:
The Uplift Model analyzes sales promotion history to predict outcomes and categorizes customers into 4 groups. This segmentation helps identify which groups should be targeted with marketing activities:
- Sure Things: Intentionally purchase regardless of marketing stimuli, hence don’t require marketing efforts.
- Persuadables: More likely to purchase when stimulated by marketing efforts.
- Lost Causes: Uninterested in the product from the start, so marketing efforts are unnecessary.
- Sleeping Dogs: Immediately respond negatively to stimuli, resulting in negative outcomes for the business.
Therefore, focusing marketing activities only on Persuadables, who respond to campaigns, helps save costs.
Effective Uplift Modeling Tips:
- Select relevant data.
- Choose appropriate experimental methods and trial group categorization (Control & Treatment), such as Randomized Controlled Trials (RCTs).
- Select models suitable for the data and business, e.g., Decision Tree, Neural Network, Random Forest, Gradient Boosting.
- Adjust parameters and feature selection, e.g., using Dimensionality Reduction to simplify model complexity.
- Utilize expertise from specialists to develop Uplift Models, reducing time and development costs.”
If you enjoy this content, please follow our page for updates. Thank you!Top of Form😊.
Lastly, SCB TechX is ready to provide any organization with professional advice, technology solutions, and comprehensive Data Platform services through TechX Data Platform.
If you are interested, please feel free to contact us at contact@scbtechx.io Or visit us for more details at https://bit.ly/3QjtHgl
