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Optimisation using Julia
While planning their marketing campaigns, our clients had to understand how their marketing spend affects their KPIs. We created models to understand the effect of individual marketing channels such as TV, Radio, Digital etc on KPIs like sales, qualified reach or profits. We had to help them to build optimised brand plans and campaign plans that use the allocated budget effectively.
Knowing how the marketing spend affects the KPIs enables us to optimise the marketing spend for maximal result. We also had to suggest the optimal plan to achieve desired business outcomes within user defined constraints, e.g. user defined % range of permitted spend changes.
We used Adbudg S-curves to optimise the marketing spends as they have several useful characteristics for optimisation and it is easier to find the point where the ROI is maximised. Using the response curves for each of the individual channels (TV, Radio, Digital), we could find the optimal spend for each individual channel with an easy to solve optimisation problem. The result is an optimal marketing mix that maximizes the chosen KPIs.
In this talk we will delve into how to find the optimal marketing mix using S-curves and Julia.
- Introduction to the Marketing domain and the optimisation problem
- Model and data considerations
- How we went about choosing Julia
- Walkthrough of the solution
- Challenges faced
Basic understanding of Data Sciences
Ginette is working as Senior Developer at ThoughtWorks for 9 years. She has worked on solving problems across multiple domains like retail, marketing and publishing.