Business Simulations With Python
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Business Simulations With Python
Using Monte Carlo to Explore Customer Lifetime Value and Customer Acquisition Cost
As I wrote this post on business strategy for data scientists , I realized it might be fun to run a simulation for a marketing campaign and the cohort of new customers that it produces.
A lot of my professional life has been spent in the world of finance and investing. I’m more used to thinking about companies as a whole (analyzing them at the aggregate level) than on a day to day level. But I do find the more granular details really interesting. After all, what’s a whole if it’s not the sum of its parts?
A great way to learn more about something is to simulate it (with reasonable inputs and assumptions) and then study the results.You will often be surprised by how seemingly simple interactions among a few key variables can produce some surprising results. So let’s use Python to simulate a marketing campaign and see what happens.
We will focus our simulation on customer lifetime value (CLTV) and customer acquisition cost (CAC), the key metrics of many a startup(and public companies as well). In my previous business strategy post, I explored these metrics in depth conceptually, so please refer to it if you want more background.
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