Learn how much historical data is needed to start with machine learning. Then, capture your most valuable business outcomes.
In order to make predictions, machine learning requires historical data which is from a wide enough time frame to generally capture all kinds of variation you’d expect.
This data should be stored in a spreadsheet, that has:
You run an online, subscription-based product. But users are cancelling their subscriptions. You want to predict this ahead of time, and implement strategies to retain those users.
To do this with machine learning:
Ask yourself: given enough time and memorization, could an intelligent human find the factors they need to make strong predictions given only your data? If so, there's a very good chance machine learning can as well.
Once you have that data, you’ll need to process it.
So how should you format your data to get maximum power out of machine learning?