What is the best way Reinforcement learning, RNN or others to predict the best action we have to take to maximize sales?

I have a dataset composed of few features :

customerId, actionDay1, SalesDay1, actionDay20, SalesDay20, actionDay30, SalesDay30

action can be :

• call
• email
• face 2 face
• nothing

sales : amount of sales in \$

my goal here is to predict the best action we have to take in any day (1, 20 or 30) to sale more.

some customer prefers email, some prefer to be called every time, some others prefer to not be contacted to buy.

the pattern is different for each customer. my first thought was to apply reinforcement learning for this problem, but I found some difficulty to do the right environment, but also the reward function. a reinforcement learning would work without data and the model will be different for each customer. I would like to have a model that can approximate the behavior of all customers using the dataset I have.

does anyone have an idea on how I can approach this problem using reinforcement learning or something different like Recurrent Neural Net?

• I understand that you've already explored the patterns route in the customers' response and did not find any. And now you want to try the Reinforcement learning route. Answer to your question will be surely interesting. Good Luck! Jul 9 '19 at 15:41
• What kind of information on the client are you planning to use? just the id or some other info ? like a profile of a user and not the exact user himself Aug 9 '19 at 13:16