I have a project with data of sales field officers who visit their customers and enter the progress details. Visit can be an order or any kind of customer interaction.
Let's say one sales guy has around 1000 customers, It's only natural that he might skip some customers which can result in loss overtime. So I have the data for the visits done by him since the customer was onboarded. What model should I use to check the old frequency of visits done by him and factors which are stated below so that I can say like:
"Do you want to get in touch with "this" customer. ?"
So basically by checking his previous interaction rate, In case if he forgot to visit, I need to recommend like that.
Data points are like:
- date/time - date when visit done
- remarks - what was discussed
- there is a status which is related to internal
- and some other customer details.
So what model should I use or which technique do you think is best suited for this problem. I'm fairly new in machine learning and kind of learning it by doing.