I am trying to forecast sales for a company that runs a few stores. In many cases, I am pretty successful using some basic methods in Excel to forecast sales for every month, but I'd like to be more successful when it comes to forecasting for both whole months and each day within the month.
I'm not sure what is the best approach and how far I should be reaching. Biggest everyday variables that impact sales include:
- month of the year
- day of the week
- week of the month
- is it a holiday? which?
- number of weekends in the month
- does payday land on beginning of month or end of last month
- number of same-store nearby
- number of competitor stores nearby
I could think of many more variables that impact sales, but this small list is more than my current forecasting tool, Excel, can handle.
Based on my current knowledge, I'd guess regression would be the way to go, but I wonder if machine learning would be a better option (have no idea if someone that doesn't know much about machine learning could get useful data within a couple of weeks or if that's something that takes years).
What is a good tool to learn to use for something like this, that doesn't require months of work to get the first meaningful results (I understand that any field could take years to master, but for me it would need to be useful pretty fast, even if mastered over a longer time)? I do some coding in PHP and use MySQL a lot. I am interested in learning Python if that's a good tool for that. But I am able to quickly learn to use most tools, just don't know where to start.