Hi Everyone,
The topic I'm getting tripped up on right now is forecasting future sales rep commissions based on total sales amounts. I am not super familiar with the R Predictive Tools so I would appreciate some help. How do I go about doing this?
Note that in the output, I am more concerned about an estimated total sales rep commission amount than I am about an estimated distributor sales amount, but if I can get both that would be great.
Thanks!
Here is the example fake data:
Input (Historical Data):
Quarter | Total Distributor Sales ($) | Total Sales Rep Commission Amount |
2021-Q1 | 100000000 | 575000 |
2021-Q2 | 105000000 | 590000 |
2021-Q3 | 105000000 | 600000 |
2021-Q4 | 125000000 | 650000 |
2022-Q1 | 106000000 | 700000 |
2022-Q2 | 95000000 | 650000 |
2022-Q3 | 120000000 | 750000 |
2022-Q4 | 130000000 | 700000 |
2023-Q1 | 121000000 | 800000 |
Desired Output (Forecast):
Quarter | Total Distributor Sales ($) | Total Sales Rep Commission Amount |
2023-Q2 |
| |
2023-Q3 |
| |
2023-Q4 |
| |
2024-Q1 |
| |
2024-Q2 |
| |
2024-Q3 |
| |
2024-Q4 |
|
Hi @Miles_Waller ,
the best way for you to get started with this is to try the example workflows using the AMIRA and ETS tools. You can access this by right-clicking on either one and selecting "open example":
This will walk you through how they work.
You have the data in the right format, in that each row represents the time series element (period) you wish to predict.
There are more resources here:
https://help.alteryx.com/20231/designer/time-series
https://help.alteryx.com/2018.3/ToolCategories/TimeSeries.htm
I hope this helps,
M.