Not sure you can foercast anything good out fo your datas.
You have three incomplete record, for affiliates 4 5 and 6, (set of 0s)
You have affiliate 7 with values to low to distinguish a trend from variability.
Affiliate 1, 8 and 10 (and 3 up to august) show similiar 'up and down' variation from month to the next, while having different trends.
If this variations result from seasonal demand variation, then you can 'extract' that seasonality, remove it from the data, then extrapolate and re-apply the seasonal factors on the result.
But you would need at least two years history to know if it's seasonal effect or not.
If it's not seasonal effect, but rather identical reaction to demand change (promotions, competitors etc..), then you could still (barely) calculate and remove that effect to calculate a trend, but won't be able to predict future monthly value as you won't know how the demand change effect will be in the future, and it account for variations about 50% of the total.
If you normalize your data (divide each affiliate value by the serie max) and plot them, you will see there is no clear trend.
If you think there is some seasonality, and/or can put the hand on more years, I can tell you how to extract and use it.