Why is the intercept negative. Does it mean that one sub increase would mean a revenue increase of 24.4
The negative intercept does not mean "that one sub increase would mean a revenue increase of 24.4". The slope coefficient means something like that (but different to it). The negative intercept tells you where the linear model predicts revenue (y) would be when subs (x) is 0.
Your question appears to be prompted by confusion about the fact that in your fitted model, $E(Y|x=0)\neq 0$, even though logically, you would expect no revenue then.
This situation is not only common, it's to be expected. You normally cannot expect a relationship identified on data over a limited range to be appropriate everywhere, and so you should beware putting any real meaning on the fitted value at 0 unless your $x$ values encompass 0 (at which point you'll likely see that in fact revenue is much closer to what you'd expect there).
The assumption of linearity of relationship between $y$ and $x$ might be reasonable over the range of your x values, but that gives no basis on which to extrapolate outside the range of your data.
We don't really know what's going on in the green part.
Nevertheless you should check that assumption of linearity within the range of your data, via a residual plot.
[Even when you have good reason to fit a linear model to data that extends over the entire range of possible values of $x$ - including 0 - and to expect that $E(Y|x=0)= 0$ it's still pretty common practice to fit an intercept.]