It’s just a double application of the two-event formula, first thinking of as a single event:
Any probability result that is true for unconditional probability remains true if everything is conditioned on some event.
You know that by definition, $$P(A\mid B) = \frac{P(A\cap B)}{P(B)}\tag{1}$$ and so if we condition everything on $C$ having occurred, we get that $$P(A\mid (B \cap C)) = \frac{P((A\cap B)\mid C)}{P(B\mid C)}\tag{2}$$ which is the result that puzzles and surprises you; you think it should be $$P(A\mid (B \cap C)) = \frac{P(A\cap B \cap C)}{P(B\cap C)}.$$
So, let's start by setting $D = B\cap C$ write $P(A\mid (B \cap C)) = P(A\mid D)$ as in $(1)$ to get \begin{align} P(A\mid (B \cap C)) &= P(A\mid D)\\ &= \frac{P(A\cap D)}{P(D)}\\ &= \frac{P(A\cap (B \cap C))}{P(B\cap C)}\\ &= \frac{P(A\cap B \cap C)}{P(B\cap C)}\tag{3}\end{align} which is what you think the result should be. But observe that if you multiply and divide the right side of $(3)$ by $P(C))$, you can get \begin{align} P(A\mid (B \cap C)) &= \frac{P(A\cap B \cap C)}{P(B\cap C)}\times \frac{P(C)}{P(C)}\\ &= \dfrac{\dfrac{P(A\cap B \cap C)}{P(C)}}{\dfrac{P(B\cap C)}{P(C)}}\\ &= \dfrac{P(A\cap B \mid C)}{P(B\mid C)} \end{align} which is just $(2)$. In short, the intuition about $(2)$ is that it is just $(3)$ (which you agree with) re-written in terms of conditional probabilities conditioned on the same event $C$.
Just draw the Venn diagram. We then have $$\Pr[A \cap B \mid C] = \frac{\text{"1"}}{\text{"C"}}, \quad \Pr[B \mid C] = \frac{\text{"1"} + \text{"2"}}{\text{"C"}}, \quad \Pr[A \mid B \cap C] = \frac{\text{"1"}}{\text{"1"} + \text{"2"}},$$ and the relationship follows by dividing the first expression by the second.
