When I first learned the dot product and the cross product in $\mathbb{R}^3$ I spent some time understanding when I would like to use them. After some time I understood that the dot product usefulness was its ability to detect orthogonality and its relationship with projections. In the same manner that the cross product gives means to deal with areas.
Now in multilinear algebra I've learned about the wedge product of vectors defined in the tensor algebra. The definition I have is that if $T(V)$ is the tensor algebra of the space $V$, we let $J$ be the ideal generated by all elements of the form $T-\operatorname{sgn}(\sigma)f_{\sigma}(T)$ for each $T\in T^k_0(V)$, $\sigma\in S_k$ and $k\in \mathbb{N}$ and we set $\Lambda(V) = T(V)/J$. The wedge product is then the product of this algebra, given by means of $(T+J)\wedge(S+J)=T\otimes S + J$ from where it follows bilinearity, skew-commutativity and so on.
This is hardly used on differential geometry and Physics, so that there should be some intuition on when to use the wedge product. I've also been able to see that if we are in $\mathbb{R}^2$, then $v\wedge w = \det(A)e_1\wedge e_2$ with $A$ being the matrix whose columns are $v$ and $w$. In that case, $v\wedge w$ is the area spanned by $v$ and $w$ times this $e_1\wedge e_2$ so we could think of it as a piece of plane.
However, in other cases this doesn't work apparently. So, when we use the wedge product? What it is supposed to represent?