Let us consider i.i.d. random variables $\{a_k,b_k\}_{k \geq 1}$ defined on a common probability space $(Ω, \mathcal F, \mathbb P)$, following a symmetric Rademacher distribution and the associated random trigonometric polynomials $S_n(θ)= \frac{1}{\sqrt{n}} \sum_{k=1}^n a_k \cos(kθ)+b_k \sin(kθ)$. A seminal result by Salem and Zygmund ensures that $\mathbb{P}-$almost surely, $\forall t\in\mathbb{R}$ \[ \lim_{n \to +\infty} \frac{1}{2π}\int_0^{2π} e^{i t S_n(θ)}dθ=e^{-t^2/2}. \] This result was then further generalized in various directions regarding the coefficients distribution, their dependency structure or else the dimension and the nature of the ambient manifold. To the best of our knowledge, the natural question of the fluctuations in the above limit has not been tackled so far and is precisely the object of this article. Namely, for general i.i.d. symmetric random coefficients having a finite sixth-moment and for a large class of continuous test functions $φ$ we prove that \[ \sqrt{n}\left(\frac{1}{2π}\int_0^{2π} φ(S_n(θ))dθ-\int_{\mathbb{R}}φ(t)\frac{e^{-\frac{t^2}{2}}dt}{\sqrt{2π}}\right)\xrightarrow[n\to\infty]{\text{Law}}~\mathcal{N}\left(0,σ_φ^2+\frac{c_2(φ)^2}{2}\left(\mathbb{E}(a_1^4)-3\right)\right). \] Here, the constant $σ_φ^2$ is explicit and corresponds to the limit variance in the case of Gaussian coefficients and $c_2(φ)$ is the coefficient of order $2$ in the decomposition of $φ$ in the Hermite polynomial basis. Surprisingly, it thus turns out that the fluctuations are not universal since they both involve the kurtosis of the coefficients and the second coefficient of $φ$ in the Hermite basis.