Understanding of clouds is instrumental in interpreting current and future spectroscopic observations of exoplanets. Modelling clouds consistently is complex, since it involves many facets of chemistry, nucleation theory, condensation physics, coagulation, and particle transport. We develop a simple physical model for cloud formation and transport, efficient and versatile enough that it can be used in modular fashion for parameter optimization searches of exoplanet atmosphere spectra. The transport equations are formulated in 1D, accounting for sedimentation and diffusion. The grain size is obtained through a moment method. For simplicity, only one cloud species is considered and the nucleation rate is parametrized. From the resulting physical profiles we simulate transmission spectra covering the visual to mid-IR wavelength range. We apply our models towards KCl clouds in the atmosphere of GJ1214 b and towards MgSiO3 clouds of a canonical hot-Jupiter. We find that larger cloud diffusivity $K_{zz}$ increases the thickness of the cloud, pushing the $tau=1$ surface to a lower pressure layer higher in the atmosphere. A larger nucleation rate also increases the cloud thickness while it suppresses the grain size. Coagulation is most important at high nuclei injection rates ($dotSigma_n$) and low $K_{zz}$. We find that the investigated combinations of $K_{zz}$ and $dotSigma_n$ greatly affect the transmission spectra in terms of the slope at near-IR wavelength (a proxy for grain size), the molecular features seen at ~1micr (which disappear for thick clouds, high in the atmosphere), and the 10micr silicate feature, which becomes prominent for small grains high in the atmosphere. The result of our hybrid approach -- aimed to provide a good balance between physical consistency and computational efficiency -- is ideal towards interpreting (future) spectroscopic observations of exoplanets.
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