Submarine slope channel systems have complicated three‐dimensional geometries and facies distributions, which are challenging to resolve using subsurface data. Outcrop analogues can provide sub‐seismic‐scale detail, although most exhumed systems only afford two‐dimensional constraints on the depositional architecture. A rare example of an accessible fine‐grained slope channel complex set situated in a tectonically quiescent basin that offers seismic‐scale, down‐dip and across‐strike exposures is the Klein Hangklip area, Tanqua‐Karoo Basin, South Africa. This study investigates the three‐dimensional architecture of this channel complex set to characterise the stratigraphic evolution of a submarine channel‐fill and the implications this has for both sediment transport to the deep‐oceans and reservoir quality distribution. Correlated sedimentary logs and mapping of key surfaces across a 3 km2 area reveal that: (i) the oldest channel elements in channel complexes infill relatively deep channel cuts and have low aspect‐ratios. Later channel elements are bound by comparatively flat erosion surfaces and have high aspect‐ratios; (ii) facies changes across depositional strike are consistent and predictable; conversely, facies change in successive down depositional dip positions indicating longitudinal variability in depositional processes; (iii) stratigraphic architecture is consistent and predictable at seismic‐scale both down‐dip and across‐strike in three‐dimensions; (iv) channel‐base‐deposits exhibit spatial heterogeneity on one to hundreds of metres length‐scales, which can inhibit accurate recognition and interpretations drawn from one‐dimensional or limited two‐dimensional datasets; and (v) channel‐base‐deposit character is linked to sediment bypass magnitude and longevity, which suggests that time‐partitioning is biased towards conduit excavation and maintenance rather than the fill‐phase. The data provide insights into the stratigraphic evolution and architecture of slope channel‐fills on fine‐grained continental margins and can be utilised to improve predictions derived from lower resolution and one‐dimensional well data.