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The accuracy of photometric redshifts (photo-zs) particularly affects theresults of the analyses of galaxy clustering with photometrically-selectedgalaxies (GCph) and weak lensing. In the next decade, space missions likeEuclid will collect photometric measurements for millions of galaxies. Thesedata should be complemented with upcoming ground-based observations to deriveprecise and accurate photo-zs. In this paper, we explore how the tomographicredshift binning and depth of ground-based observations will affect thecosmological constraints expected from Euclid. We focus on GCph and extend thestudy to include galaxy-galaxy lensing (GGL). We add a layer of complexity tothe analysis by simulating several realistic photo-z distributions based on theEuclid Consortium Flagship simulation and using a machine learning photo-zalgorithm. We use the Fisher matrix formalism and these galaxy samples to studythe cosmological constraining power as a function of redshift binning, surveydepth, and photo-z accuracy. We find that bins with equal width in redshiftprovide a higher Figure of Merit (FoM) than equipopulated bins and thatincreasing the number of redshift bins from 10 to 13 improves the FoM by 35%and 15% for GCph and its combination with GGL, respectively. For GCph, anincrease of the survey depth provides a higher FoM. But the addition of faintgalaxies beyond the limit of the spectroscopic training data decreases the FoMdue to the spurious photo-zs. When combining both probes, the number density ofthe sample, which is set by the survey depth, is the main factor driving thevariations in the FoM. We conclude that there is more information that can beextracted beyond the nominal 10 tomographic redshift bins of Euclid and that weshould be cautious when adding faint galaxies into our sample, since they candegrade the cosmological constraints.

Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses