Farmer households employ various coping strategies to address climate and non-climate shocks, which are primarily categorized into production-focused and consumption-focused approaches. While the former has been extensively remarked on in recent studies, the latter has received little attention in the literature. In this study, we developed consumption-focused coping strategies by balancing the likelihood of household shock exposure with welfare outcomes for 1369 farmer households in Senegal. The outcomes are estimated using a discrete choice model regression. We then modeled the challenges faced by Senegalese farmer households using a Data Envelopment Analysis (DEA) approach, enabling us to measure household efficiency in achieving balanced gains. The household shock exposure regression equation results confirmed the role of food and non-food factors in controlling the probability of shock; however, outcomes may vary across households, particularly in expenditure items linked to lifestyle transformations. The DEA results revealed a non-linear relationship between shock exposure probability and efficiency scores, explaining the variability observed in household expenditure outcomes. Excitingly, the nonlinear impact of shock efficiency was rarely observed for food expenditure items, highlighting an unexpected resilience in this crucial area. These results indicate that policies aimed at improving consumption-based welfare should be differentiated rather than uniformly applied. The empirical findings show relatively consistent responses in food consumption across households, supporting the use of broadly implemented food-related assistance and nutrition security programs. In contrast, nonfood consumption responses exhibit substantial heterogeneity, particularly for health, education, and mobility-related expenditures. Accordingly, interventions targeting these domains should be tailored to household characteristics and efficiency levels to more effectively buffer welfare losses under economic and environmental shocks.