Achieving consistent sensory quality in espresso is crucial for the coffee industry. So far, several work have been addressing this challenge, but remain some unexplored aspects such as deepening analysis by combining machines parameters information and consumers preferences. This study investigates the causal effects of deviations from target espresso machines parameters (water temperature, flow and pressure) on consumer-rated sensory attributes: Aroma, Bitterness, Concentration and Richness. Firstly, we tried to understand the correlation between the features and the final satisfaction of consumers, and secondly, combining datasets of consumer evaluations and machine parameters. We employed causal inference framework to estimate the Average Treatment Effect (ATE) of parameters on sensory outcomes using linear regression with backdoor adjustment. While the statistical analysis did not show significance regarding the conventional 0.05 alpha level, some trends were observed. Temperature deviation was the most influential parameter, positively affecting Aroma, Concentration, and Richness, while negatively affecting Bitterness. Robustness checks using placebo treatment, random common cause, and data subset refuters generally supported the findings. This research highlights the complexity of espresso extraction and the estimated influence of the deviation of the parameters on the features of this beverage, and the need for further research with larger datasets and consideration of other influential factors to fully elucidate the impact of brewing inconsistencies.