Unlocking certainty in commercial development A data-driven experiential retail strategy for Cairo’s coffee sector

Abstract

Rapid advances in digital technologies and intensified competition have increased uncertainty in retail investment decisions, particularly where product differentiation is limited. In Cairo’s coffee shop sector, experiential and phygital features are increasingly adopted, yet their investment value remains insufficiently quantified. This study applies a contingent valuation approach within a pre-investment hedonic valuation framework to evaluate experiential retail interventions prior to implementation. Eleven hypothetical phygital scenarios were assessed across three experiential categories using an online survey of 100 consumers. Conditional probability, Bayesian probability modeling, and association rule mining were integrated within a Contingent Valuation–Machine Learning (CVML) framework. Results show selective market acceptance, with a 44.9% average adoption rate and a 2.22 × willingness to pay premium among adopters. Immersive sound-zoned environments, nutrition and calorie information, and smart pick-up shelves consistently emerged as priority investments. The CVML framework enables experiential retail strategies to be evaluated before capital commitment, reducing pre-investment risk and supporting data-driven decision-making.