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(1) Background: Privacy usability in IoT smart home companion applications remains an underexplored domain despite mounting regulatory requirements and accelerating user adoption. Heuristic evaluation offers a scalable pathway to privacy usability assessment, yet validated frameworks for applying such methods in real industrial settings are scarce. This study presents the first empirical application of the ABCDE Privacy Framework, a ten-heuristic instrument grounded in Nielsen’s usability principles and Privacy by Design, to an IoT companion application developed with a major European home appliance manufacturer. (2) Methods: A structured workshop was conducted with a multidisciplinary team of seven participants (five industry professionals and two researchers) following a two-round protocol: a qualitative heuristic discussion phase (Round 1) and an individual scoring phase (Round 2). Data were analysed through MAXQDA. (3) Results: Average heuristic scores ranged from 3.6 (H9: error recovery) to 4.8 (H6: recognition; H10: documentation), with an overall mean of 4.32. Six second-order themes were identified, including Transparency Asymmetry, Centralised but Decontextualised Privacy, and Shared Household Complexity. (4) Conclusions: The ABCDE Privacy Framework is feasible, time-efficient, and analytically productive in real industrial contexts, generating design-relevant insights and enabling cross-role team alignment within a two-hour session. These findings support its potential as a scalable tool for Privacy by Design practice in IoT product development.