Despite the abundance in methodologies for tourism demand modeling, most methods examine demand growth levels rather than growth patterns. The latter, however, can be of great value for destination management to minimize business risks and for authorities to prescribe effective policies. Meanwhile, describing demand growth as a simplex S-shaped life-cycle curve may oversimplify the heterogeneity in visitor flows. There is thus a need for methods that can identify market segments based on demand growth patterns to enable smart destination management strategies and provide theoretical insights. This article introduces a longitudinal profile analysis via multidimensional scaling (LPAMS) as an effective and easy to implement data-driven segmentation tool. This practitioner-friendly quantitative analytic tool is justified in the theoretical background of embracing complexity in business research, data disaggregation, and modeling interdependence in tourism forecasting. The conceptual and procedural details of LPAMS are explained at a level that is comfortably understood by researchers and practitioners, together with methodological comparisons with conventional methods. A demonstration of LPAMS is presented to identify five typical annual arrivals’ growth patterns of Australia’s 43 main inbound markets over 1991-2016. This study contributes to the methodologies for longitudinal tourism demand analysis and market segmentation techniques.