To foster long-lasting satisfaction with and loyalty to their services, it is imperative that transit agencies understand, and make decisions in accordance with, customer needs and preferences. Since it is usually infeasible for agencies to tailor actions at the scale of the individual, an alternative strategy is to conduct a market segmentation analysis on one or more data sources to identify sufficiently similar groups of transit riders to consider within a decision-making process.

Challenges arise in terms of selecting both the variables to consider in a segmentation analysis and the methodological approach. One potential approach is to use predetermined (a priori) segments, identifying a set of characteristics at the outset that might represent important differences among transit customers, and creating segments based on these (for example, commuters versus non-commuters or suburban versus central-city riders). An alternative is to use market-defined (post-hoc) methods, using statistical clustering and classification methods to identify groupings that may not be apparent from surface-level examination. These data-driven strategies are useful in that they can assist decision-makers in discovering key differences within groups defined by one or more sociodemographic characteristics.

The quintessential TCRP report on this topic, published in 1998, is TCRP Report 36: A Handbook: Using Market Segmentation to Increase Transit Ridership. The purpose of this report was to introduce the “whats” and “whys” of market segmentation, including several case studies on how to appropriately plan for and research the development of a suitable segmentation scheme and then implement findings into actionable strategies that fulfill the transit agency’s goals of increasing ridership, bringing in new customers, and boosting satisfaction levels of different groups of users. In the 25 years since the publication of the 1998 Handbook, scholars in the business, social, and mathematical sciences have published new research with relevance to this topic. Moreover, passive data collection and “big data” sources have become more widely implemented and available for profiling transit customers, and the rise in remote work, which has accelerated in the wake of the COVID-19 pandemic, has challenged conventional thinking about typical rider segments. A targeted census of approaches to collecting data, extracting and describing segments, and tailoring product and service decisions to the needs and preferences of transit market segments would allow for the dissemination of success stories and potential pitfalls surrounding forward-thinking market segmentation practices, in addition to how agencies might benefit from adopting certain practices under various scenarios.

The objective of this research is to deliver a comprehensive update on market segmentation strategies and best practices in the form of a handbook that mirrors and expands on the content of TCRP Report 36. This handbook will draw on both multidisciplinary academic literature and real-world case studies at public- and private-sector organizations in the public transit realm.