Path Data in Marketing: An Integrative Framework 

The authors define paths as “records of consumer movements in a spatial configuration” or as “a conscious agent’s movement in a physical or simulated environment that is observable”. 

As part of the suggested framework, two primary dimensions are identified: “characteristics of spatial configuration” and “the agent”. Specific characteristics of the actual spatial configuration, either if it is physical or nonphysical, continuous or discrete, as well as the existence of constrains, will influence the model and the approach of the analysis. Defining agent factors such as the level of (1) “social interaction”, (2) ”goal-directedness” and (3) “forward-looking-behavior” should also be considered. 

Based on literature review, references to relevant related research sources are introduced. Several examples in the context of “retail/service environments”, “advertising studies”, “e-commerce”, “experimental research” and areas outside marketing are also considered. In the next section important operational issues, considerations and restrictions for researchers working with any form of marketing path are identified.

Finally, the authors conclude on potential directions of future research in the field.

Diverse backgrounds, concerns, areas of expertise and experience can always throw a different light on a subject. In this respect, it is interesting to point out how one of the key defining sub-dimensions for an agent, the level of social interaction, is approached for a web browsing experience. 

For environments like retail the influence of peer interaction modifying the shopper (agent) behavior is evident. It can encourage or discourage the purchase. However, web browsing is considered by the authors an activity where “little interaction among agents” happens. Not enough interactivity to even make it part of the model.

This can be true if we assume that web browsing experience happens in an isolated and deterministic context. Is this entirely true? I wonder how realistic this assumption becomes in an environment where the interaction with peers through social media, use of mobile devices or similar activities is dramatically increasing. It may be time to review the model for web path analysis to incorporate more social interactions. On the other hand,  perhaps the influence of this new factor is minimal or totally irrelevant to the model. 

In any case this article brings to the table interesting “thought provoking metaphors” and invites you to think outside the commonly accepted boundaries on how to extract more insights from path analysis environments.