LRW Resources

Back to Resources
Path to Purchase

Customer Journeys and the Path to Purchase

Posted On  November 17, 2015

There is a quiet revolution taking place among a minority of marketing researchers.  This revolution, noble and ambitious in its cause, is aimed at undermining a basic but profoundly powerful idea: that the customer journey can best be described generally, and that it can be summarized by a psychological process of funnel-like conversion, where beliefs and norms transform into attitudes, attitudes combine with situations to form intentions, and intentions translate into some purchase decision.

This kind of conceptual model is appealing in its simplicity. But like many other models popular in marketing research, it is not grounded in the day-to-day (or minute-to-minute) reality of consumers navigating a marketplace. It fails to address the real-world events that consumers experience, the choices they make, the marketing they encounter, the research that they do, the people whose advice they consult, and so on and so forth. Such “touch points,” which occur from the time a need arises to the point at which a purchase decision is made, offer important opportunities for intervention to marketers – and so require our attention in our modeling.

Not One But Many Paths to Purchase

A recent voice in this quiet revolution has come from Dr. Frank Zinni who argues that when considering how consumers navigate a marketplace for products there is not one but many paths to purchase. Some people may act out of habit, some may seek the advice of friends, others may look for discounts, while others might do some combination of these, and other “purchase journey” steps. The relevant point here is that plural pathways can come into focus only when we shift our attention to “touch points” and customer journey events.

This shift in attention creates what may appear to be a big fat analytic mess. The unit of analysis has now morphed from variables into ordered events, making it unclear if and how standard regression models can be employed. And the amount of noise now appears to have increased, since at this granular level everybody’s path to purchase appears quite different from everybody else’s. To be sure, this is not the kind of complexity and plurality that is useful to marketers!

Dig Deeper into Each Kind of Customer Journey

However, it is possible to distill this complex data down in ways that provide unprecedented consumer insights for business. For example, using analytical methods that geneticists use to sequence DNA, it is possible to identify regularities in customer journeys, reducing thousands of seemingly unique paths to purchase to just a handful of common ones. It is possible to relate different kinds of journeys to purchase decisions that benefit (or hurt) our clients’ sales. And it is possible to dig deeper into each kind of purchase journey to better understand the micro-dynamics of consumer choice and strategy. This knowledge helps to identify what types of marketing will be more (or less) effective.

The application of advanced analytics to actual customer experience data provides clear marketing insights with real business impact, both strategic and tactical. Strategic, because it is based on a holistic understanding of the ways customers navigate a specific marketplace. Tactical, because the results can inform day-to-day marketing decisions, like when to send what message to whom. This is ultimately the path to nirvana: providing consumer insights to marketers that they can actually use.


  1. Missing in all this is just what would you do with such detailed micro-data?. Surely most marketers are looking for the bigger picture and an ability to focus resources efficiently on a few key stages in the shopper journey. I doubt any marketer could hope to achieve more than that.. Our company carried out a qualitative shopper journey study on a female personal care category recently and frankly the similarities in the journey were far greater and more relevant than the outliers. . Indeed the study highlighted a less sophisticated shopper and less engaged than our client was expecting. The complications around trying to represent every journey also becomes quite convoluted when the shopper themselves changes from one pattern to another e.g. as a result of climatic considerations at a particular time. Seems to me a good old qualitative in-depth approach will move you quicker to identifying key patterns in the shoppers journey than a data driven approach based on too many variables.

  2. Chris, I agree that what is useful to marketers is the “big picture” – in no way am I saying otherwise. Let’s not confuse the data that is the basis of analysis (not variables, but events) from the results of analyzing that data. Its in the results that we want to make sure there is a “big picture”. One type of result referenced in the article, “regularities in customer journeys”, is not intended to “represent” every journey but to classify them into a given type. Basing such classification on large representative samples allows us to get a better read of how shoppers in the entire market are navigating the marketplace, a marked advantage over qualitative work. Once classified, it becomes possible to generate market-level profiles of the various paths to purchase, much like in a segmentation.


Your email address will not be published.

Subscribe to Our Perspectives

Hi! We're glad you're here. LRW is now part of Material,
and our site will be migrating to in the near future.
Bookmark me!