Since entering the personalization space a few years ago and getting the chance to work with leading retailers across North America, we have noticed that many people talk about omnichannel marketing as though it automatically addresses the customer journey in a positive manner that benefits both customers and the retailers that serve them. This view is not entirely correct.
In fact, at least in the context we hear many people speak about it, omnichannel has more in common with retargeted ads than with true customer journey mapping or optimization. To understand why this is the case, we need to look at what exactly a customer journey is.
What Is a customer journey?
A customer journey refers to the series of interactions a given customer has with a company over time across various channels. This journey can go to desirable places such as loyalty and higher lifetime value…or it can go to undesirable places such as churn or purchasing products only when a discount is offered.
To understand and influence the customer journey, one must take into account the crucial dimension of time. The journey, in this context, is not so much about which channels customers use to engage with your brand, but the nature of those engagements over time. Touchpoints are important but the cumulative nature of those interactions is what influences the relationship between the brand and its customers.
Personalization and the customer journey
Personalization is a big umbrella term that covers anything from adapting the colors on a website to better match the tastes of a particular user to recommender engines to automated workflows and beyond. However, if the personalization system in question does not take into account the series of interactions a customer takes with a retailer over time, it cannot be said to address the customer journey in a comprehensive fashion.
For example, product recommendations derived from logic like “people who bought this also bought this” or “you viewed X, you might like similar item Y” tend to have a narrow scope that does not examine the shifting nature of customer tastes. This is the reason we so often find ourselves looking at item suggestions that present something very similar to the product we just purchased. You may buy cycling shoes on Amazon, but right after doing so, you probably do not want to immediately buy more cycling shoes.
Omnichannel experiences versus journeys over time
Many people think of the customer journey in channel-based terms. The customer saw our display ad, went to our website, subscribed to the email list and purchased via mobile; so we should deliver a seamless and personalized experience across these channels. It is a good mindset to have. People want to be able to browse and purchase on any channel at their convenience.
But if that seamless and personalized experience does not look at the fluctuating and evolving preferences of customers over time, it is not optimizing the journey. Rather the personalization system is only making certain points in that journey consistent across different channels. In this sense, omnichannel personalization is more similar to following a customer with the same display ad across a bunch of websites than it is to understanding and shaping their journeys.
How to understand and influence customer journeys
There are numerous ways to model journeys, some more effective than others. One method is to set up automated workflows that map to customer behavior at various points of interaction. For example, an onboarding email might be sent when customers first sign up to an email list and a re-engagement email sent to inactive subscribers.
In contexts with a low number of dimensions, workflows can be effective. If there are only a few customers and products, it is possible for a human to set up a process that adequately corresponds to customer behavior. However, for mid to large size retailers with thousands or even millions of customers, it is simply impossible for a human to map out the behavior of each individual customer. More advanced methods are required to personalize the journey.
Fortunately, machine learning and data-science have evolved to the point where it is now possible to take in transactional, web, email, and other data and use this data to create a “map” of the space in which customers browse and purchase products. By plotting out the path a customer takes within this space, you can understand where they are heading over time. If you know where customers are heading, you can gently nudge them in the direction you would like to see them go–while not only respecting, but catering to their individual tastes and preferences.