Although retailers attract tons of customers over the holidays, they often don’t do so well to retain and engage these customers into the new year. Much of this can be explained by the peculiar way shoppers behave at this time of year and how retailers react to such behavior.
During the holidays, people tend to buy gifts for other people rather than make purchases for themselves. What they buy during this period, therefore, doesn’t reflect their behavior during the rest of the year. If retailers want to resonate with customers year round, they must put holiday shopping into the context of customers’ year round behavior.
Seasonal Based Promotions Overlook Crucial Variation
The challenge marketers face when trying to contextualize holiday behavior isn’t a lack of data, but rather how to make sense of mountains of it. The sheer amount of data that most retailers are flooded makes it difficult for most tools to analyze in meaningful way at the level of the individual customer.
So, when looking at data over the entire year and trying to fit holiday shopping into this context, marketers often fall back on looking at aggregate trends: people tend to buy winter items in the fall and winter; summer items in the spring and summer; and look for killer discounts on an assortment of items during the holidays. This is why we see holiday promotions offering generous discounts, winter promotions promoting winter items and summer promotions promoting summer items. The problem with these methods is that their focus is too broad to be consistently meaningful to the individual customer.
By ignoring individual customer preferences hidden in their aggregate data, retailers miss out on revenue and risk churn by bombarding customers with promotions that may be salient to the time of year but are irrelevant to the individual. Which is why more and more marketers are turning to personalization solutions. But here too they run into issues.
Conventional Personalization Systems and Recommendation Engines Suffer From Tunnel Vision
It may seem like an obvious point that to keep customers engaged beyond the holidays, you need to look at their interactions with you over a longer period of time. And for humans, this probably is obvious. But it’s harder to grasp for many machines.
The bulk of personalization systems, remarketing solutions and recommendation engines are built around some variation of the following logic: “people who bought/looked at this also bought/looked at this”. The flaw with this logic is that it tends to restrict product recommendations to a narrow range of items that estimate a given customer’s tastes and only within a limited timeframe that isn’t representative of the customer’s overall preferences. This results in customers being blasted with product offers that may reflect their holiday shopping, but don’t really speak to what these people are truly interested in.
For example, suppose a woman is shopping for electric razors as a Christmas gift for her husband. Attracted by an ad promising a generous discount, she lands on a major retailer’s site, browses through razors and purchases one. The site then suggests more razors despite the fact that she’s probably not interesting in becoming an electric razor collector. Let’s also suppose the site has her email. In early January, they send her winter promotions, some of which strike her fancy while most don’t, and so she becomes a low-activity subscriber.
In this example, the retailer has either too narrow a focus (the on-site recommendations), or too wide a focus (the winter promotion emails). In each case, the woman’s individual preferences are ignored.
Putting Holiday Data into the Context of the Entire Customer Journey
To contextualize holiday shopping within the overall behavior of an individual customer, you need technology that can go beyond “people who like this also like this” and discern individual customer journeys from an ocean of clicks, opens and transactions over the entire year and beyond. This is what we do at Coherent Path. But what exactly is a ‘customer journey’?
You can think of the customer journey as the speed and trajectory a given customer takes within a product space. Roughly put, the trajectory determines which products they’ll purchase and the speed determines when they’ll buy those products. At Coherent Path, we plot this customer journey over time through these spaces. This enables our solution to identify which behavior, such as holiday shopping, is and is not characteristic of a particular customer.
In this way, holiday shopping can be put into the broader context of a customer journey while still focusing on the individual. In doing so, retailers can create experiences that delight shoppers throughout the year by putting the right products in front of them at the right time.
The holidays deliver a swell of revenue for retailers, but it should be kept in mind that this is temporary. To retain customers into the new year and build valuable relationships, holiday shopping needs to be put into the context of the entire customer journey. Conventional seasonal promotions are insufficient for this task because such methods overlook important individual variation masked by broader trends. Conversely, conventional personalization systems and recommendation engines tend to offer products within narrow categories that customers have already seen and not acted upon. In contrast, solutions that understand the customer journey in its entirety allow holiday shopping to be put into the proper context. This enables retailers to create experiences that customers will love not just during the holidays, but throughout the year.