Just a couple of years ago, users who shared Netflix accounts baffled the streaming service’s recommendation algorithm, the tool that’s supposed to learn your preferences and suggest movies and TV shows you’d like to watch from the company’s extensive catalog. But while you’re binging on “Breaking Bad,” your kids might be streaming Disney movies, leading Netflix to suggest content that might not appeal to everyone in your household.
If you happen to use Netflix as it was originally intended—that is, one account, one user and one data set for making predictions—it works fantastically. The trouble is, virtually nobody uses it that way.
The answer to this problem was simple: user profiles. These would allow the company’s millions of subscribers to create several profiles on any one account, and recommendations would be more aligned with each individual’s interests.
This strategy seems to be working, since research suggests that 75 percent to 80 percent of what people watch using the streaming service comes from what Netflix recommends, instead of what people search for. It comes as no surprise, then, that retailers are scrambling to apply this same logic to the grocery world.
Segmentation in the Age of Big Data
Today’s grocery businesses are leveraging the data and technology at their fingertips to segment customers based on historical purchases, browsing patterns, and more, allowing them to create targeted offers for shoppers as part of an omnichannel experience. Technology-savvy consumers have come to expect—and even demand—this level of personalization, with many considering it the new norm.
By grouping consumers by age, geography, gender, income and family status, marketers have been able to draw conclusions about each group’s shared interests and consumption behaviors, but the assumptions we’ve grown to accept from traditional demographic segments are becoming less reliable. A frequently cited example of this would be Ozzy Osbourne and Prince Charles: Both were born in 1948, grew up in the United Kingdom, married twice, have two children, are wealthy and like dogs.
In the age of Big Data, it’s easy to dismiss segmentation as an outmoded methodology, but the segmentation of old is quite different from the advanced tactics used today. Rather than grouping customers based on their demographic traits, modern techniques use value and behavioral dimensions to create a multitude of microsegments that define themselves organically through data analysis.
In its most rudimentary form, a household is best described as a group of people with the same last name, living at the same address. But the traditional concept of the household is changing: There are more multigenerational households, and many families are delaying—or even abandoning—marriage. Beyond just recognizing that these shifts are taking place, it’s important for marketers to consider how such changes will influence consumer culture and shape product demand.
“Responsibility for groceries is becoming more evenly dispersed throughout the household, and the role of the primary shopper is being replaced with multiple shoppers who divide and share responsibilities.”
Responsibility for groceries is becoming more evenly dispersed throughout the household, and the role of the primary shopper is being replaced with multiple shoppers who divide and share responsibilities.
On the one hand, this raises questions about how well each shopper represents the needs of the household they shop for. On the other, it means that marketers have more opportunities to appeal to individual customers.
When it comes to balancing the needs of the individual versus household, the truth is that both must be taken into consideration. After all, in the age of the consumer, it’s all about delivering truly contextualized and highly relevant experiences—but what’s relevant to Ozzy Osbourne will likely differ from what’s relevant to the Prince of Wales.