Nostalgia is an influential driver of consumer decisions and purchases. CivicScience data has shown on numerous occasions how consumers who say they’re influenced by nostalgia are likely to make different types of purchases. These include foods and experiences (McDonald’s adult Happy Meals), clothing and fashion choices (‘90s-inspired jeans) and electronics and media like DVDs (interest in Blockbuster's return), to name just a few instances.
How do consumers rate their likelihood to purchase by nostalgia? CivicScience data from May 2023 show that more than half of U.S. adults say they are likely -- either "extremely" or "somewhat" likely -- to make a purchase when it makes them feel nostalgic for the past.
Not everyone feels nostalgia in the same way, of course. Many are looking for products, trends or experiences that defined their youth. Previous data show that nostalgia for different eras varies extensively by age, which is to be expected. For example, Millennials are most nostalgic for the 1990s while Baby Boomers are most nostalgic for the 1970s. Yet fans of eras that they weren’t yet around for are also motivated by "nostalgia" in a sense, such as Gen Z-aged Stranger Things fans’ affinity for certain brands and music of the 1980s that were popularized by the successful Netflix series.
Nostalgia sells, but which consumers are motivated by it? At the top of the pack, the groups most likely to say they make purchases based on feelings of nostalgia are Gen Z and Millennials.
Consider that part of what’s driving nostalgia marketing is a desire on the part of more brands to appeal to younger consumers, such as Gen Z and Millennials. And that makes sense. Combined, these two generations represent nearly half of the total consumer market right now.
But, just how accurate are young adult respondents at judging whether they’re likely to buy things based on feelings of nostalgia? In other words, are young consumers under age 45 who believe they are motivated by nostalgia actually more likely than older adults to make purchases based on it? Digging a little deeper into the data shows that the "nostalgia factor" wrapped up in consumer purchasing decisions is more complex than face value.
In general, respondents who say they are generally influenced to make nostalgic-based purchases are significantly more likely to have actually done so (made a nostalgic-based purchase) in the past month.
However, crossing these questions -- a general belief about how someone makes purchases based on nostalgia with a past account of an actual nostalgic-based purchase -- allows for deeper insight into consumer behavior. Further analysis by CivicScience of the cross-reference above led to the calculation of a "d prime" score that essentially measures the accuracy of the response to the first question -- the general likelihood to buy something based on nostalgia. Applying this score to the general question and breaking it down by age, we see that older adults (over age 45) are actually more likely than younger adults to accurately answer they tend to make nostalgic-driven purchases. That’s to say, older adults have more accurate insight into how nostalgia influences their purchasing behavior.
Ultimately, the findings show that although younger adults may indeed be more likely than older adults to describe themselves as likely to buy things based on feelings of nostalgia, it is in fact middle-aged and older adults who, when they describe themselves this way, are most likely to be correct.
This finding has important implications, especially for any brand or organization looking to capitalize on self-reported feelings of nostalgia to drive purchases. For such companies and marketing teams, it would make sense to pay particular attention to -- and track -- self-reported feelings of nostalgia among consumers aged 45-54.
Insights are derived from the latest edition of the CivicScience report “What We’re Thinking: Insights on Current Events & Consumer Psychology,” an ongoing series available to clients. Get in touch for more info.
This article originally appeared on CivicScience.
Posted at MediaVillage through the Thought Leadership self-publishing platform.
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