Every marketer wants to influence consumers, but if you listen to the social scientists you’d realize that our jobs are even harder than we may think. Case in point: according to a study from Duke University, up to 45% of the choices we make daily are habitual, not conscious decisions.
Purchasing decisions are no exception. U.C.L.A. professor Alan Andreasen studied the way consumers buy CPG products like toothpaste and soap. His findings confirmed that we’re pretty much on autopilot as we walk through the aisles, filling our baskets with the same stuff we’ve always bought. But he also affirmed what all marketers know: When consumers go through major life events – graduating from college, getting a first job, getting married, moving, having a baby – shopping habits can change if we’re engaged by a clever marketer.
As New York Times observed, “a precisely timed advertisement, sent to a recent divorcee or new homebuyer, can change someone’s shopping patterns for years.”
The economic impact of targeting consumers with the right message just as a new life stage begins is huge. Consider just one example: Having a baby. New parents will spend $720 per year on baby clothes, $550 in diapers, and $1,260 in formula. And according to a 2011 United States Department of Agriculture survey, families with just one child under the age of two spend up to $15,460 a year on them. Teens can run as high as $17,000 per year. There’s a lot of money at stake.
How to Identify and Target Life Stages
Since we know that life-stage targeting has long-term affects on consumers, the next question to ask is: can marketers use life-stage targeting to message consumers online? The answer is yes, but constructing accurate life stage segments demands two essential requirements: declared demographic data and massive volumes of shopping intent data. Here’s why:
In-market and intent data signals alone won’t indicate a life stage. For instance, consumers who Google car seats are likely to be parents, but that is in no way a given. They may be grandparents, or even office managers tasked with ordering a baby shower gift for a coworker. In-market is often short term; life-stage isn’t.
So how do you distinguish between in-market and a life stage? The first thing you need is a robust set of declared demographic data to serve as a truth set. Shopping surveys, presented at key points throughout the online retail ecosystem, are excellent vehicles to collect age, gender, income, education, ethnicity, family composition – all sorts of demographic data from tens of millions of consumers.
Next you need accurate shopping-intent data so you can detect purchasing patterns. Here’s where scale is critically important. A new mom may switch to gentler brands of household cleaning supplies, which is very relevant insight to a CPG marketer, but on an individual level, that signal is lost. If you see billions of shopping data signals a month, you get a lot closer to the truth. Fortunately, some ecommerce companies already collect much of this information from hundreds of millions of shoppers who transact across their retail networks.
The real value comes by joining both data assets together. Data scientists can use statistical analysis to reveal life stage segments based on shopping patterns and validate them with demographic data. That analysis can help marketers flag new moms who pay more attention to certain CPG product categories—like baby wipes—and are receptive to new messages from relevant brands.
We’ve observed that consumers who declare they’re recent grads in surveys go on to purchase small appliances, bedding and work clothes. They’re quite different from first-time homebuyers who also buy plenty of appliances, but already have bedding and clothes. On the surface they may look similar since they’re both buying stuff for the home, but they’re not the same. The value of life-stage targeting is that it enables marketers to target new grads differently than those first time homeowners.
Precisely Timed Advertising via Programmatic Marketing
Once you’ve identified when consumers are at critical life stage changes – along with the products they’re likely to buy – the final step is to deliver those precisely timed ads to change their shopping patterns.
Add retail signals to demographic information, deliver it programmatically and you have the recipe for results. Demand-side platforms (DSPs) purchase campaign inventory via real-time auctions – one impression at a time. Purchasing decisions are based on the unique combination of user data (including life-stage segment), page and campaign attributes. In other words it asks: Is this consumer a bride-to-be, is this a site that delivers conversions, and how many times has she seen my ad, and so on.
All of the pieces are falling into place, precisely as millions of Baby Boomers and Millennials are expected to move through significant life stages. My bet is that life-stage targeting will soon be the new buzzword of programmatic marketing, after all, there’s a lot of consumer money at stake.