In years past, outbound marketing tactics were ruled by basic audience segmentation such as when and where different demographics consumed content. The decisions made on where to place billboards, or when to run TV and radio ads, relied heavily on a game of educated guesses.
If a demographic was most likely to buy from a particular brand or invest in a specific product, a lot of research went into finding and blanketing the places and times this demographic could best be reached. Of course, not every person seeing or hearing the messaging became a paying customer, but if even just a small percentage were hooked, the marketing tactic was deemed successful.
The problem with audience segmenting was in finding the perfect data set. Being too broad meant missing the smartest targeting opportunities; being too specific meant alienating potential buyers who didn’t fit the narrow criteria. The more attributes you use, the more difficult the segments are to understand.
So what should you do?
What’s Appealing About Audience Segmentation
As marketers, we like hard numbers.
We want to know exactly which campaigns are working, how many people are responding, and ultimately how many people are buying products or services as a result. Segmentation was appealing because marketers had the ability to glean an understanding from the data sets they had about customers and potential customers.
For example, if you knew that millennial men that live in a rural area tend to buy your product, the prevailing wisdom was to segment your list to advertise to people with these demographic and geographic characteristics. The issue with segmentation is that it can be too broad and miss why certain millennial men that live in rural areas buy your products and others with the same characteristics don’t.
In the 1950’s, Seventeen magazine created a target persona, called “Teena,” from survey data they gathered from teenage girls and their mothers. Teena could be described as:
Teena the High School Girl has a pack of problems. She’s what older folks call an awkward adolescent — too tall, too plump, too shy — a little too much of a lot of little things. But they’re big things to Teena. And though she doesn’t always take her troubles to her mother, Teena writes her favorite magazine for the tip-off on the clothes she wears, the food she eats, the lipstick she wields, the room she bunks in, the budget she keeps, the boy she has a crush on. Seventeen seems to have all the answers — that’s why like Teena, smart advertisers use Seventeen.
The survey data was used to create an audience segment that the magazine could promote its “too tall, too plump, too shy” message to. It’s this segment of the audience that Seventeen could then advertise products that would tone their “too-much-ness” down. The strategy was very effective at marketing to a specific segment of the Seventeen audience even if it feels a bit manipulative of teenage girls’ insecurities.
So, even with its flaws, audience segmentation was the best shot most marketing departments had at finding target customers for a long time.
Measuring Behavior and Preferences
Fast forward to the marketing of today. Brands have many tools at their disposal to understand customers on a deeper level, from tracking cookies to customer relationship management software. These tools, combined with smart inbound marketing initiatives, market to an individual level based on preferences and behavior collected. Yet many brands still rely on the outdated practice of audience segmentation to attempt to target customers.
In some cases, the business leaders or marketing heads just don’t know any better. Audience segmentation is the status quo and so it stays in play. In other cases, misinformation abounds about the cost and effort to implement more pinpointed, smart endeavors. In either situation, money and resources aren’t being fully utilized to successfully convert strangers to buyers.
So What’s the Alternative?
— Whenever possible, marketers should personalize content 1:1.
Audience behavior data and customer relationship management technology combine to show what specific customers are interested in buying based on their own behaviors. We know that there are complexities that influence each individual buyer’s journey to a purchase. While there is no definite way to predict that outcome, indicators like online behavior and past purchases can shed a lot of light on it.
Using programs that empower data analysis, or hiring a company that specializes in personalization targeting, can make a world of difference in who actually buys from your company. It’s important to understand that personalization is also not an exact science, but it comes much closer than outdated methods.
Perhaps the greatest benefit to marketers when it comes to personalization is that customers actually like it. There is definitely some caution from consumers when it comes to accuracy of marketing information (ever been creeped out by a Facebook ad that mirrored a recent Google search?), but consumers overall like personalization if it actually helps them.
A Digital Trends study found that 73 percent of consumers favor brands that use personalization to guide their buying journey. eTailers are using intent-based personalization to offer things like information content and discounts to shoppers in real time to help them along in the buying process and in most cases is seen as a positive by the buyer.
The more customized the marketing messaging, the better the chance it will be received the right way by the right person at the right time. The right marketing personalization tools can take the labor out of the process, too.
As marketing targeting technology continues to improve, brands would be wise to abandon outdated audience segmentation initiatives in favor of a tailored customer path to buying.