It’s become clear that all marketing data isn’t created equal. While demographic information has its place, our customers now put a high value on a unique combination of semantic and behavioral data to build high-performing audience segments.
Programmatic campaign planning still frequently starts with identifying a target audience, then filling in the blanks with information like gender, age range or income bracket. Unfortunately, this approach doesn’t often drive the kind of performance clients desire. That’s one of the drawbacks of making assumptions that age, gender and income indicate a user’s interest in purchasing a product. These data points are more valuable when they are complementary to other components in the targeting mix.
This attempt to apply an old model into the contemporary structure of digital marketing reveals the conceptual shortcomings of socio-demographic data when it is not layered with other data sources, particularly in a programmatic campaign. It’s become critical for marketers to think of other, more meaningful ways to find an audience.
Consider the example of a luxury watch brand. In this case, an advertiser believes their target audience is men, aged 18-40, who make more than $100,000 a year. Within that group there could be personas as diverse as bankers, plumbers, and rock stars. If they only target based on demographic data, they will inevitably miss users who have an interest in their product. As well, valuable ad dollars will be spent on people with no interest in the product at all.
There is a better way. Semasio Semantic Behavioral Targeting builds segments for marketers based on the words and content that people consume -- helping brands target their ideal, engaged, and interested audience. Now, reconsider our example.
A Semasio audience will not only capture those bankers, plumbers, and rock stars who do in fact have an interest in luxury watches (while excluding those that don’t), they will also include users such as a wife who has been in search for a gift for her husband who likes watches.
Regardless of income bracket, gender, or age, the target customer is more accurately found. Through prospecting, of course, you know that not all users have purchase intent, but you are finding those who are more likely to make a purchase. The upside of Semantic Behavioral Targeting is a much stronger signal than simple demographic data, with the additional benefit of knowing the target consists of users who have explicitly engaged with the desired content.
Data and insights should not be dismissed out of hand, but should be mined for what’s of value and what can be combined with new approaches -- like Semantic Behavioral Targeting -- that give you a window into consumer interest. All data isn’t equal, but much of it still has a place in the modern marketing mix. It’s time to rethink where, when, and how to use it best.
