Know Your Audience: the Difference Between Alice Cooper and Donald Trump
Alice Cooper and Donald Trump are not the same type of person. Are you shocked? If you were using demographic data, you probably would be surprised. Your data would show them both to be older Caucasian males who belong to a high income bracket and who live in a high income neighborhood.
As you accumulate more data on both these fellows, you’ll notice the difference and will realize that you may not want put them both in the same audience segment – or maybe you would if you’re running a wacky golf-related campaign.
Advertisers who want to improve the performance of campaigns have to start with a deep understanding of the consumer. While demographic data has a lot of value in targeting audiences via TV and print media, digital media enables a more personalized way of advertising based on deeper insights marketers can gather on consumers.
Now, with many large advertisers, the majority of the budget is earmarked for TV, where there is the easy temptation to just use demo data about age, gender and household income for targeting. This is how marketers have done it for years and years. However, recent studies from both Comscore vCE and Nielsen OCR show that most ads don’t hit their target audience. Comscore recently revealed that 57% of display ads didn’t hit their intended demographic target. Remember my reference to Alice Cooper and Donald Trump? For the uninitiated, Alice Cooper is a rock/metal singer, and Trump is, well, The Donald. If I were to use simple demo data to reach a TV audience of men, ages 65+, nationwide, I would reach VERY different people – both Alice and Donald. Yes, both are the same demo, but that’s where the similarities end. Marketers need to redefine how and who they target.
With the advent of people-based targeting, marketers have the opportunity to reach real people and not just phantom faces within a demographic. Marketers are now equipped with data to target people based on their actual online (and offline) purchase behavior and interests. This affords the opportunity to tailor ad experiences with appropriate messages to individuals vs. groups. If marketers can layer in purchase-based or CRM data to discern between existing customers and prospects, it pays tremendous dividends. This type of data helps personalize creative, and studies have shown that providing the right message in an ad contributes to a marketing conversion 4-5 times more than customary demographic based targeting of media. With people-based targeting, marketers can use first-party data to understand their highest value customers, and then layer in third-party data and other info to create a richer profile of customers to better target ad messages.
At our company, we regularly run new acquisition campaigns using additional behavior and intent data, and in some cases, this yields 7 to 10 times more acquisitions than demo-based consumer targeting. Here’s one scenario of how a brand with more customer insights can achieve this type of success. A marketer could have data on individual men in the 35 to 44 age range. Other data that can be layered on top of this could be career (perhaps he works in IT, medicine, education), lifestyle (married and no kids, married w/kids, single parent), interests (travel and political motivations), and intent (needs for his business/work, new SUV, shopping at high-end retailers). Having this information gives advertisers a more robust view of current customers, plus the ability and precision to reach those exact customers and the ones who look like them.
In campaigns, gathering knowledge about audiences is often overlooked or over-simplified. Because audience data is a vital pillar for a well-performing campaign, it pays off to think beyond simple demographics and explore a wide myriad of data sources available for the marketer.