By Pete LaFond, vice president of marketing, TruSignal
The holiday season is coming. Think that statement’s a bit premature? With 1 in 5 consumers beginning their shopping in September, we humbly disagree. Digital marketers are already busy making their lists of which consumers to target. But have they checked them twice?
As usual, these marketers are looking for two main things: more customers and greater sales. But digital advertising waste is a real concern. Marketers need to be sure that they’re refining their digital targeting strategies to keep threats like bots filed under “naughty.”
Fortunately, by observing two simple rules, marketers can reduce digital ad waste by more than 20 percent. Here’s how.
Out: segments. In: people.
Even though many consumers have started thinking about their holiday purchases, the online signals you might use to target them in your acquisition campaigns are not yet abundant. So how do you find them, both efficiently and effectively?
Digital retail marketers have traditionally relied on targeting segments: gender, age and income, sometimes narrowing in on predefined cohorts like soccer moms. Another common strategy has been to zero in on a specific website or platform, expecting it to over-index on a coveted demographic.
But these methods have some glaring inefficiencies. First, bots can easily imitate segment characteristics, so a cookie-based approach to segment targeting is susceptible to ad fraud. The ANA estimates that “bot traffic in programmatic inventory averaged 17 percent,” and bot traffic consumes “19 percent of retargeted ads.”
Second, demographic segmenting and site-specific targeting makes an important assumption: all people with certain key characteristics are of equal value. The reality is, this is not the case and both techniques dilute the efficiency of your marketing.
People-based audiences avoid these inefficiencies. Built using verified consumer profiles and then matched with online cookies, the approach significantly reduces the bot issue. The focus isn’t just on a single criterion or a limited set of attributes that can be easily mimicked, but thousands of data attributes that together help evaluate whether each profile is a good fit for your brand.
Conversion is the only quality that matters
As the holiday season approaches and consumers begin projecting more online signals, most digital marketers will use behavioral targeting and lookalike modeling for their acquisition and prospecting campaigns.
While these tactics might round up the quantity of prospects to hit your quota, there’s no guarantee these consumers will be a good fit for your brand. No matter how late in the season, targeting signals over people can yield some inaccurate results. The real attribute you’re looking for is not a particular demographic, but the likelihood to convert.
So how do you find these people? It can be done through audience filtering. Built using first and third party profile data, an audience filter builds your “naughty list” for you, identifying the consumers to avoid — those who, based on rigorous analysis of thousand of attributes are not a good fit for your brand. In the end, it can help brands eliminate more than 20 percent of digital advertising waste.
This holiday season, marketers are set to spend more of their budget on digital advertising than ever before. There’s no need to waste those dollars chasing bots and targeting the wrong consumers. By moving beyond unsophisticated behavioral and segment targeting strategies, they can start proactively embracing a people-based approach that fuels holiday sales growth and digital campaign efficiency.
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