Writing Off Behavioral Targeting?
Seven of the most important types of behavioral targeting that are worth trying.
Seven of the most important types of behavioral targeting that are worth trying.
Theoretically, any type of action a consumer does online can be defined as their “online behavior.” From their previous actions (i.e., clicking on a banner) to taking those actions and building a predisposition model based on their “likelihood to.” Standard targeting tactics can increase the value of advertising for publishers, networks, agencies, and brands; however, by optimizing the way we target users online, there is the opportunity to increase consumer relevancy and subsequently, conversion rates. It’s the more advanced targeting tactics (those that are beyond standard content and geography) that allow you to reach users further down the purchase funnel.
According to a research study by the Network Advertising Initiative, users who clicked on behaviorally targeted ads increased their likelihood to convert by 2.48 times the conversion rate of standard RON (define) ads while increasing the cost of these ads by only 2.08 times the cost. While the study admits to missing the key component of how likely users are to click in the first place (especially as this pool of online users is continually shrinking), it’s more important than ever to recognize the overall benefit of creating relevancy for consumers.
While standard behavioral targeting methodologies vary across different publishers and networks, it’s not necessarily successful across the board, and results can vary pending overall success metrics.
In the ever-evolving competitive nature of online advertising and opportunity to leverage backend technology, optimizing and trying different types of behavioral targeting are important. Below are a few worth considering and when not to give them a try:
While the above list is not inclusive (each company has its own favor), it can be helpful to consider some before excluding advanced targeting tactics from your media buy. As noted in many of the options, often the top-performing metrics are less scalable, hence the importance of testing and optimization.