Native advertising is designed to fit naturally into the content of a web page or application. It’s becoming the preferred form of advertising, as customers pull away from banner ads and pop-up windows and businesses veer toward discretion rather than an all-out sales pitch.
Research done on native versus traditional digital advertising has revealed that native may at times be much more effective than display ads.
Native advertising benefits both the publisher of the website and the advertisers. It’s a symbiotic process that draws customers closer to products and content that fits their demographic and for which they may even be searching. Facebook and Instagram ads are formatted similarly to posts; they fit the screen well and are relatively unobtrusive. Pinterest does the same thing; its ads often look almost exactly like the actual feed content. Blog articles that include related content at the bottom of the piece are also using native advertising. Sponsored content is sometimes considered a form of native advertising as well, and vice versa, though it’s not a traditional “ad” but an entire piece of content instead. Similar to native ads, sponsored content can look very similar in style and theme to the webpage on which it’s hosted.
In contrast, traditional display ads sometimes draw the customer’s attention away from a page’s content. That often takes the form of a pop-up window or flashing bright colors on the sidebar of an article. They aren’t always obvious, but display ads can be annoying and intrusive, and depending on how they’re designed and presented, they can also be seen as spam. Many customers have started to tune them out. They have a purpose and can certainly be useful for businesses, but they also have downsides.
Notably, the interconnected nature of devices and accounts can occasionally cause native advertising to flop. For example, if a user simply logs into Facebook on their work computer once, they will start receiving ads on their personal devices for whatever they regularly research at work, even if it’s far from something they’re actually considering purchasing themselves.
Intelligent or learning-system technology gathers information from a database of customer history. It records clicks, searches, and purchase data and steadily learns patterns. As a result of those patterns that it sees, machine learning makes decisions to place ad content in front of customers. It picks up small details about customer interactions and presents the following content accordingly.
Machine learning takes a large burden away from businesses because they aren’t forced to do everything manually. It automates some of the time-consuming marketing decisions and tasks that would otherwise fall to humans.