Advertising and Privacy: What Privacy-Focused Marketing Means for Digital Advertisers
The advertising world is changing vastly as it relates to data privacy—here’s everything a digital marketer needs to know in 2021.
Data privacy-focused advertising is here and it’s surely not going anywhere, and that means advertising and privacy is changing quickly. Big tech companies and digital advertising providers—like Google and Facebook—are pivoting to keep up with the dynamic future of digital advertising, so you may be wondering what this means for your marketing strategy and questioning some of the marketing strategies you’ve implemented in the past.
How was the advertising industry affected by advertising regulations?
One of the driving forces of this change in advertising is Apple’s release of iOS 14.5 and the enforcement of the App Tracking Transparency (ATT) prompt in early 2021. To put it plainly and simply, this prompt lets the user control which apps are tracking their activity across other companies’ apps and websites. While the impacts of this prompt are ever-changing, here’s what digital advertisers should know right now about advertising and privacy for their marketing campaigns.
Do advertisements invade privacy?
Now more than ever, user privacy is of the utmost importance, there’s no doubt about it. However, you still want to make sure you’re doing everything you can to market your product, business, etc. to people who will actually turn into leads and eventually customers. All of that said, the line between ad targeting and invasion of privacy can be a blurred one, but when you steer clear of personalized advertising, you’re less likely to cross that line.
What getting rid of personalized advertising means for advertising and privacy
Historically, advertisers have been able to use app tracking—in conjunction with other strategies like micro-targeted advertising—to serve customers targeted ads based on things they have searched for. By giving customers the ability to decide who can and cannot use app tracking, the ATT prompt has caused marketers to need to shift their focus to other advertising strategies. Fear not, though—this isn’t necessarily bad news for marketers. Change in the digital marketing world is inevitable, and these tactics can help digital marketers run more data-secure ad campaigns. It’s also important to note that this ATT prompt that comes with the iOS 14.5 update does not impact Android users (yet)—who make up 72.83% of the worldwide market share.
What are the dangers of advertising?
Surveillance advertising has drummed up a lot of controversy within the advertising and privacy space because it uses behavioral profiles to serve ads and risks the data privacy of consumers. Here are the digital advertising strategies you should assess and consider for your digital marketing campaigns to steer clear of controversy and potential data-privacy violations.
How are ads targeted without personalized advertising?
When looking for effective targeting strategies that can mimic the effectiveness of personalized advertising (while abiding by advertising regulations), look to contextual targeting—aka when advertisers place ads using the content of the website (think: cookware ads on a recipe blog). Contextual targeting doesn’t track or target specific users or groups the way surveillance advertising does. This type of targeting is “privacy-friendly,” and ensures a transparent and accountable consumer experience while continuing to market to people who are likely to show interest in your product.
Authenticated-consent ad buys
Websites that use authenticated consent collect advertising consent without using third-party cookies. Instead, they capture consent through identity-based signals. For example, when a user logs in to a platform and sets up their ideal consent preferences, those settings will follow them to other platforms. This tactic allows advertisers to deliver a seamless advertising experience to consumers across domains and devices without sacrificing trust, personalization, or relying on third-party cookies. It’s similar to a cookie, but the consumer has to log in in order for the consent settings to take action, giving the consumer way more control over their privacy.
Changes in Google ad privacy have made data-driven decision-making more difficult, there’s no doubt about it. In turn, this has made it increasingly difficult for marketers to measure the complete customer journey. Without a full look at the way customers interact with your ads, how will you know what’s working and what needs to be changed? Enter: conversion modeling, which uses machine learning to account for gaps in data when measuring the impact of marketing campaigns.
In this new data-privacy-first world, many devices may not allow for cookies. This causes major gaps in reporting when identifying who is interacting with what aspects of your campaign. So, these conversion models analyze large amounts of data over time to identify correlations between key data points and use those insights to make predictions about customer behavior. Modeling also estimates the missing conversions in Google Ads—in other words, whether or not a Google ad interaction led to an online conversion—without identifying individual users. The proactive testing and validation processes not only ensure accuracy but also put users and their data privacy first.
This modality of measuring is crucial as the cookie-less world continues to evolve because it allows you to have the most accurate measurements possible when determining how your campaigns are performing and if you’re meeting target revenue goals.