The Data Privacypocalypse is a Digital Advertising Revolution. Follow Apple’s Lead.
Apple’s efforts to preserve user privacy as data becomes scarcer have paved the way for their $4 billion digital advertising business, which is well-positioned to lead the ad industry in establishing a new standard for digital advertising and data collection. The ad industry has been slow to adapt to the end of an era in which data was freely available. As a result, Apple is well-positioned to lead the digital ad industry in establishing a new data standard.
Having control of an ecosystem is an advantage.
Google and Apple own both the application stack and the hardware ecosystem, giving them a huge advantage over competitors. This gives them the ability to control how ads are delivered and measured. As data becomes increasingly difficult to obtain, these advantages will become both a barrier and a competitive weapon.
50% of consumer markets have built-in ‘privacy-first’ features.
As the industry adapts to regulatory and technical changes, Apple is well-positioned to protect its walled garden. This is because it has included various operating system and browser privacy features that make third-party targeting and measurement difficult. App Tracking Transparency (ATT) framework, Apple’s Intelligent Tracking Prevention (ITP), SKAdNetwork, and blocking third-party cookies in Safari, all work to prevent surreptitious data collection. Almost half of all U.S. smartphones and one-fifth of browsers are effectively forcing the industry to adopt a first-party data standard that is opt-in. Cookies and smartphones can no longer be used to measure users across different websites, locations, and apps in browsers as a result.
Ad Measurement Is At Greater Financial Risk Than Targeting.
Multi-touch attribution based on third-party cookies and mobile identifiers has become essential to measuring and optimizing advertising campaigns. Achieving the most efficient ad media measurement and optimization is difficult without multi-touch attribution, which allows advertisers to allocate their budget more efficiently and achieve a higher return on investment by understanding how different marketing channels interact. By simultaneously measuring how users interact with a brand across multiple channels, including online ads, website visits, social media interactions, and in-person interactions, advertisers can monitor campaign performance. Using this data, advertisers can measure the effectiveness of specific marketing channels against one another and distribute their budgets accordingly. Without multi-touch measurement that considers upstream and other channel touches, it would be difficult to estimate the impact of each marketing channel.
Last-touch will continue to dominate.
Privacy-protecting measurement techniques will create a preponderance of last-touch attribution which has made other closed environments so successful (e.g., the last click is attributed to a sale, regardless of other upstream interactions). Advertisers will be less inclined to invest in cross-channel campaigns if they cannot measure them accurately. Third-party, open ad ecosystems that encourage multi-touch measurement may become “optimized out” of campaigns due to walled gardens and closed systems.
The Alternatives Are Adaptations, Not Replacements
By using third-party ID providers like LiveRamp and ID5, advertisers are preparing to compensate for lost third-party cookie data. Due to their lack of scale, ID alternatives, in the interim, have been used in tandem with third-party cookies to track consumers across multiple websites and apps for measurement and targeting. Several new IDs charge fees for use and may not work with walled gardens or other independent IDs. For advertisers and publishers, this data cannot be collected without expensive integrations or fees, so you need to develop a first-party data strategy.
The data free-for-all is coming to an end.
With the acceptance that third-party cookies are going away, marketers and publishers must focus on building direct user relationships. Advertisers need to develop trust with users to develop a first-party data strategy to target and measure users on different websites and applications.
How to Follow Apple’s Lead.
If you interact directly with your customers incrementally and respectfully, you will gain their trust and allow you to access their personal information, including their email addresses. You can use third-party data to understand how your customers engage with your brand outside of your channels once they have opted in.
Get the opt-ins!
Apple customers chose to be tracked through ATT by 22%. Publishers can learn from Apple’s approach by creating opt-in environments that build trust and first-party profiles incrementally. When trust is established, use various activities to gather information about users. You can register them directly, subscribe to your services, purchase your products, take surveys, run contests, or do other things. Users may be more inclined to opt-in if you explain how you use their data and the benefits, such as exclusive content.
You should also create an easy opt-in process. When users don’t have to provide too much information or go through a lengthy procedure, they will be more likely to opt-in. Ask for the basic opt-in first and then the email address. Following up with each subsequent visit by asking for one or more additional pieces of information, but without being too intrusive. Each incremental touch should increase the value of the requested data and benefits to the user.
Divide your opt-in users into cohorts.
A user’s first-party opted-in data can be segmented according to their age, gender, location, content consumption, past purchases, and any other information they have provided. You can identify which groups are most likely to purchase your products, use your services, or engage with your brand.
Finding similar anonymous users can be accomplished by identifying common signals.
Using your opt-in users as a panel whose characteristics and actions are known can help you engage anonymous users who haven’t opted-in. An anonymous user can be compared to an opt-in user group by identifying universal characteristics and traits, such as the addresses they visit or the apps they use, between them. When comparing anonymous users with opt-in users, non-user data signals (such as content) should be used as a key. You can apply opt-in segment characteristics to anonymous cohorts once you’ve identified matches.
The focus on data privacy by Apple will prevent a data free-for-all while preparing it to dominate the digital advertising market. To survive in this new privacy-first environment, you must establish a first-party data strategy and gain user consent. By gaining their users’ trust and encouraging them to opt-in directly or to share their personal information, publishers and advertisers can segment their opt-in users into cohorts. Use non-user data signals (for example, content) to locate similar anonymized users whom you can apply your predefined segments.
