How to Make Your App Marketing Strategy Worth the Investment in an ATT World

Is your app marketing strategy working? The 26th of April 2021 saw a pivotal change in data use for consumers, businesses, and third-party marketers when Apple issued its new privacy system, ATT, across its devices. Available on the updated iOS 14.5, ATT (or App Tracking Transparency) provided iOS users with the choice to o***** to data-tracking within apps. While Apple devices have had the ability to opt out of data tracking for a while, it has always been concealed deep within iOS settings. As of 26th April, apps contained a pop-up message directly asking users if they would like their data to be tracked to allow ad personalization to continue. 

Apple’s new iOS has been quickly adopted by Apple device users, with data suggesting 80% of users have already downloaded the 14.5 or 14.6 updates and gained more control over their web privacy in the process. Naturally, most users were expected to opt-out of data tracking and this has caused unrest among those businesses who leverage third-party data to inform their advertising. Snapchat and Facebook have publicly condemned Apple’s new system, with concerns focused on Apple’s monopolization of the app ad market on Search Ads, a system designed to advertise apps on the App Store, as well as worry for their own reduced channel efficiency. Marketers also voiced their concern, but their actions may be more telling, as they set their sights on Apple Search Ads (ASA) because it operates independently of cookies, IDFA, and third-party data. Despite this, there are some drawbacks that shed doubt on the platform when it comes to ROI for marketers.

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The ASA Landscape and How AI Is Set to Evolve App Marketing

While Apple’s ATT update has quashed a portion of the brand’s privacy concerns, it’s also had an impressive influence on their bottom line and market share within app advertising.

According to statistics from the mobile marketing analyzer Branch, spending on ASA has tripled over the last six months, with the company’s share of app purchases as a result of advertising clicks rising from 17% to 58%. One reason for the spending increase is the currently limited channel offerings on social media, as they rush to realign their operations without tracking capabilities and find a fix for the higher customer-acquisition-costs (CAC) catalyzed by an increase in advertising activity as brands focused efforts online as a result of the pandemic. 

As ASA surges in advertiser focus and use, the amount of money and resources now devoted to the channel has increased competition, leading advertisers to try and find a way to make their app marketing strategy worth the investment in an ATT world. New technology within AI for specific use in ASA will provide the edge these marketers need. 

There are a few fundamental reasons why ASA did not show the same levels of current interest in a pre-ATT advertising environment. ASA is a high-touch channel, meaning it requires near-constant monitoring and analysis to provide the best chance for successful advertising. With keywords, search terms, and consumer behavior subject to rapid changes, marketers are in a constant battle with ASA to get up-to-date actionable data for effective ad spend. Doing this without the use of AI is time-consuming, costly, and often yields unsatisfying results. Issues in scaling up ASA channel efforts are also apparent, particularly in international markets across multiple timezones, given the amount of attention ASA required.

A further challenge comes with the poor “Search Popularity” data housed within ASA – data that is 48 hours delayed and applies a 7-day moving average, making advertisers’ jobs harder than they have to be, particularly in fast-paced, dynamic and event-driven markets. The use of AI using real-time “Search Popularity” data would transcend current capabilities, providing the ability to gather far more actionable insight. Simply put – garbage in = garbage out for AI, and since keyword and popularity trends can now be delivered accurately in real-time through CMA’s data (for the first time since the launch of ASA), Apple’s advertising efforts are more accurate and more effective than those that have been possible previously. 

Why Advertisers Should Focus More Budget Towards Apple Search Ads in the Wake of ATT

Despite these metric difficulties, ASA –  and the App Store generally –  contains many advantages for the advertiser.

Firstly, the App Store has billions of users that search within the store on a monthly basis, meaning that the pool of potential customers is virtually unmatched on iOS.

Secondly, as ASA is an Apple-owned product, it doesn’t operate with the same restrictions that previously IDFA-dependent channels do. This places ASA as a resilient advertising channel going forward as it’s not facing the learning curve that third-party-based data acquisition channels are.

Ultimately, this gives ASA an advantage above previously successful ad networks and social channels which relied on third-party data for success (oh, and it also provides far greater conversion reporting and accuracy for campaign optimization).

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Lastly, advertisers and marketers understand that consumers using the app store are primed for conversion. These high-intent prospects use the store to discover or purchase products. For many brands conversion is a primary focus KPI and, while ASA suits this priority, it also harnesses great benefits for product awareness and customer lifetime value (LTV). 

Current ASA data are not capable of providing the up-to-date atomic values required for a data-driven marketer to react to the vast consumer, societal, and event-driven changes to App Store users in every country across the world; simply put, too much of an advertiser’s spend on ASA is being fuelled by out-of-date metrics. Using Apple’s own data significantly increases the risk of bidding on overly saturated and under-served (or even worse stagnating/irrelevant) keywords. 

How App Marketers Can Leverage AI and App Store Optimization to Increase Ad Spend ROI in an ATT World

While these shortcomings might deter advertisers from relying on ASA when it comes to ROI, AI is capable of negating many of these issues, making ASA a reliable advertising channel going forward.

Providing real-time actionable data increases an advert’s relevance and effectiveness, as marketers can choose the currently applicable trends that will impact ad changes within minutes. 

Innovations within AI that have been built specifically for ASA have come at the correct time, we are the first to provide a system that utilizes these AI advantages in line with the increasing use and dependence on the ASA system. This AI has been built by some of the global leaders from high-frequency trading and is underpinned just as importantly by a brand new real-time search tracking dataset. This software is already delivering competitive advantages to some of the most successful global brands in the iOS market and continues to grow in adoption. 

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Ultimately, leveraging AI in ASA along with the right data gives advertisers the ability to avoid wasting budgets and time on stale keyword and search analytics, and instead offers a way of using ASA channel investments to their maximum efficiency.

By understanding the search patterns occurring on this channel across all countries at every hour of the data, ASA advertisers have a far better chance of achieving a scalable and efficient CPA, capturing a far higher share of voice than their competitors. With the rise in ASA use for advertising, the disappearance of third-party IDFA data, and the introduction of ATT in 2021, it seems that the trend of focusing on ASA as an advertising channel will only increase. The early adopters of AI for this purpose may have an advantage when it comes to understanding changes, gaining relevant insights, and improving implementation speed, and should produce KPI-pleasing advertising as a result.