artificial intelligence in marketing

Artificial Intelligence in Marketing: How can we leverage AI in mobile advertising?

The recent shifts in the digital environment due to the massive arrival of AI and the decline of third-party cookies have created a transitional period in the digital ecosystem. Especially for those of us who have been working on mobile development and advertising know first-hand already some of the pros and cons of all these digital changes. But what does AI imply in mobile marketing ? What have we learned so far about artificial intelligence and how can we leverage it?

 

The new era of mobile privacy and the AI arise

After the arrival of the iPhone 12 we started blind in the post-IDFA era with mobile advertising on iOS devices due to the latest privacy changes affecting ads setup and tracking. Apple found the formula for an enhanced version of the SKAdNetwork that sorts things out for its Search Ads platform. Meanwhile Google Ads found its own get around on iOS via  conversion modeling and Facebook/Meta triggered Advantage+ campaigns as the AI-powered, privacy-safe solution on iOS.

But how is AI helping with attribution and audience targeting through the mentioned ad channels? How do we know if we are pointing in the right direction when we are not able to understand the parameters and values of conversion modeling or the so called data-driven attribution on google ads and how can we deal with data discrepancies between ad channels and MMPs (Mobile Measurement Partners) if we can’t rely on the way traffic is being attributed by the ad channels on the first place?

 

Difficulties of advertising attribution

It is a difficult moment to allocate campaign efforts and sync data discrepancies between tools and understand how we are attributing campaigns if we have less and less data points about how ad channels are getting results, what audience segments are they using, what are the audience sizes and profiles and how do they segment them under Performance Max or Advantage+. It sounds like the use of AI on ad channels might be 𝘩𝘢𝘳𝘮𝘪𝘯𝘨 our ability to optimize campaign performance. 

 

Time to approach AI data & mobile analytics differently

It is time for us to test our attribution modeling and how are we collecting data. We should start implementing testing methods under our attribution system and under the ways we’re collecting user data and invest more on predictive modeling to have a systematic approach to our user projection metrics such as LTV or ROAS.

It seems that keep holding onto MMP data and ad channel data the 𝘰𝘭𝘥 𝘸𝘢𝘺 in this new AI era and a privacy-centric approach won’t give us any leverage in advertising – no matter we’re using AI generated texts and images and AI-powered marketing campaigns. 

 

How to leverage AI in mobile advertising

The very first step that most app developers are clear about is that tracking your conversions and knowing your numbers builds the ground to help settle the business growth but it is not enough to build a mobile marketing strategy. We know that last-click attribution will be soon deprecated and implementing Firebase Analytics and Facebook SDKs into our app won’t mean we will be able to collect suitable user data from our ad campaigns.

We need first to test our own data warehouse and allocate an in-house process to calibrate our own data over time. Test the impact of your ad campaigns differently – not relying 100% on the ad channels data – and think beyond standards. Start testing your incremental impact of your marketing activities in your business – How much does your marketing boost your business and how? 

     

      • Build your in-house data system, starting to create the so-called holdout groups when doing advertising to measure your incremental impact and campaigns efficiency. Incremental testing will be one of the pillar of our new mobile privacy-first era

      • Understand the impact of ad fraud on your campaigns with the help of AI tools but including human revision processes. Check for unfamiliar metrics that aren’t matching usual patterns

      • And calibrate your LTV and ROAS over time and other user projection metrics you might be relying on

    In this new era of mobile privacy and AI automation we need to be cautious about the way ad channels are collecting data and find the most suitable solutions to maximize mobile advertising and leveraging AI in business.

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