APPLovin - Impacts of Privacy Changes

To begin, we're going to cover some of the remaining questions from last time:

The final step here is to cover the last question posed earlier:

1. Are there differences in the data you can collect from users across jurisdictions?

Apple: Although data privacy laws differ, ATT is a global implementation so for this analysis differences in data access will be assumed to be non-material across jurisdictions

Google: AAID/GAIDs are still available across jurisdictions, but Google plans to depreciate access to advertising IDs over time. Currently, Google is looking to use user-selected topics to personalise ads over advertising IDs. Developers will still be able to get user-specific data on the apps they developed. This information and any past ads seen by the user are stored locally.

New advertiser targeting will be done through specific audience lists, which means each device stores a distinct identifier/flag that identifies it as part of an audience list.

Advertising networks then use these audience lists to suggest personalised ads, and bidding is from advertisers targeting the audience lists that the user is in.

i.e. I am now sending you which audience list I am in, rather than sending you all of my information for you to determine my price point

How Does Differential Privacy Play Into This?

Differential Privacy:

Differential privacy is the act of adding random noise to user information to improve anonymity within a dataset. Within the context of Google's privacy sandbox, this means that there is noise added to a user's list of interests (if the user is interested in gaming and finance, it may add a third category called health). However, consistent identifiers (IP addresses, location, device type data) can still be used to fingerprint a user.

Additionally, when an application requests ad personalisation, it can only make one request to the Topics API per week, receiving a topic from the user's top 5 interests across up to 3 epochs (with each epoch representing a week). As a result, the ad network may receive up to 3 topics selected from a potential pool of 15.

In terms of reporting, this means noise is added to ad reporting, and the system only provides aggregated insights. Instead of knowing whether user X made a purchase as a result of an ad, it will generate a report saying that over 1000 clicks, 5 users made a purchase.

Obviously, this will affect the ability of auction platforms to maximise the value of bids for ad slots, as advertisements should become less effective (lower CTR, conversion rate) on a macro level.

Hence, once these new privacy changes are rolled out, we will likely see ad revenue across the industry decrease.

The exact percentage of this impact on AL's revenues will need to be modelled (potentially by looking at competitors when apple implemented the IDFA changes), but this is no doubt a significant downside risk.

Other questions that flow naturally from this include:

1. How have the IDFA changes affected AL compared to direct competitors?

• look at revenue flows immediately following IDFA changes compared to competitors

1. What percentage of AL's revenue comes from users on Apple?

• how can we meaningfully determine this? how can we meaningfully determine what percentage of their revenue comes from users on Android?

1. How might market participants react to any new rules/regulations?
2. What is AL's current performance in MAX and AD compared to competitors?

• where can we find a reliable data source for this?

1. What is AL's market share in the markets in which it operates?

• where can we find a reliable source for this?

1. What do their margins look like and how does this compare to competitors?

• competitor identification here is key

1. Right now, Foroughi claims that AL has no real sales team, and their sales mostly come organically from WOM. What's stopping competitors from creating their own version of AXON 2.0 (and is AL even fundamentally performing better than competitors)?

• what is Applovin's sales pitch?

Hence, the next update will be focused on AL's competitors. Then, we will dive into the financial modelling of this company.


Although the layout of this research process has shifted somewhat as expected, we have just about finished looking at the core business (except for some key figures, which will be updated during financial modelling) and will now move into looking at the competitive landscape, with technicals to follow.

Please leave any comments or suggestions you may have, and I'll be sure to take them into account for next time.

Price at time of writing: $490.75 USD