Mobile Dev Memo

The site of record for the mobile industry. Mobile advertising, freemium monetization, and performance marketing.

[Eric Seufert @eric_seufert]

Netflix’s second advertising pivot

"I believe that Netflix should pivot its advertising business once again, spawning a third period in its advertising arc. This new period could be defined by three strategic shifts:

1. Opening the Netflix Ads Suite to direct, self-serve buying

2. Offering a substantial proportion of its mobile games for free, monetized by its own ad platform and with no Netflix login required

3. Introducing a free, ad-supported tier in certain Western European and Asian markets, with a goal of ultimately rolling it out worldwide"

https://t.co/ft18iCapfH

[Eric Seufert @eric_seufert]

Value propositions for third- and first-party agents

"So if third-party agents are effectively fetching and re-sorting the output from retail platform agents, meaning the purpose they serve is principally discovery, and retailers can play agents against one another on commissions, what monetization model are third-party agents left with for the commodified purpose they serve in eCommerce? Increasingly, it looks like advertising."

https://t.co/W2QhVkMFdd

[Eric Seufert @eric_seufert]

How big is Google’s AdMob?

“The composition of Google’s Network segment revenues has always been opaque. But the segment has, at least in recent history, also been somewhat economically immaterial; I characterized it as “vestigial” in 2024 (see also the second part of that series).

Network contributed just 9.1% of the company’s advertising revenues in Q3 2026, and the delta between Network and YouTube has grown to nearly $4BN since YouTube first eclipsed Network in Q3 2023. That said, the fact that the Network segment grew for the first time in 17 quarters in Q3 is worth unpacking, particularly given the specific in-app context of AdMob.”

https://t.co/KKbSPIutlV

[Eric Seufert @eric_seufert]

I wrote the first entry in the Google’s Gambit series two years ago, in October 2024. My point at that time was Google was re-architecting its core revenue engine from an “engagement distribution” mechanism to an “engagement sink,” and that by doing so the company could increase engagement and potentially monetize that augmented time spent.

The real question now isn’t “is this happening?,” because that question was answered two years ago. Yes, AI Overviews and AI Mode are subsuming engagement. The forward-facing question is whether those new content formats can — in six months, 12 months, 24 months — monetize at parity or better than the legacy product.

[Eric Seufert @eric_seufert]

Amazon made two things plain in its earnings call last night:

1) It expects its on-site agent, Alexa for Shopping, to be "the primary shopping agent customers use to shop Amazon," meaning it seems unlikely to meaningfully open its catalog to third-party agents for agentic shopping tasks, and
2) Alexa for Shopping has seen significant adoption by Amazon customers, with over 400MM customers having used it in the trailing 12 months.

To my mind, the notion that (third-party) Agentic Commerce is a Mirage has already been demonstrated. For instance, Tony Xu noted in the DoorDash call this week that third-party agents had completed "several hundred orders in total" on its platform. There is no "there" there with Agentic Commerce; platforms have an inherent, insurmountable data and capabilities advantage with shopping tasks and their own agents will outperform the third-party agents that are even given access.

And those third-party agents are increasingly starved of access. Walmart recently published its Agentic Access Terms, and the company forces third-party agents through Sparky for autonomous checkout, meaning they effectively just remit Sparky output. Jassy noted on the Amazon call that the company does "anticipate working with horizontal agents," but my sense is this will look either like *advertising* deals (Amazon struck such a deal with ChatGPT last month) or Walmart's access terms, broadcasting Alexa for Shopping into third-party surfaces.

I've seen analysis attributing the deceleration in Amazon's advertising business (26% in Q2 to 11% in Q3) to third-party agentic commerce. This is absurd on its face. First, Jassy said as much on the call. Second, Amazon *blocks* external agents, so by definition, endemic brands would not see their ad spend displaced by third-party agentic discovery. And third, and most importantly: Prime Day moved from Q3 to Q2 in 2026.

Third-party agents will fulfill the discovery role in commerce, which means that advertising is the most natural business model for them. Everything is an ad network.

[Eric Seufert @eric_seufert]

Alphabet Q3 2026 earnings: AI Mode’s monetization penalty

Q3 2026 may mark a turning point for Google Search. The original bear thesis, that engagement would migrate to chatbots, has been demonstrably refuted, but the second bear thesis, that monetization in AI Mode must be structurally weaker than legacy Search, remains salient.

While we don't know how AI Mode ad monetization will ultimately resolve, Meta's experience with Reels offers helpful guidance; AI Mode won't necessarily be a permanent drag on Search ad revenue.

I unpack this in more detail in my analysis of Google's Q3 2026 earnings. No paywall.

https://t.co/uuQTCQuPEZ

[Eric Seufert @eric_seufert]

Apple’s identity-resolution block is not ATT for the web

"I’ve seen Apple’s new identity resolution service-blocking policy be compared to the company’s App Tracking Transparency (ATT) policy, introduced in iOS 14.5 in 2021.

Although I was vocally critical of ATT at that time, I take a different view in this case; I believe that Apple’s justification for blocking these so-called identity resolution services is defensible, differs in material ways from ATT, and, ultimately, serves the best interests of the consumer without directly privileging Apple’s advertising interests."

https://t.co/Kl4gxga4b6

[Eric Seufert @eric_seufert]

Walmart’s MCP server is generally misunderstood; it doesn’t provide carte blanche catalog / transaction access and, if anything, is further support for the idea that Agentic Commerce is a Mirage.

First, Walmart is allowing third-party agents to *connect to Sparky*, its own on-platform agent. This is an agent-to-agent gateway. Walmart retains the consumer data and first-party consumer relationship. And Walmart exercises fundamental control over product discovery and recommendations if Sparky is the agent interface.

Second, autonomous checkout is permitted only under Walmart's conditions. Consumers must authorize the agent through their Walmart account and establish permissions and spending limits, which Walmart enforces. To use the Gateway, the consumer must connect their agent to their Walmart account by authenticating directly with Walmart. So Walmart continues to accumulate user-level purchase data for use in a) the product recommendations returned by Sparky and b) Walmart Connect.

Third, third-party agents are restricted from using Walmart’s data for any purpose that could possibly intermediate Walmart. From its terms:

An Agent or its Deployer must not: (a) conduct systematic or bulk scraping, collection, storage, or other use of Walmart Proprietary Data; (b) retain Walmart Proprietary Data beyond what the Permitted Purpose reasonably requires; (c) use Walmart Proprietary Data to generate content, target advertising, create synthetic data, train models, or produce commercial analytics, reporting, or data-licensing products; or (d) license, resell, syndicate, or redistribute Walmart Proprietary Data to any third party.

Walmaet’s agent gateway relegates external agents to distribution interfaces, and it preserves Walmart's first-party consumer relationship and advertising economics. This isn’t a strategic embrace of third-party agentic commerce.

I was going to publish about this last week but got sidetracked by $META earnings. Post going live tomorrow.

[cfarm @cfarm54]

great pod by @eric_seufert on how ads fits into the bigger dynamic $googl ecosystem https://t.co/byNXArI6mQ

[Adam Epstein @aepstein_]

I joined @eric_seufert on the @MobileDevMemo podcast this week to talk about Amazon and agentic commerce.

The jumping-off point was a question I wrote about a few weeks ago: why Amazon blocked Meta’s Muse and welcomed ChatGPT Ads into the DSP in the same month.

What we covered:
- Why retailers’ economic incentives may stop them from fully embracing open agentic commerce platforms
- How Amazon’s retail signals (ratings, pricing, inventory, Prime eligibility) inside ChatGPT could change how consumers shop
- If people’s desire to browse limits mass adoption of autonomous shopping agents
- What happens to brand relationships when an agent mediates the entire path to purchase
- Whether Amazon’s control of the full ads and logistics stack is an unbeatable moat against rival shopping agents

Episode: https://t.co/XweeYuvdnx

[Eric Seufert @eric_seufert]

Meta Q3 2026 earnings: interpreting early Muse metrics

I don’t think I’ve ever been tagged in as many X posts as I was yesterday when Mark Zuckerberg stated on the Meta earnings call that shopping is the most common use case for Muse, and that the average Muse transaction size is $200.

At first blush, this seems to undermine my 'Agentic commerce is a mirage' thesis. But I believe that deconstructing Zuckerberg's statements reveals a different interpretation.

I've made my Q3 2026 earnings analysis for Meta free; no paywall.

https://t.co/Y0EZVsiIEX

[Eric Seufert @eric_seufert]

The catalyst for this tweet was a conversation I had last week with a friend who is the CMO of an F100 company. I didn't want to share any details that could leak identifiable information, but he gave me permission this morning:

Like every major brand / retailer, he's considering just how permissively and fulsomely to integrate with third-party agents for agentic discovery, and how much functionality should be made available outside of his owned environment.

This is a salient and critical question! Agentic discovery could become an important part of the funnel. But in some implementations, it could also be corrosive. If agents are merely recommending his products / company among a relevant set and delivering incrementally net-new users, integrating / cooperating is essentially costless.

But that very obviously and predictably won't be the case. Some users would have been reachable with ads. Will they behave differently when exposed to an in-agent recommendation versus an ad? Will their AOV change as a cohort? What about their product journey? Will they be as reachable after their first checkout?

Of course, we don't know, so we have to test this. How do you design an experiment that captures this? How do you construct the exposure and holdout groups? How long should this experiment be run? How do we accommodate the upcoming holiday season, the paid promotion of new agents that influences their usage in ways that are unlikely to persist, and differences across categories and geographies?

These are genuine, serious challenges, and his board has been extraordinarily accommodating in allowing him to put together a thoughtful, comprehensive "agentic" strategy. But it occurred to me in speaking with him that many CMOs are absolutely about to be replaced because they either aren't given that time / space to experiment (and the CEO has a friend who is confident that he can 3X the business with his "agentic playbook") or because they say yes to everything without any clear vision for how the business will be impacted.

[Filip @filippkowalski]

Out of all the podcasts/yt around the mobile industry, Mobile Dev Memo (@MobileDevMemo) became my favorite

Every episode has fresh, unique, and insightful takes

run by @eric_seufert

[Eric Seufert @eric_seufert]

30% agent share with a 3% take rate by 2030 is extraordinarily aggressive.

Repeat this arithmetic with 5-10% agent share and the entire endeavor looks futile / indefensible.

Unless, of course, agents don't implement a take rate, which, for many reasons, can't scale to a stable equilibrium.

Rather, if agents implement ad partnerships like the one Amazon has already struck with OpenAI, allowing the largest retail platforms to integrate directly into off-platform agentic purchasing workflows while retaining control over user relationships and their advertising revenue, then everyone's incentives align, and DAU (not eCommerce share or take rate) is the only determinant of revenue.

[Eric Seufert @eric_seufert]

Using natural language user profiles in RecSys

"Spotify recently published a paper, Textual User Taste: Natural-Language User Context for Foundation-Model Recommender System at Scale (Fazelnia et al., 2026), that touches on a fascinating and timely topic of broader research at the intersection of RecSys and language modeling: whether the dense user embeddings used in candidate retrieval and ranking can be complemented with, or perhaps even replaced by, a natural language description of a user’s preferences."

https://t.co/lHy5b2QVFV

[Mostly Borrowed Ideas @borrowed_ideas]

Well put!

[Eric Seufert @eric_seufert]

Agentic commerce is not a mirage for travel

"But the travel use case of agentic commerce presenting an obvious and fairly unobjectionable alignment between retailer, agent, and consumer also hides a sleight-of-hand that some of the proponents of agentic commerce would prefer to go unnoticed: that this alignment contrasts substantially with the dynamics of retail eCommerce, and so championing agentic travel booking — which is convenient, and which does provide unambiguous value to hotel chains, airlines, and consumers alike — doesn’t serve as a blanket endorsement of the agentic commerce enterprise."

https://t.co/Y6GxgUBOSf

[Eric Seufert @eric_seufert]

Anecdotes and personal experiences can be useful tools for understanding the utility of products for specific use cases, but I think it’s a mistake to use such a narrowly-scoped instrument to try to explain the business models of trillion-dollar companies — and, more contemporaneously, why they’ll be utterly disrupted by AI. Certainly this is true for a company like Google $GOOGL, as the mechanics of digital advertising are more complex than they might appear when looking at the results for any given query.

The notion that Search merely, exclusively monetizes the results that would have otherwise been exposed organically, almost like a protection racket, is flawed. Search ads offer keyword adjacency / expansion tools, and shopping journeys start long before a consumer knows exactly which product they want to buy. Further, marketing teams can test their spend for revenue incrementality; doing so
with Google Search is straightforward. Certainly some Search ad spend is wasted but that’s true for every ad channel.

“Google Search dies because of Muse” ignores the incremental product discovery value of search advertising, the fact that Google has launched its own AI products that currently reach in aggregate billions of people per month (AI Overviews: 2.5BN, AI Mode: 1BN), the fact that Google owns the most popular browser, the fact that Google operates a mobile platform, and the fact that Google operates a suite of consumer products that are all deeply integrated.

And in the context of this specific argument, it also ignores the fact that Muse will need to generate meaningful revenue at scale and will almost certainly do so with advertising.

In some ways, Google Search has already died (and been resurrected in a different form). This is the premise of my Google’s Gambit series, which I started publishing long before Muse. The company is adapting in real time to new consumer interaction models. If consumers find agents useful for product discovery, there is no reason to believe that Google *can’t* accommodate that.

But to reduce a ~$250BN annualized business to a consumer- and advertiser-hostile protection racket, and then assume that Google cannot adapt its distribution and monetization machinery to an agentic consumer workflow (which it
already partially has, through Universal Commerce Protocol, Universal Cart, agentic checkout, etc.), is, in my view, overly simplistic and naïve.

[Eric Seufert @eric_seufert]

There are two fundamental problems with this set of scenarios related to Muse’s revenue contributions to Meta by 2030:

- A and B (worst and base), where Muse is 0.5% and 2.3% of revenue, respectively, are economically irrelevant to Meta and mean the company should shut the product down absent some second-order effects;

- the revenue assumptions in the only scenario that is commercially meaningful to Meta (C, best case, 7.8%) presume a uniformity of direction in take rate, interchange fees, and GMV share with scale that is improbable, and they ignore the opportunity cost of making Muse free and monetizing it with ads.

The first point is obvious: even with the lofty assumption of 15% eComm addressability by third-party agents (!), and 40% (!!) of Muse GMV passing through partners willing to accept a 4% transaction take rate (!!!), Muse accounts for 2.3% of Meta’s revenue by 2030 in scenario B. Immaterial. Who cares.

The second point is more nuanced. In scenario C, 60% of Muse GMV (!!!!) runs through partners willing to pay a 5% take rate (!!!!!). That doesn’t follow from scenario B; surely the largest retail platform holdouts would negotiate a lower transaction fee. That is to say: the highest fees are likely realizable by the smaller players first, and the average take rate probably decreases as total eComm penetration increases.

But more importantly: why would Meta prefer a uniform transaction fee to the auction mechanism it has spent two decades perfecting? Merchants have heterogeneous margins, conversion probabilities, customer values, product lifecycles, and willingness to pay for access to a consumer. An auction allows them to express that willingness to pay; a 5% transaction fee reduces all of that heterogeneity into a fixed percentage.

This is the opportunity cost missing from the model. Meta already generates enormous advertising revenue per user by auctioning access to consumer attention and intent, without needing to intermediate the transaction or secure a commercial agreement covering the resulting GMV.

The model implies ~76MM Muse users in scenario C. Transaction fees + interchange generate roughly $396 per user per year.

For context, while Meta no longer reports geographic ARPU, its earnings disclosures imply current US/Canada Family ARPP somewhere around ~$340/year: UCAN revenue is running at roughly $95–100BN annually against an estimated ~275–300MM daily users. And UCAN revenue grew 32% YoY last quarter.

So even in scenario C, Muse needs each US user to push $12,784 of annual GMV through the product (>$1,000 / month), 60% of that GMV to flow through fee-paying partners, those partners to accept a 5% rake on average, and Meta to capture 10bps of interchange just to generate ~$396 of commerce revenue per user in 2030.

Whereas Meta’s existing advertising machine, today, is generating something like ~$340 per UCAN daily user.

So Meta could just show those users ads.

And the latter mechanism allows merchants to bid according to the actual value of each impression rather than Meta attempting to impose a uniform fee. So the model ultimately demonstrates just how heroic the assumptions have to become before transaction monetization can approach competition with Meta’s existing advertising machine.

[Eric Seufert @eric_seufert]

Apple blocks alternative IDs in iOS 27

"Another reason to be dubious about the long-term durability of alternative identifiers is simply that Apple likely views them as inimical to its privacy goals. I wrote about the interminable game of whack-a-mole that Apple plays with advertising platforms and intermediaries alike in April 2023, when Apple closed a loophole that allowed third-party cookies to be presented as if they were first-party cookies through IP-address cloaking.

Ultimately, Apple has the resources and the patience to outlast any practices it simply doesn’t want taking place on its platforms. In that sense, every workaround or loophole always has an expiration date for the Apple ecosystem."

https://t.co/prjhp8vrkN