Moats & Multiples

Global Equity Analyst | London | Investing in the world's best businesses | Not investment advice

[Moats & Multiples @moats_multiples]

Ask most investors to name a Swiss stock and you'll hear Nestlé, Roche or Novartis.

Almost nobody says Swiss Marketplace Group. It owns the country's #1 property, car and classifieds sites, and I expect EPS to double by 2030.

Three monopolies for the price of one:
https://t.co/A4YjBo7xYN

[Moats & Multiples @moats_multiples]

Taking some accountability for his actions would be good. Irrespective of whether you think FICO scores are severely underpriced or they are Pulte’s punching bag, the rate at which Lansing increased prices drew the ire of regulators and opened the door for competition. Whining about being attacked shows seriously little self awareness. On top of this he has torched shareholder capital by doing levered buybacks at a materially higher share price.

[Moats & Multiples @moats_multiples]

$FICO CEO just lost the plot on Q4 earnings call!

“Ashish, I guess I can't blame you for asking the question, but maybe it's time for me just to explain a little bit of a change in philosophy and in how we talk about our pricing and our programs and so on. I know, I think you all know, it's no secret that transparency and detail on our programs and pricing have not been particularly helpful for FICO. We were of a view for many years that because the FICO score at $10 or $4.95 or whatever we were charging, was such a tiny fraction of overall closing costs, we really didn't think that the price was a very big deal. We thought that the value so far exceeded the price that why not share details around the pricing just so that everyone understands how little it is in the scheme of things? As you all know from watching events over the last several years, we've really been attacked for, you know, what we consider to be, you know, not very good reasons. We're attacked because we're transparent and clear about our score price. As you all know, the credit files cost a lot more, credit evaluation costs are much more.

In fact, every other element of the closing is a lot more than what FICO charges. Yet somehow FICO has become the poster child for affordability in housing, which is just a crazy thing. Internally, we have had a lot of conversations about has this transparency been helpful, and the conclusion is no, it has not been helpful. I think you guys know that we have probably been in the top decile of open transparent, help everyone outside understand what we are doing inside, but it has not really worked very well for us. On a go-forward basis, our intention is to not share every detail. We are not going to share every pricing program. We are not going to share what the prices are. We are not going to share all of the terms. They are going to be customized, but by customer to meet customer needs. We are just not going to provide all that kind of information. To your very specific question, is the average price of a FICO Score going up, down, or sideways? We are not going to answer that. You guys who have been watching us and watching the industry can understand exactly why we are not going to answer that.”

Yikes 😬

[Moats & Multiples @moats_multiples]

@firstadopter None of the great investors have a 100% hit rate. He has made some poor calls on tech in recent times but I continue to believe his portfolio is well positioned to compound at attractive rates for many years to come. Plus his total tech exposure is small.

[Moats & Multiples @moats_multiples]

I can see where agents take on the burden for more search but people still like to discover things. No one is asking their agent to just book them a holiday. They will spend time researching a destination and then perhaps the agent does the grunt work of planning an itinerary and booking the logistical elements. The future will be somewhere between the two extremes.

[Moats & Multiples @moats_multiples]

I've been thinking about the implications of AI for Google's ($GOOG) Search business and I think there are two very different ways this could play out.

Just looking at my own usage, I'd estimate the number of websites I actually click on has fallen by ~80% yet I'm probably consuming more information than ever before.

Historically, Google operated a remarkably effective exchange. Websites produced content, Google organised it and directed free traffic. Advertisers paid Google for access to that traffic. AI fundamentally changes that arrangement as Google (and others) can satisfy the user's query without directing them to the underlying source.

But does this destroy value for Google or allow it to capture more? Consider the following two scenarios:

Scenario 1 - Cannibalisation
Google makes search a materially better product for consumers, but the economics deteriorate. Click-through rates collapse whilst the cost to resolve a query increases due to higher compute usage.

At the same time, the websites producing the information become less economically viable as their traffic evaporates, undermining the entire ecosystem Google helped create.

The result is a better user experience at the cost of a smaller and less profitable line of business.

Scenario 2 - Consolidation
As organic search traffic declines, businesses still need to acquire customers. If AI becomes the default interface for discovering products and services, businesses could become increasingly dependent on paid distribution. And because AI queries contain far more context about what users actually want, Google could potentially deliver more qualified leads to advertisers.

Better conversion rates would allow Google to charge more without necessarily compromising advertiser returns.

In this scenario, Google captures an even greater share of the economics previously accruing to businesses through organic traffic. Companies with differentiated products and services can afford to pay more for customers, whilst those dependent on cheap traffic struggle.

The result is a business that potentially earns more from fewer clicks, despite the higher cost of serving each query.

I'm personally more inclined to believe the second the scenario but interested to hear how others are thinking about this.

[Moats & Multiples @moats_multiples]

@SMone7337 I think Meta's platforms are generally more conducive to "discoverability" i.e., finding things you didn't know you wanted. Search has been more catered to answering specific questions. YouTube and maybe Maps are probably better applications for pure interest targeting imo.

[Moats & Multiples @moats_multiples]

@bgill12971631 Good point, as cost per token asymptotes to the cost per electron then the cost to serve for Google falls dramatically.

[Moats & Multiples @moats_multiples]

@freetinkerer But even those non-commercial queries directed traffic to websites which themselves were dependent on ads to some extent e.g., news and media outlets. What incentive do they have to keep creating content if AI trains on their data and resolves consumer queries?

[Moats & Multiples @moats_multiples]

@MercilessWei This is the delicate balance that I think Google needs to figure out. Monetisation of AI enabled search whilst maintaining consumer trust.

[Moats & Multiples @moats_multiples]

"Compute is procured and committed in advance and the expense is incurred as it is brought online and added to our fungible pool, often in large, discrete steps."

This statement in Anthropic's S-1 highlights the crux of why it is inherently so difficult to gauge the future economics of AI/neocloud/semiconductor companies.

Demand follows a generally continuous curve (in this case exponential). Supply comes online in discrete blocks. Moreover, investment decisions are made well in advance of knowing what the demand will look like.

Right now, the demand for compute is growing so quickly relative to available supply that the economic justification for investing in additional capacity appears relatively straightforward.

However, there will come a time where demand growth inevitably moderates. The problem is that supply coming online at that point will reflect investment decisions made 12-18 months earlier, when expectations for future demand were considerably higher.

Demand doesn't even have to decline, it simply needs to grow more slowly than the rate at which new capacity is added. When the two lines do intersect, there is a big problem.

This is where the economics deteriorate remarkably quickly. As successive blocks of supply come online, utilisation begins to fall. Providers compete to fill excess capacity, rental prices decline and returns on invested capital compress. With much of the new supply being debt financed, that creates another vector of risk.

In fact, the irony in all of this is that the today's extraordinary scarcity may be precisely what creates tomorrow's oversupply.

There are plenty of people on this platform who are far more knowledgeable than me on AI and its implications. I am also certainly no AI bear.

I don't question whether AI demand will continue growing. I question whether it will grow fast enough, at sufficiently attractive prices, to absorb the enormous amounts of capital being committed today.

[Moats & Multiples @moats_multiples]

I'd say significant but it depends completely on usage. Users will follow a power law curve and their propensity to pay will depend on derived/perceived utility. Creating additional tiers of pricing enables more people to pay based on their levels of engagement. Adding more features prior to raising prices across all tiers improves perceived value.

[Moats & Multiples @moats_multiples]

Some thoughts on Spotify ($SPOT) post Q3 earnings:

1) Whilst the business continues to add subscribers at an impressive pace (25m+ each year since IPO), the real story is that each subscriber is becoming materially more valuable. Premium gross profit per subscriber has been on an upward trajectory and annualising Q3 rates would put it at close to €20 per sub. Pricing and better content economics are translating to materially better unit economics.

2) At the same time, growth is becoming increasingly self-sustaining. Total MAUs has grown 5x since 2017 whilst SG&A intensity has nearly halved. Spotify is adding millions of users without needing a proportional increase in the cost base to acquire and support them.

3) Put the above two together and the earnings algorithm looks very attractive. Spotify is adding users + monetising them better + spending less on acquisition and support. Looking at pure subs growth therefore misses the forest for the trees.

4) I still think Spotify has considerable latent pricing power. Premium ARPU increased to €4.95 during the quarter despite healthy subscriber growth. Mgmt's playbook seems fairly clear: improve the product, drive engagement, monetise.

5) AI is potentially reinforcing the company's moat. Spotify's recommendation engine is powered by granular proprietary data about user preferences. Features like mixing tools tell Spotify how users interact with individual songs. Agentic interfaces like Muse can tell Spotify, in natural language, exactly what users want to hear and why. That data feeds the recommendation engine which improves engagement, retention, and ultimately LTV.

6) The company now boasts nearly €10bn of cash on the balance sheet with no debt. Mgmt was clear about returning more excess capital to shareholders.

[Moats & Multiples @moats_multiples]

Chart created by Fiscal AI (https://t.co/ySBh2PdZK2)

[Moats & Multiples @moats_multiples]

I appreciate the point you're trying to make here but I think comparing Uber to a franchise model falls short on several accounts.

1) A McDonald's franchisee makes a dedicated, largely irreversible investment to participate within its system. Uber driver's have existing capital that has been deployed on an asset not earning a return. For Uber to be successful they simply need drivers' marginal earnings to exceed their opportunity cost.

2) Uber drivers are more akin to suppliers than they are to franchisees. Uber itself operates a network, bringing guaranteed demand to the drivers. The point on what a fair take rate should be is open to debate but supplier economics are generally going to trail that of the network owner.

3) Uber drivers are not locked into a system, they have a real option to either not drive or switch to another app. The customer side of the network dictates the demand and Uber should have the right to earn a significant return in creating an efficient marketplace for all participants.

[Moats & Multiples @moats_multiples]

Couple of interesting takes related to AI from $MCO 3Q26 earnings call:

1) AI related issuance has accounted for a little over 50% of YTD issuance growth (i.e., 6 points of issuance growth) and around 40% of revenue growth (i.e., 4 points of MIS growth). In rough numbers that's $300b+ of incremental issuance and $130m of incremental revenue.

2) CEO said there is "plenty of demand" for AI and that "companies would issue more debt if they could" to fund the build-out. This tells me two things. First, there's probably plenty of runway left for AI growth. Second, not every point of growth is equal and as more of this growth is debt funded, it inherently carries more risk.

3) Moody's analysts estimate ~$800b of hyperscaler capex in 2026 rising to $1t+ in 2027. A significant proportion of this is likely to be debt financed which is issuance positive but yield negative for the ratings agencies.

4) Large financial institutions (historically tech laggards) have significant investment agendas as it relates AI investment so budgets are substantial. However, their willingness to pay more is tied to outcomes.

5) Moody's MCP user growth has been 4x in the past three months with usage increasing 10x. Paying MCP users has doubled and while this is still small, could represent meaningful upside to MA growth in time.

[Moats & Multiples @moats_multiples]

My take from $NFLX 3Q26 results:

1) Weak engagement has not yet translated to weak monetisation. US/global churn improved yoy despite price increases. Memberships continue to grow and UCAN revenue still grew 11%. The consumer proposition remains strong.

2) US engagement is clearly the biggest concern from the market. Mgmt admitted the US "isn't growing as fast as it could" and needs more homeruns. Hiring Peter Rice as CCO looks like a direct response to weak execution rather than a change in strategy.

3) NFLX is spending aggressively to fix this. YTD cash content spend is up ~19% and additions to content assets are up 24%. FY26 cash content spend should approach $20b vs. $18b last year (according to prior mgmt commentary).

4) The important question remains whether an incremental dollar of content spend earns the same or better returns as previous dollars. Roughly 5% of spend (~$1b) is now going to live events, despite it driving only ~1% of viewing hours. Mgmt argues the payoff comes through user acquisition and ad load but the hurdle rate on content spending is changing.

5) With cash content spend coming down significantly as a proportion of revenue, margins have inflected over the past five years. That said, the next leg of margin expansion gets harder because its more dependent on revenue growth as amortisation will catch up with higher spending (especially with higher live mix).

6) I wouldn't treat layoffs as a major new margin lever. Annual cost savings should be $200m+ (rough math: median salary of $200k x 1,000 staff). Mgmt explicitly said the cuts create capacity to reinvest in growth. Looks more like resource allocation towards content and product.

7) Thesis doesn't seem to be fundamentally broken but the upside has changed. NFLX seems to be progressing in its natural maturation curve and investors want to see the business delivering continued growth with incremental content spend that earns a very high ROI.

[Moats & Multiples @moats_multiples]

@MtnTimeInvestor I agree, biggest risk I see here is a knife fight on take rates to win agentic volume. Potentially depresses margins near-term but growth in volumes more than makes up for it in dollar profit growth.

[Moats & Multiples @moats_multiples]

This is the creation of a new wave of demand for the likes of $UBER (among others).

My view is that agentic AI will not only improve conversion but it will create entirely new transaction volume.

Zuck himself states his usage of Instacart expanded massively after Muse began executing purchases on his behalf.

As agent adoption grows and these agents move from answering questions to continuously acting on our behalf, the friction cost of ordering a ride, meal, groceries, or deliveries collapses.

The biggest beneficiaries of this shift in consumption habits will be scaled players with real-world infrastructure in place to facilitate such transactions.

The way I see it, agentic AI doesn't shrink the TAM for Uber but it dramatically expands it.

Source: Cheeky Pint - Zuckerberg’s $100 Billion Bet