GOOGL--Well placed to be AI king? Plus FH24 result comments--TOP10 position

 Understandable business

GOOGLE is the world's largest advertising company. Driven by the success of its search engine, the economics of the “pay-per-click” model and the secular shift to online advertising GOOGL has been one of the most successful businesses ever. Search remains the core product and with over 4b users, the aggregated search data generated allows GOOGl to continually improve results, drawing in more users and completing a strong competitive barrier. The drivers are the number of searches, the ability to attach ads to those searches, the click-through rate and the rate per click. The other main part of the ads business is Networks, where GOOGL runs the ad part of third-party websites, and arranges and places ads. This is a more cyclical and less strategically well-placed business, expected to lose share over time.

Online ad penetration sits at 61% for the US increasing about 1% per year. Potential growth can come from ROW, as well as most searches are not monetised at all (est 80%). Therefore despite the saturation, reasonable growth is on offer.

Search remains the domain of GOOGL, it essentially rules this space with 90% share. The share has remained high for a long time. Search is significant at around 60% of revenues and probably a much higher share of profits. The risks here are multiple. The advent of AI-generated information could potentially disrupt the dominance. How this plays out is unknown and could take many paths, the main issues as I see them are as follows. Firstly, it is likely that the share of queries on search as a percentage of the whole will reduce. That does damage the huge information advantage that GOOGL has over everyone else, the extent and timing are unknown. GOOGLE has a couple of advantages. Firstly, it probably has time, the transactional-related searches are, at this stage, less likely to be the most vulnerable compared, for example, the creative or in-depth data gathering or research searches. That outcome is not great but not disastrous at this stage. GOOGL has tome to respond which is critical. Secondly, GOOGL is not in denial over the AI threat and appears to be willing to match spending on AI advancement at the expense of profits to attempt to safeguard the search domain. The success of this strategy will not be apparent for some time and, I suspect, sentiment will wax and wane. Big question can the search business be counter positioned and what will management do in this case?

Besides search, GOOGL has other large customer products.

1)     Google Photos: >1.0 bn users

2)     Google Maps – partially acquired in 2004: >1.0 bn users (MAUs)

3)     Gmail: >1.8 bn users (DAUs)

4)     YouTube – acquired in 2006: >2.0 bn users (MAUs)

5)     Google Play Store: >2.5 bn users (MAUs)

6)     Android – acquired in 2005: >2.8 bn users (MAUs)

7)     Google Workspace: >3.0 bn users

8)     Chrome Browser: >3.3 bn users

Some of these are directly monetising businesses such as YT, Play and Maps, others such as Chrome (browser) and Android (mobile) allow GOOGL to influence and embed the search function.

Google Play and Apple’s App store are an app store duopoly around their respective devices.

The ability of GOOGL to accumulate and analyse first-party data is second to none and the amount of touch points and interwoven access to customers through various channels is enormous.

GOOGLE has adopted a strategy of partnering with others to embed themselves and is willing to share revenues to do so. Including, Android phone makers, Apple and YT creators. The Apple partnership is particularly big and remains a risk if outlawed or Apple changes its strategy. GOOGLE pays Aapl est $21B pa. for default search settings on iPhones.

There is a growth opportunity for YT as more ad dollars are expected to move from US linear TV ($175B 2022) to CTV market ($16b) in the future. YT can offer a more targeted viewer base. YT is also building up its less cyclical subscription business. YT is the number one, viewed streaming TV service and second only behind Disney for broader media.

In Cloud (GCP), GOOGL is the third largest operator behind AMZN and MSFT. Although it is difficult to see GCP catching the two larger incumbents, the ability to profitably grow this business, together with the synergies of AI expansion make the cloud vital to the story. The cloud industry is forecast to grow as enterprises move server users to the cloud, but also the expansion of AI allows GOOG to offer the complete package and advance its AI ambitions with its infrastructure. GOOGL appear to have identified security and AI features as its differentiation in this market.

A former Sales Director for EMEA at Google Cloud explained well where Google’s advantages and disadvantages are compared to AWS and Azure:

· Disadvantages: less extensive range of infrastructure applications, less spread of data centres (although they are working fast to open many new areas, including Europe), a smaller array of offerings, and less strong sales team and partner channels than the other two.

· Advantages: flexibility, easier to manage if you have hybrid clouds, advantages in use cases like big data, machine learning, artificial intelligence, and analytics; better connectivity and flexibility when it comes to open-source software

The use case where many industry experts agree is that for AI, Google has the most advanced developments and setups and as the percentage of spend on cloud shifts more towards SaaS products and AI and less towards infrastructure Google might have an edge here. So even though GCP is smaller than AWS and Azure it’s growing at similar rates as the other two and it seems it has solidified itself as the number three public cloud provider. The perception of GCP in the developer community has also improved a lot from what it was just a few years ago when nobody would even think to compare it to AWS or Azure. Google’s benefit is also that Google and YouTube are GCP’s best and biggest clients. Also, with the transition into more video content, GCP should benefit from Search and YouTube needing more computing power but at the same time having a strong cloud infrastructure can also be an advantage for YouTube and Google Search as the discovery engines are using more AI algorithms for recommendations for content as well as for ad monetisation.

 

Waymo is GOOGL’s self-driving technology and operates at sizeable losses. Competitors have begun to exit this space and GOOGL and TLSA appear the main remaining chances of success in this field. GOOGL appear to have identified Waymo as the best chance in the Other Bets portfolio and has committed another $5B (6/24). A continuation of its historic capex run rate. “Other bets” is a 4% charge on ebit, which could be worth a positive value.

The AI threat to GOOGL can be couched in terms of whether GOOGL can innovate faster than the competition can get distribution. GOOGLE appears to be improving here in both areas. Early days but we are seeing the ability of the search business to be flexible regarding integrating the useful parts of AI and staving off competition. Large language models could be similar with a few ultimately being dominant. GOOGL is very likely to be one of these. Data resources and integration into distribution will then be critical. The ability of GOGL to keep users, advertisers and content providers engaged and supportive of the value proposition is important.  

Amazon will continue to gain advertising share in its e-commerce niche. They already have a reasonably large advertising business and it is difficult to see how GOOGL can stop this where AMZN has customers that limit their searches to AMZN and not on search. The result will be a drag on revenues to some extent

Regulatory issues are a risk for GOOGL. They come in various forms, competition/antitrust (search, play), privacy, security and content/safe harbour for websites. Large payouts from time to time can be expected but an existential threat is not considered likely from this area.

The company points out the margin challenges due to changes in mix, eg. EM/DM, Desktop to other modalities, YT/Play lower margin than search and that AI spending could impact margins as user experience is sought before monetisation. Product mix between, ads, devices, subscriptions, platforms and cloud could lower the margin.  TAC is expected to continue to grow.

Current result FH24.

The Fh24 result shows solid yet slowing revenue numbers.  There was a cycling of strong numbers. Efficiency gains were noticeable.

The focus was on the AI capex spend and on any size or timing of a return that could be generated on the massive investment program.

GOOGL comments-

We are pleased to see the positive trends from our testing continue as we roll out AI overviews, including increases in search usage, and increased user satisfaction with the results.

People who are looking for help with complex topics are engaging more and keep coming back for AI overviews. And we see even higher engagement from younger users, aged 18 to 24, when they use search with AI overviews

Beyond AI overviews, AI expands the types of queries we are able to address and opens up powerful new ways to search.

We've always wanted to build a universal agent and it's an early look at how they can be helpful in daily life. (ed. that would be big!)

And we are focused on matching the right model size to the complexity of the query in order to minimize the impact on cost and latency.

AI-driven improvements to quality, relevance, and language understanding have improved Broad Match performance by 10% for advertisers using Smart Bidding. Also, advertisers who adopt PMax to Broad Match and Smart Bidding in their Search campaigns, see an average increase of over 25% more conversions or value at a similar cost. (AI-enhanced products for advertisers)

However, in the third quarter operating margins will reflect the impact of both the increases in depreciation and expenses associated with the higher levels of investment in our technical infrastructure, as well as the increase in cost of revenues due to the pull-forward of hardware launches into Q3.

Obviously monetization is something that we would have to earn on top of it. The enterprise side, I think we are at a stage where definitely there are a lot of models. I think roughly, the models are all kind of converging towards a set of base capabilities. But I think where the next wave is, working to build solutions on top of it. And I think there are pockets, be it coding, be it in customer service, et cetera, where we are seeing some of those use cases seeing traction, but I still think there is hard work there to completely unlock those

People are deeply engaging with Gemini models across Vertex and AI studio. We now have over 2 million developers playing around with these things, and you are definitely seeing early use cases. But I think we are in this phase, where we have to deeply work and make sure on these use cases, on these workflows. We are driving deeper progress on unlocking value, which I'm very bullish will happen, but these things take time. So -- but if I were to take a longer-term outlook, I definitely see a big opportunity here…………..obviously, we are at an early stage of what I view as a very transformative area and in technology when you are going through these transitions, aggressively investing upfront in a defining category, particularly in an area in which in a leveraged way cuts across all our core areas our products, including Search, YouTube and other services, as well as fuels growth in Cloud and supports the innovative long-term Bets and Other Bets is definitely something for us makes sense to lean in………….I think the one way I think about it is when we go through a curve like this, the risk of under-investing is dramatically greater than the risk of over-investing for us here, even in scenarios where if it turns out that we are over investing. We clearly -- these are infrastructure, which are widely useful for us. They have long useful lives and we can apply it across, and we can work through that. But I think not investing to be at the frontier, I think definitely has much more significant downside. Having said that, we obsess around every dollar we put in. (ed. GOOGL losing not a mind set here, rather overspend than leave the door open)

I think we (hyperscalers) are all pushing very hard, and there is going to be a few efforts, which will scale up on the compute side and push the boundaries of these models. What I would tell is regardless of how that plays out, you still think there is enough optimizations we are all doing, which is driving constant progress in terms of the capabilities of the models. And more importantly, taking them and translating into real use cases across the consumer and enterprise side, I think on that frontier.

These comments point to encouraging early signs but the real work is ahead. The model build phase will move to an implementation of real-world cases. That could cause some inconsistency in returns. With large upfront investment without a certain return profile. As GOOGL states the option of losing is not considered an option for them.

 

Operating History

Operating results are solid but vary a bit for such a dominant large company. Perhaps this is as economic sensitivity grows as the company matures.

Revenue growth: 5Y rolls averaged 20%, with a range of 18-23%pa. EPS growth has averaged 5Y roll of 22%, with a range of 2-38%, so some volatility exists. TA has grown 5y rolls of 12-17% and is slowing. ROE on the other hand is increasing, has averaged 18%, with a range of 13-30%.  GM has averaged 56%, maybe low due to TAC etc being taken at this line, with median variability. NPM has averaged 22.5%, with a range of 17-30%, Currently 24%.

CF generation has been strong for the group, but we see 34% of FCF going into capex over the last 3 years and 37% over the last 5 years.

Forecast ROE of 31%, together with a reinvestment rate (historic) of 53% gives a MCniven PE of 21X.

Management

The GOOGL culture and management is quite unusual. The company's history has been one of never having to struggle from the start and being flush with cash. Over time that has manifested itself in varying capital allocation, over the last several years and could be criticised for not being too successful. Notably with the recent challenge to search there appears to be a positive change. Management has commenced what appears to be a significant cost-cutting operation and allocating resources to AI at the expense of moon-shot bets and other projects.  We have seen efficiency improve.

Management's ability to execute has been mixed. The initial attempts at integrating AI into the search function and LLM have been mixed but adequate. The Subscription strategy makes sense it would add to the strength of the business, but execution is key. The business model is more subtle than producing/selling phones or software, taking skill to be relevant and efficient.

Management is not in the MSFT and AMZN mould in terms of having aggressive GTM and monetisation drive and can be described as stable, considered and watchful.

Transferring the CFO to Other Bets looks like a sign of more aggressiveness on costs. Certainly, there is likely to be much fat in the GOOGL operations. Expense control will help margins.

GOOGL is legendary for staff benefits.

Balance Sheet

The balance sheet holds an enormous amount of net cash. The company buys back stock but also has a large SBC. CF reconciliation is good  (3Y 105%, 5Y 106%) and Cf generation is strong.

Other

SBC is enormous at 7% of revenues and 30% of NPAT. Much of the FCF is taken neutralising this issuance.

PE historically has been 30X with a low of 20X. The past historic rating is probably not as relevant in the future.

The market is focused on GOOGL's ability to stay relevant in its various businesses, search, YT and cloud given a dynamic AI environment. GOOGL appears to have allayed fears of existential risk but changes are possibly large and uncertain.

The current capex arms race between the hyperscalers, GOOGL, MSFT, AMZN META et al, is leading to many questions. Like how much is the likely capex spend, for how long is it likely to go on for and what is the return profile on this spend. As the path becomes known the outcome will shape the players' businesses.

CONCLUSION - VALUATION

GOOGL is a cash machine that is an incumbent but is also proactive in the challenge. Will GOOGL be counter-positioned in the future? Given the comments above is likely they will destroy the existing businesses and reinvent themselves rather than become irrelevant. The chances of that occurring are not straightforward. GOOGL has the huge advantages of incumbency, an R&D bank, a data bank and enormous distribution. There is a risk that the results will lag as GOOGL puts customer user satisfaction before monetisation. They wll invest and take the pain with the aim to achieve a better longer-term company is my read. All these issues could cause some volatility going forward for the business and the share price.

A 15% eps growth for the next five years and a 22X exit rate give 8% pa returns, at $178. 10% return at $160.

 

 

 

 

 

 

 

 

Please note the disclaimer.

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