Apple's M&A Strategy, Explained
PLUS: Chick-fil-A, Duolingo, Bitcoin rally.
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Today, we are talking about Apple’s approach to M&A deals (and its best deals ever).
Also this week:
Chick-fil-A’s ~$22B Biz
Duolingo: Engagement Comes First
…and them fire memes (including Bitcoin’s rally)
PS. Check out the newest episode of my podcast Caffeinated Deep Dives, which is about the history of hot sauce and how a Vietnamese-Chinese immigrant turned Sriracha into a $1B+ business (Apple, Spotify, YouTube).
Apple’s M&A Strategy
Earlier this month, Apple acquired image-editing app Pixelmator. The deal helps to strengthen Apple’s creative tools and offers an alternative to Adobe’s Photoshop.
The acquisition is pending regulatory approval and is likely in the 8-figure range, which means Apple probably paid for it by finding change in the cushion of its lobby couches (the iPhone maker currently has $160B+ of cash sitting on its balance sheet).
Apple doesn’t really splurge on M&A and its largest acquisition ever was Beats Electronics in 2014 for $3B. While that headphone business has been dwarfed by AirPods, Apple took the Beats streaming service to jumpstart Apple Music (the Beats origin story slays me; a sneaker company approached Dr. Dre for an endorsement deal but Dre’s partner Jimmy Iovine intervened by saying “you should do speakers, not sneakers” … and, now, every time my wife wants to go shoe shopping, I say “you should do speakers, not sneakers”….and she ignores me but I smile knowing Dre said yes to Jimmy).
Apple’s $3B Beats deal is much smaller scale than the biggest deals from its Big Tech frenemies:
Google: Motorola Mobility in 2012 ($12.5B)
Facebook: WhatsApp in 2014 ($19B)
Amazon: Whole Foods in 2017 ($13.7B), MGM Studios in 2021 ($8.5B)
Microsoft: ActivisionBlizzard in 2022 ($68.7B), LinkedIn in 2016 ($26.2B), Nuance Communication in 2021 ($19.7B), Skype in 2011 ($8.5B), Github in 2018 ($7.5B), Nokia in 2013 ($7.3B)
Why hasn’t Apple shot its wad on a massive deal? A CNBC article in 2021 has a decent breakdown and the jist is that Apple uses M&A to acquihire talent — usually from small teams — that bring expertise for an emerging technology or tech required for existing Apple products.
Here are some more details on Apple’s M&A process:
Once-a-month frequency: Between 2015-2021, Apple did 100 deals (a pace of one deal every 3 or 4 weeks).
Smaller deal sizes: As noted, Apple’s largest acquisition is Beats ($3B) but most of its M&A deals are in the tens of millions.
Key valuation metrics: Apple typically values a company based on the number of technical employees (eg. it will pay $3m per engineer), not revenue or fundraising valuations. Hired talent gets paid out for any equity they have in the existing startup, then receive a lucrative “golden handcuff” deal from Apple with fat equity that vests over 3-4 years.
Acquihire approach: Target companies are asked to demo their technology to Apple. If there is interest, Apple’s deal team enters the conversation. Apple makes acquihires for engineering talent (“individual contributors”) to fill gaps in its tech stack (Apple doesn’t target sales or marketing talent). Example M&A deals include tech for FingerID (AuthenTec), iPhone shortcuts (Workflow), Apple News+ (Texture), voice assistance (Siri), Apple Music (Beats).
Sector-specific buying sprees: When Apple wants expertise in a sector, it will buy up multiple firms. Take semiconductors: it bought PA Semi in 2008 ($278m), Intrinsity in 2010 ($121m), Passif Semiconductor in 2013 (undisclosed). Over the past decade, it acquired a lot of car-related talent (for its now defunct autonomous vehicle project) and a lot of VR/AR firms (for Apple Vision Pro and other eyewear projects).
Very secretive: Acquired companies are asked not to update their LinkedIn profiles. Some NDAs don’t even allow the employees to tell family and friends about a deal (the self-discipline required to not flex an Apple acquisition on your LinkedIn bio must be immense).
An instructive example of Apple’s M&A approach is its brief flirtation with Tesla.
Over the years, there have been various reports about Apple potentially acquiring the EV leader including during the Model 3’s “manufacturing hell” period in 2017-18. Tesla was worth $50-60B at the time and Apple had ~$100B under its mattress on hand. Aside from that fact that Elon almost certainly wouldn’t work for someone — and that Tim Cook probably wouldn’t offer his CEO seat — the deal didn’t make sense from Apple’s strategic approach.
According to leading Apple analyst Neil Cybart, there are three criteria that Apple does not look for in an acquisition:
Brand: Apple is already one of the world’s top brands (if not the top brand).
Revenue: Apple doesn’t need to add revenue through acquisitions (only through its own products).
User base: Apple already has 2B+ users, many of which are total suckers (me) that will buy almost anything it sells.
These attributes — brand, revenue, users — are the exact strong points that Tesla would have brought to the table. Of course, Tesla has a ton of technology and talent. So, Apple just poached a bunch of technical Tesla employees. In 2018 alone, Apple hired ~50 former Tesla workers including Doug Field, Tesla’s Senior Vice President of Engineering (as mentioned: Apple shut down its car project earlier this year after a decade and $10B+).
Another example which is kind of an exception that proves the M&A rule is when Apple invested $1B into Didi — China’s Uber competitor — in 2016. While not a full M&A move, that deal was pricey by Apple standards and seen by many as a political decision since the company has such a large consumer market in China and manufactures so many devices in the country.
So, what is Apple’s best M&A deal based on the “talent and tech” perspective?
Three that stand out in my mind (all happen to be pre-Cook):
NeXT Computer ($404m in 1997): This is the Big Daddy. The Big Enchilada. The Big Kahuna. Apple was hurting in the mid-1990s and this deal brought back Steve Jobs. His startup NeXT Computer had created a really expensive high-end workstation that Apple ditched but its operating system (NeXTSTEP) became the core for Apple’s future MacOS (and later operating systems including iOS). Google buying YouTube for $1.65B (2006) and Facebook buying Instagram for $1B (2012) are often touted as the greatest tech acquisitions ever since both those deals ended up creating ~$500B of value for the acquirer. After the acquisition of NeXT, Apple went from $3B to $300B from Jobs return to when he died in 2011 and Cook took over (another 10x since). Technically, it was an acquihire making it the most baller acquihire ever.
FingerWorks (Undisclosed in 2005): Founded in 1998, FingerWorks — honestly, great name — created gesture recognition and multi-touch technology for people with medical conditions such as carpal tunnel syndrome. The company’s main product was an easy-to-use keyboard and gesture pad. Apple initially licensed the tech for its Mac trackpad but then bought the company and brought the talent in house. The IP became the basis for a little known feature called iPhone’s touchscreen.
PA Semi ($278m in 2008): In the early 2000s, Apple engaged semiconductor design firm PA Semi for its CPU processing technology. But — as with FingerWorks — Apple ended up acquiring the company and its 150 engineers to create custom chips for future iPhones, Macs and iPads (and now Wearables). This acquisition led to Apple Silicon (e.g. “A” series for iPhones, “M” series for Macs), which is now a massive hardware moat for the business.
NeXT, FingerWorks, PA Semi
Moving forward, could Apple change its M&A approach?
It might have to since nothing will ever be as lucrative as the iPhone, which is the greatest consumer product ever but in a now totally mature category. Granted, a mature category that is printing ~$200B a year for Apple.
More broadly, Apple’s entire business churns out an annual operating profit of ~$100B on ~$400B of revenue. It spend ~$30B on R&D and doesn’t have huge CapEx requirements compared to its Big Tech competitors (which are spending tens of billions a year on data centres for AI and cloud). That’s why Apple is able to maintain a $50-100B buyback program (and will soon hit a total of $1 trillion in buybacks since Cook started the program in 2012).
If needed, it’ll always have the cash for a big move.
This isn’t to say that Apple hasn’t been able to Cook up new business lines internally (pun very much intended). Over the past decade, the $3.5T tech giant has turned Wearables into ~$40B a year vertical selling AirPods and Watches. Meanwhile, Apple’s services business has scaled to ~$100B a year.
But there have also been recent flops for the “next big thing”. The Apple car project didn’t work out. The Vision Pro is currently niche and the Apple Intelligence foray has been meh so far.
If the eventual augmented reality (AR) glasses aren’t a hit and the iPhone can’t crack generative AI, does Apple just make a splashy acquisition? Maybe an AI lab? A film studio like LionsGate? A meatier media play such as Warner Bros. Discovery? A robotics company for Apple’s move into the home? Electronic Arts to get into gaming? Dole to get into the fruit business (straight out of Forrest Gump)?
There are a lot of possibilities (although, antitrust may not agree).
One major acquisition that gets floated every few years is Apple buying Disney. CEO Bob Iger and Steve Jobs were pretty close and Iger even wrote in his biography that he thought the two companies would have merged if Jobs was still alive. Today, Apple could potentially use Disney’s assets in live sports and IP for AR/VR content (the House of Mouse also has a $1.5B investment in Fortnite game-maker Epic). But Apple has zero proficiency in running theme parks and there are way cheaper ways to acquire a content-making machine than dropping $200B (however, Disneyland’s $10 bottle of waters do fit the same high-margin profile that Apple hardware products enjoy).
These type of mega-deals feel very unlikely. Apple is always hyper-focused on a few product lines and can ride the iPhone-Wearables-Services trifecta for a long time until it cracks AR/VR or the wheels fall off. In the meanwhile, I’ll simp on more Apple products and make the dumbest memes humanly possible with the Pixelmator app.
PS. My Caffeinated Deep Dive podcast episode on the iPhone talks a lot about Steve Jobs comeback at Apple in the mid-1990s and how FingerWorks turned into the iPhone's multi-touch screen.
Chick-fil-A’s ~$22B Biz
In 2023, Chick-fil-A had sales of $22B — up 20x since 2000 — making it the 3rd largest restaurant chain in America on a sales basis after Starbucks ($36B) and McDonald’s ($26B). Of those three companies, Chick-fil-A easily has the best pun in its name and we can thank S. Truett Cathy, who invented the OG sandwich in 1946 (before making it the signature item for a restaurant by the same name in 1967):
“Chick” is to represent [the] juicy chicken, and “fil-A” as a play on the word “filet” – with a small twist. [Cathy] replaced “et” with “A” to represent the “Grade-A” quality of [the] chicken.
The chicken sandwich operation is pretty impressive when you look under the hood:
Nickname: First, I only recently found out that Chick-fil-A fans call the chain by its acronym “CFA”. This makes all the sense in the world but as a one-time holder of the Chartered Financial Analyst (CFA) destination, I feel that my financial test-taking accomplishments have been somewhat diminished. The CFA chicken sandwich is much more culturally relevant — and much much much more crispy and delicious — than the CFA financial designation.
Cash printer: CFA generates its revenue from only ~3k locations in the US, Canada and Puerto Rico. In comparison, Starbucks has ~38k global locations while McDonald’s is at ~40k. If we zero in on non-mall locations in the United States, CFA brings in $9.4m per store, more than double the same type of McDonald’s store at $4m.
Really good at drive-thru: A study by QSR found that customer satisfaction for fast food chain drive thru was highest for Chick-fil-A and Carls Jr. (Wendy’s was the worst). This is interesting because CFA actually has the longest average total wait time (8 minutes and 29 seconds). Here’s the kicker: the wait time is longer because CFA is so damn popular and has the most cars in lines (an average of 4.74 cars) but the actual time per car (1 minute and 47 seconds) was the shortest of all the chains. CFA has a very low error rate on orders — helped in part by a simplified menu — which means there are less delays (saving time even if there are more cars).
How is CFA so well run? One reason is that the chain is very discerning on the type of franchisee it will partner with. Zachary Crockett — my former colleague at The Hustle — has an incredible piece on CFA’s operator selection process:
According to Chick-fil-A, 60k people apply to be operators every year — and only ~80 are selected.
With a 0.13% acceptance rate, it’s harder to become a Chick-fil-A franchisee than it is to get into Stanford University (4.8%), get a job at Google (0.23%), or even become a special agent for the Secret Service (1%).
The operators that are accepted have interesting requirements that are different than other fast food franchise chains: 1) there is no minimum net worth (it ranges from Subway requiring $80k to Wendy’s requiring $5m); 2) there is a very low franchise fee of $10k (Subway charges $15k while Burger King and Jack ‘N The Box charge $50k); and 3) CFA has the lowest total investment to start.
While the initial outlay for a CFA franchisee isn’t huge, the chain charges the highest royalty fee (15% of sales; and 50% of net profits) relative to other fast food chains (most do a royalty at 4-6% of sales).
CFA’s selective process filters for top-tier operators and leads to happier employees. Here is how one CFA Manager describes it:
The company is very selective in its hiring process. This is the most important piece, because it’s really hard to turn a naturally negative person into a cheerful employee.
The company has a great training program. No new employee is “thrown into the deep end,” but instead are given one or two “Certified Trainers” who a) become their best friend at the store, and b) teach them every position methodically before they’re “off on their own.”
The company does have a bit of a cultish personality to it. Being cheerful with guests isn’t an accident, it’s an expectation, and that expectation can be communicated in both positive and negative ways depending on the specific store. Good stores build each other up, bad stores beat each other over the head with the “rules.”
The company tends to overstaff their stores. This is by design, and only in comparison to other quick service restaurants. When you might have four or five front of house employees during peak time at a Taco Bell, odds are the CFA down the road has between 12 and 16 front of house staff at that same moment. When you’re not dying from stress, it’s easier to be nice.
The food is pretty damn good (for fast food, at least), and it’s easier to be nice when you’ve just had a good (break) meal.
Impressively, the chain is raking in these revenue figures while closed on Sundays for religious reasons. You just know McKinsey consultants are banging on their doors with a simple pitch to “increase revenue by 1/7th” with one little trick.
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Why Duolingo Optimizes For Engagement (Over Everything Else)
Duolingo CEO Luis von Anh went on the Decoder podcast and shared a ton of insights on the language learning app (and its absolutely demented Owl mascot).
The most notable takeaway for me was why Duolingo leans so hard into gamification. Critics of Duolingo often say that gamified app-based learning is not the correct approach for language (the running joke is “I spent 20 hours on Duolingo Spanish and only know how to say ‘donde esta los bibliotecas?).
von Anh says he will always optimize for engagement over education because of how insanely competitive it is to keep people’s attention:
From the beginning, this is a central thesis that we believe here at Duolingo: the hardest thing about learning something by yourself is staying motivated. In fact, that is probably the reason for the vast majority of our success is that we realized that early on. From the beginning, we have tried to have a thing that is enjoyable to use and that keeps you coming back. We have probably spent more effort on that than anything else. […]
The reality is it’s not always true that engagement and learning outcomes are at odds. But when they are, we usually prefer going for engagement. I’ll give you an example. There are some things that are frustrating, and frustration makes you leave. We actually just smooth them. By that I mean, if I could force you to sit there, I may be able to teach the material to you in five minutes, but it’d be a very frustrating five minutes. Instead, what we do is teach it to you in two hours — just way slower, but the whole time, things are animating on the screen and you’re getting dopamine hits or whatever. Even though a really good teacher could have taught it to you in five minutes, watching you make mistakes, it would have been frustrating. We much prefer to keep you around.
Part of the reason is because we’re in an app setting as opposed to a school setting. In a school setting, the truth is the kids are held hostage there. They can’t leave. With an app setting, the tiniest frustration, people are like, “You know what? I’m going to go to TikTok now.” We just can’t lose those users. So we always opt for engagement, but that doesn’t mean we won’t teach the material to you. We’ll just take it a little slower.”
Honestly, it’s a very fair point about the smartphone as a distraction machine. When I used to read Kindle on my iPhone, I’d finish 1% of a book then flip over to X/Twitter as a “reward” and doom scroll for 5 minutes. It was pathetic. This is the reason I started using two iPhones: an older one with almost no apps (Kale Phone) and just the normal one packed with everything (Cocaine Phone).
The education vs. engagement tension is something that the team behind Blinkist — the app that turns books into 15-minute reads (a pretty ridiculous idea tbh) — brought up in a New Yorker profile:
Blinkist went live in 2013. Luck was on their side in the form of the iPhone, which was being updated—or, if you prefer, was cajoling the human brain ever deeper into a hostage situation—pretty much on an annual basis. “A lot of our ideas gravitated around knowledge management: how we can teach people something quickly,” [Blinkist co-founder Holger] Seim says. “We thought, What can we do with that new device? We naturally came to the idea: Wouldn’t it be good to have something that helps you learn on a smartphone, and spend those downtimes more meaningfully than playing Angry Birds?”
Duolingo and Blinkist obviously aren’t the most optimal way to learn. But in the modern smartphone attention economy, you have to fight fire with fire. It’s a bit depressing but that’s the nature of the beast. And both apps are definitely superior to mindlessly scrolling TikTok or playing Angry Birds.
Anyway, here are some other Duolingo insights from von Anh:
Learners prefer animated characters to humans: “It’s been very much on purpose for us to not put humans in the app, as in human teachers. There’s nothing wrong with human teachers. It’s just the case that, from the beginning, we’ve been a technology company, and we’ve wanted to make it so that technology teaches you. There are a couple of reasons for that. One is that it’s a lot cheaper to teach you with technology than with a human teacher. The other thing is, somewhere between 80 and 90 percent of language learners don’t want to talk to another human. They may tell you they do, but they don’t. It’s because when you’re learning a language, you’re pretty shy about it, and only the extreme extroverts are okay talking to a stranger on video in a language that they’re not very good at. The majority of people won’t do it.”
Duolingo teams are built around metrics (not features): “Our teams don’t own features. Our teams own metrics. So we have a team for subscription revenue. We have a team for daily active users. And they can touch whatever they want in the app. All they have to do is continually increase the metrics. There are positives to this, which are very aligned to metrics. There are negatives in that no team owns certain features. When something breaks, there are a lot of people being like, ‘It’s not my feature. I don’t know.’…There are positives and negatives, but all in all, this has actually worked out really well for us…and then the other thing that is really important is we have guardrail metrics. So here’s how that works: If you are on the team that’s trying to improve subscription revenue, your goal is to improve that metric. But we tell you, “You can’t mess up any of the other metrics.”
As for the Owl mascot, von Anh says a small team of really online (and funny) people run the social. There are some weeks when the Duolingo TikTok account — with 13m followers — has the most-viewed videos on the entire app. On rare occasions, von Anh has had to spike a idea because it went too far (including a skit that involved the Owl taking a user hostage until they learned a language).
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Vitalik Buterin on Prediction Markets
Last week, we talked about how prediction betting markets (Polymarket, Kalshi) did better than the polling industry to forecast the US Presidential election results.
Ethereum co-founder Vitalik Buterin has a good blog on the power of these platforms and describes them as “a betting site for the participants, a news site for everyone else” and how observers “can be more informed by reading the news and the charts, than by reading either one alone”.
The eye-opening example for him was the recent Venezuelan “election”. Most people expected the country’s strongman ruler Nicolas Maduro to easily sweep to victory in a sham process. But Polymarket showed a 23% chance that an opposition leader would win. Buterin saw this and closely watch events in the country:
Ultimately, Maduro did stay in power. However, the markets clued me in to the fact that this time, the attempt to unseat Maduro was serious. There were huge protests, and the opposition played a surprisingly well-executed strategy to prove to the world just how fraudulent the elections were.
Buterin calls this field “info finance” and believes that AI could play a huge part in the next leg for the industry. How? Well, the value of predictions is based on how many people are willing to bet on a topic. There are obviously interested parties for the US Election and sporting events.
But what about micro-events that concern only a few people. Like, “will Trung go to his quarterly teeth-cleaning or push it aside out of pure laziness”. The current volume on such a bet might be minuscule ($10). However, AI agents could be properly trained to give forecasts and bet on thousands of such questions and therefore create markets where they would not otherwise exist (in the case of teeth cleaning, my wife really wants get extra information for that forecast).
“[Info finance] is relatively difficult to make work when it must depend on humans to participate on each question,” writes Buterin. “AIs greatly improve this situation, enabling effective markets even on small-scale questions. Many markets will likely have a combination of AI and human participants, especially as volume on specific questions suddenly switches from small to large.”
Sidenote: Polymarket’s CEO had his house raided by the FBI and they took his electronics (phone, laptop) after the US election. Some corners of the internet thought it was retribution for the platform forecasting a Trump victory but the more likely reason is that the crypto-based betting market wasn’t supposed to serve US customers and it might have (it’s not hard for customers to whip up VPNs). Either way, here was the CEO’s first tweet after the news dropped:
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Some other baller links:
F1 driver Valterri Bottas…casually did an Iron Man race at his house on an off-day, with the training session lasting 11 hours and he burnt 7,000 calories (X/JoePompliano)
The new Mission Impossible trailer dropped…and Tom Cruise’s latest insane stunt is hanging off of a WWII-era airplane while in mid-air. (X/TrungTPhan)
Donkey Kong Country…will open inside the Super Nintendo Land theme park at Universal Studios in Osaka on December 11th. For decades, people have wondered why Nintendo didn’t milk its gaming IP as hard as Disney does for its IP. Well, Nintendo and Universal are revving up their partnership. The animated film Super Mario Bros. did $1.4B at the box office last year and this video of Mario creator Shigeru Miyamoto touring Donkey Kong Country — with massive piles of bananas and oversized Donkey Kong — is pretty damn enticing. (YouTube)
The perfect NFL touchdown celebration…is when a Minnesota Vikings receiver does the exact RayGun breakdancing performance from the Olympics.(X/LydiaKauppi)
xAI will be valued at $50B...after raising $6B. The Elon-founded AI lab is now the 6th most valuable startup in the world after ByteDance ($225B), SpaceX ($200B; but soon to be $250B), OpenAI ($157B), Stripe ($70B) and Shein ($66B). Elon founded and funded #2, #3 and #6 on this list. He also cut Stripe a seed check back in the day but think he's sold that stake. If you're wondering how xAI could be worth $50B, it's because investors are piling money into the handful of AI labs that might win the AGI race. xAI has training data and distribution via X/Twitter. But perhaps more importantly, Elon and team can put up an AI data centre like no one else. Earlier this year, xAI constructed a supercomputer with 100,000 Nvidia H100s in Memphis in only 122 days. It typically 3 years. Nvidia CEO Jensen Huang said Elon is singular in the ability to marshal resources and capital to complete such a build. xAI competitors were so shocked by the speed of the Memphis supercluster buildout that they hired propeller planes to study the the structure's design, cooling and heating systems. We are officially in the "spy plane surveillance" portion of the AI hype cycle. (The Information)
…and here them fire posts (including the fact that Pope Francis has been using the #Saints hashtag without knowing that it belongs to the New Orleans Saints and now people are in the replies asking him to bless their football team or fix the cap tables):
Finally, here is a hysterical sequence of posts related to Bitcoin’s +20+% surge to over $90k since the US election (TLDR: Trump administration is seen as more pro-crypto and less of a regulatory overhang on crypto assets).
Let me set it up by saying I was a huge Chicago Bulls fan in the 1990s. Really got into the NBA during the Bulls second 3-peat from 1996-98. Jordan. Pippen. Rodman. Kukoc. Kerr. Harper. Jackson. This coincided with the fact that Vancouver — where I grew up — got an expansion basketball team (Grizzlies) in 1995. The Grizzlies have since moved to Memphis but my memory of the period is very salient.
Anyway, Scottie Pippen’s X account has been promoting basketball-related crypto projects over the past year. Someone is clearly running his account and at the beginning of September, he posted “[Bitcoin founder] Satoshi Nakamoto visited me in my dream last night and predicted that #Bitcoin would be at $84,650 on November 5, 2024. Not Financial Advice.”
An objectively absurd tweet. Imagine trying to explain that post to someone in the 1990s. Hell, imagine trying to explain that to someone in 2023. Wild. People started trolling him but — lo-and-behold — Bitcoin ended up ripping past $85k on November 11. My buddy Ramp Capital was absolutely shook by these sequence of events (see two posts below).
In the days that followed, the person running Pippen’s account posted these absolute bangers as BTC hit prices that coincided with years the Bulls won championships. Again, his posts are not financial advice. This newsletter is not financial advice. Hilarious either way.
Ugh…last second meme edition. 58-year old Mike Tyson sadly lost a decision vs. 27-year old Jake Paul. Mike looks incredibly for late-50s thought and this post goes hard:
