Buying Stocks with Conviction (A Story of Apple and Snapchat)
While I believe that picking individual stocks can be perceived as gambling, I still do it, because it’s a game where with some proper research and luck, you can beat out the consensus estimate for particular companies. I am still completely of the belief that for most investors looking to dabble in stocks, the best way is still to buy an index of the broader market (ex. SPY). Here, I wish to expand on the sentiment that you should “Never invest in a business you cannot understand” – Warren Buffett. The corollary of this is “Buy what you understand”, which includes such tactics as investing in products or services that you use the most (eg. Apple, Microsoft, etc.). Buffett’s rule seems very simple and unimaginative at first, but I believe that there is more to it than meets the eye and I will show you one way I turn this motto into an investing strategy.
The Case of Apple
When we begin to think about the companies we know, Apple quickly comes to mind. It’s a simple and popular example of a high-volume, hotly debated stock. Generally speaking, we know the stock has been a top performer since the first iPhone was released, and even now the greatest debates are whether the next iPhone will sell more than is “priced in” or expected by analysts. If Apple sells more iPhones than what is priced in or expected, the stock rises, if not, the stock falls. So how do we as investors apply “buy what we understand” to this situation? For one thing, your existing usage of their products is a huge signal of understanding and serves as the basis for forming opinions about how impressive that next iPhone will be. For example, as a tech junkie and avid user of Apple products (iPhones, Macbooks, iPads, iOS, etc.), I can compare what my understanding of the demand should look like for the new iPhone/OS versus what analysts say or have priced in. The critical piece here is to have a general understanding of what it is that analysts and big time investors are pricing in. This seemingly simplistic method should not be confused with the obvious knowledge that new iPhone releases in Q3 refuel sales for Q4, and should especially not be confused with concluding that is why the stock is always “priced in”. Put another way, say a friend told you not to buy Apple because these new iPhone 8 and iPhone X sales are all “priced in”. New iOS 11, priced in. Everything, priced in. The sentiment and product understanding will address: how much of it is actually “priced in”?
Hypothetically speaking, let’s say the average Q3 product refresh has an average value-add of ‘V’, and so it is V that gets priced in by the average consensus for each year’s product refresh. But with your intimate understanding of their product offerings due to your tech junkie status, you believe that it is actually ‘V+X’ where X is relatively large, which could potentially give you an advantage. How big that X is, is a combination of two broadly defined factors: 1) Intimate knowledge of Apple products/services, and 2) your research of the analysts that are actually projecting the product refresh value for this year. This means watching interviews, reading articles, research reports and the like and seeing just how intimate their knowledge is of those products and services. You are effectively comparing your knowledge to theirs and testing the gap. This too seems fairly straight forward, but realize that your objective here isn’t to accurately forecast sales of the refresh, it is simply to judge the disparity between both of your sentiments. If there is a large disparity, then that means you believe the new refresh is value-add V+X instead of just V. Maybe the average analyst consensus is V as they think Face ID is the normal incremental value-add year-over-year, but you think that this feature is a positive game changer and will sell many more phones, thereby resulting in V+X from your perspective. You both answer the same questions but your job after answering it is to see how large that discrepancy is versus the consensus opinion on those products/features. This requires you to look beyond blind investments where everyone expects the same thing, V, but rather set a test for yourself to invest in areas where you believe you have that insight to find a V+X, or invest in V’s you like but heavy up in V+X situations. If you are pretty much always aligned with how analysts are forecasting demand and analyzing hype (in which case you concede you have no extra product expertise), then you should keep looking for the V+X opportunity.
The Case of Snapchat
Millennials like to say that their parents don’t understand certain technologies and thus have a hard time investing or making valid criticisms - this applies to investing as well. In the above I gave you the most common example I could in the form of Apple, to explain a concept. But now let us apply it to a more polarized and recent case: Snapchat. I believe Snapchat represents a situation where the so-called professionals aren’t truly experts in the product; they don’t use it as avidly as they could, and that someone like myself could have more expertise in knowing whether it’s a V+X situation. The only caveat here is that I will demonstrate why Snapchat is a bad investment (I first initiated a short position at ~$21.75 per share), thus representing a V-X.
I meet the first condition of my methodology from being an avid user of Snapchat, using it multiple times a day for the last 4 years and having “Snap Score” of 75K+ points! Of course this pales in comparison to my sister who has +197K points as of this writing but my hunch is the average analyst has barely any clue just how much usage that is. The Snap Score is the number of times you send and receive a Snapchat, so 75K points over the course of 4 years is about sending and receiving 51 Snaps per day! I am also an avid user of Facebook, Instagram and Instagram Stories, Yelp, largely posting food pictures on all of these mentioned accounts. I use these services to a large degree and have very strong opinions about them. For the motto “invest in what you understand”, this is one area where I easily ticked off in my mental checkbox. Again, the mentioned exercise requires one to contrast their own knowledge against that of analysts who think about the stock. From the weeks leading up to the IPO I indulged in countless articles and interviews about Snap, laughing at the analyst discussions of Instagram not being able to copy and grow, how Snap could rebrand themselves as a “camera company”, and how Spectacles would be their great transition into hardware. Despite how they pitched themselves, the active user count and teen population were strong, so come the day of IPO, Snap was off to the races reaching $22+ per share. This valued the company at $33 billion – larger than Chipotle, Best Buy, and Trip Advisor combined.
Upon watching more interviews defending the camera company and little in the way of ad revenue, and seeing insane size comparison charts like the one above, I saw a very large discrepancy in our understanding of the product. Investors saw a V+X, I saw a V-X: a very big –X. My firm belief of what made this product stick was face and artsy geo filters. The branded filters were bearable so long as they added a coolness factor (e.g. Burger King had its king crown you could wear). But the second it felt like an actual advertisement telling me to do something like refinance a mortgage, that filter would fail miserably and never be shared. Snapchats are sent to substitute for boring text messages. I wouldn’t want to send an ad with each text message I send to my friends, and by the same token, ads here fail too.
To add credence to my conviction, I work directly in the field of digital ad buying/targeting and the entire programmatic ad buying industry was born only in the last decade. Given my avid Snapchat use and marketing background, this is where I would draw the divide between myself and the professional research analysts. If you work in this space you know that certain Cost Per’s (conversion and landing page) are incredibly popular marketing campaigns. Without getting into the weeds on other advertiser shortcomings on Snapchat, simply imagining the difficulty of creating great filters that people would use and share and also have end users click into seems like an impossible task. The key is that they have to want to share the resulting image (filtered or not), and if it’s not cool, then scale is drastically reduced. With that in mind, here are 4 big problems with current advertising on Snapchat:
For my specific use case, any filter setup with live links would destroy Snapchat’s primary use case as a platform to send quick substitute text messages.
The advice from this example is that for the average investor, you can have the edge. You should be passionate about the company and its products, and know it inside out to identify that V+X. You don’t need to be in the industry to make a sound investment, but my example highlights a scenario in which I actualized the +X factor. My next investment involves Fitbit, based on my belief that I am acutely attentive to the smart watch market and understand the full range of use-cases from a fitness and technology perspective, at a level beyond the consensus. It all begins with your own belief, because that is how you “buy what you understand”.
The Case of Apple
When we begin to think about the companies we know, Apple quickly comes to mind. It’s a simple and popular example of a high-volume, hotly debated stock. Generally speaking, we know the stock has been a top performer since the first iPhone was released, and even now the greatest debates are whether the next iPhone will sell more than is “priced in” or expected by analysts. If Apple sells more iPhones than what is priced in or expected, the stock rises, if not, the stock falls. So how do we as investors apply “buy what we understand” to this situation? For one thing, your existing usage of their products is a huge signal of understanding and serves as the basis for forming opinions about how impressive that next iPhone will be. For example, as a tech junkie and avid user of Apple products (iPhones, Macbooks, iPads, iOS, etc.), I can compare what my understanding of the demand should look like for the new iPhone/OS versus what analysts say or have priced in. The critical piece here is to have a general understanding of what it is that analysts and big time investors are pricing in. This seemingly simplistic method should not be confused with the obvious knowledge that new iPhone releases in Q3 refuel sales for Q4, and should especially not be confused with concluding that is why the stock is always “priced in”. Put another way, say a friend told you not to buy Apple because these new iPhone 8 and iPhone X sales are all “priced in”. New iOS 11, priced in. Everything, priced in. The sentiment and product understanding will address: how much of it is actually “priced in”?
Hypothetically speaking, let’s say the average Q3 product refresh has an average value-add of ‘V’, and so it is V that gets priced in by the average consensus for each year’s product refresh. But with your intimate understanding of their product offerings due to your tech junkie status, you believe that it is actually ‘V+X’ where X is relatively large, which could potentially give you an advantage. How big that X is, is a combination of two broadly defined factors: 1) Intimate knowledge of Apple products/services, and 2) your research of the analysts that are actually projecting the product refresh value for this year. This means watching interviews, reading articles, research reports and the like and seeing just how intimate their knowledge is of those products and services. You are effectively comparing your knowledge to theirs and testing the gap. This too seems fairly straight forward, but realize that your objective here isn’t to accurately forecast sales of the refresh, it is simply to judge the disparity between both of your sentiments. If there is a large disparity, then that means you believe the new refresh is value-add V+X instead of just V. Maybe the average analyst consensus is V as they think Face ID is the normal incremental value-add year-over-year, but you think that this feature is a positive game changer and will sell many more phones, thereby resulting in V+X from your perspective. You both answer the same questions but your job after answering it is to see how large that discrepancy is versus the consensus opinion on those products/features. This requires you to look beyond blind investments where everyone expects the same thing, V, but rather set a test for yourself to invest in areas where you believe you have that insight to find a V+X, or invest in V’s you like but heavy up in V+X situations. If you are pretty much always aligned with how analysts are forecasting demand and analyzing hype (in which case you concede you have no extra product expertise), then you should keep looking for the V+X opportunity.
The Case of Snapchat
Millennials like to say that their parents don’t understand certain technologies and thus have a hard time investing or making valid criticisms - this applies to investing as well. In the above I gave you the most common example I could in the form of Apple, to explain a concept. But now let us apply it to a more polarized and recent case: Snapchat. I believe Snapchat represents a situation where the so-called professionals aren’t truly experts in the product; they don’t use it as avidly as they could, and that someone like myself could have more expertise in knowing whether it’s a V+X situation. The only caveat here is that I will demonstrate why Snapchat is a bad investment (I first initiated a short position at ~$21.75 per share), thus representing a V-X.
I meet the first condition of my methodology from being an avid user of Snapchat, using it multiple times a day for the last 4 years and having “Snap Score” of 75K+ points! Of course this pales in comparison to my sister who has +197K points as of this writing but my hunch is the average analyst has barely any clue just how much usage that is. The Snap Score is the number of times you send and receive a Snapchat, so 75K points over the course of 4 years is about sending and receiving 51 Snaps per day! I am also an avid user of Facebook, Instagram and Instagram Stories, Yelp, largely posting food pictures on all of these mentioned accounts. I use these services to a large degree and have very strong opinions about them. For the motto “invest in what you understand”, this is one area where I easily ticked off in my mental checkbox. Again, the mentioned exercise requires one to contrast their own knowledge against that of analysts who think about the stock. From the weeks leading up to the IPO I indulged in countless articles and interviews about Snap, laughing at the analyst discussions of Instagram not being able to copy and grow, how Snap could rebrand themselves as a “camera company”, and how Spectacles would be their great transition into hardware. Despite how they pitched themselves, the active user count and teen population were strong, so come the day of IPO, Snap was off to the races reaching $22+ per share. This valued the company at $33 billion – larger than Chipotle, Best Buy, and Trip Advisor combined.
Upon watching more interviews defending the camera company and little in the way of ad revenue, and seeing insane size comparison charts like the one above, I saw a very large discrepancy in our understanding of the product. Investors saw a V+X, I saw a V-X: a very big –X. My firm belief of what made this product stick was face and artsy geo filters. The branded filters were bearable so long as they added a coolness factor (e.g. Burger King had its king crown you could wear). But the second it felt like an actual advertisement telling me to do something like refinance a mortgage, that filter would fail miserably and never be shared. Snapchats are sent to substitute for boring text messages. I wouldn’t want to send an ad with each text message I send to my friends, and by the same token, ads here fail too.
To add credence to my conviction, I work directly in the field of digital ad buying/targeting and the entire programmatic ad buying industry was born only in the last decade. Given my avid Snapchat use and marketing background, this is where I would draw the divide between myself and the professional research analysts. If you work in this space you know that certain Cost Per’s (conversion and landing page) are incredibly popular marketing campaigns. Without getting into the weeds on other advertiser shortcomings on Snapchat, simply imagining the difficulty of creating great filters that people would use and share and also have end users click into seems like an impossible task. The key is that they have to want to share the resulting image (filtered or not), and if it’s not cool, then scale is drastically reduced. With that in mind, here are 4 big problems with current advertising on Snapchat:
- The filters created for a brand are optimized for awareness campaigns, not conversion campaigns – advertisers will have issues with this.
- The vast majority of filters used and shared are unbranded face filters because they do not have distracting text. These filters are just there to make you pretty/cool (think dogface or rainbow vomit), which means no money for advertisers.
- Most things that advertisers sell are objectively not “cool”, and to be limited to advertising dollars for things that are cool and legible in a filtered format to then be shared is asking for very narrow scale.
- Even if we had a magic formula for getting people to want to use branded filters and their friends to click into them, the way to click into the next Snapchat is to click the screen. If parts of the screen suddenly turn into landing page URLs then that would irritate the user (i.e. accidentally taking you to a different page).
For my specific use case, any filter setup with live links would destroy Snapchat’s primary use case as a platform to send quick substitute text messages.
The advice from this example is that for the average investor, you can have the edge. You should be passionate about the company and its products, and know it inside out to identify that V+X. You don’t need to be in the industry to make a sound investment, but my example highlights a scenario in which I actualized the +X factor. My next investment involves Fitbit, based on my belief that I am acutely attentive to the smart watch market and understand the full range of use-cases from a fitness and technology perspective, at a level beyond the consensus. It all begins with your own belief, because that is how you “buy what you understand”.
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