Amidst Tesla's (TSLA) meteoric rise, a sizable contingent of investors have become skeptical of its ability to live up to its market capitalization. They point to the company's "ludicrous" valuation, increasing competition from established automakers, and concerns around cash management. If Tesla were solely an automaker or even an automaker with green energy production capabilities, these bearish investors' claims may have some validity. But it is not. In fact, one of Tesla's most significant assets - its vehicle data - is overlooked by nearly everyone, despite its incredibly immense potential.
Tesla started collecting driving data, including data on location, speed and acceleration measures, steering, the surrounding driving environment (from cameras and ultrasonic sensors), and personal settings, in 2018. Since then, the company has collected over 3 billion miles of real-world driving data. To put the incredible scale of this in perspective, one would need to circle the Earth 378,891 times to travel 3 billion miles. Indeed, the scale of Tesla’s data-gathering operation is unmatched. Its closest competitor, Waymo, has only amassed 20 million miles, and other self-driving car companies are struggling to crack the 1 billion mark. George Paolini, a former EVP at SAP, has called it “the most effective crowd-sourced AI/ML training initiative around today.” Despite its commanding position, Tesla has yet to see significant financial benefits from this plethora of data.
This is about to change. In the short term, this data could create two sizable new revenue streams for Tesla: insurance and advertising.
Insurers need both high-quality data and intelligent actuarial processes to understand an asset's risk and properly price premiums. While actuarial science has significantly improved in recent decades, insurers' driving data has not. Currently, auto insurers can only determine one's driving record reactively (after you get in a crash, your premiums go up). With Tesla's driving data, insurers will be able to significantly improve their premium pricing by determining prices proactively based on one's driving habits and driving locations. For example, an insurer could determine that a Tesla driver frequently decelerates quicker than the average driver. Additionally, at the end of these fast decelerations, the car's proximity sensors often detect nearby objects. This could indicate that the Tesla driver often gets in near-crash scenarios, and the insurer can increase their premiums accordingly. Conversely, if a Tesla driver consistently drives under the speed and rarely gets in near-crash scenarios, their premiums could be lowered accordingly. Drivers' location data could also help inform premium pricing decisions. For example, if a Tesla driver frequently parks their vehicle in high crime areas or drives in dangerous weather conditions, their premiums could go up.
For auto insurers facing a challenging operating landscape in the next several years due to forecasted decreases in investment income and policy renewals, improving premium revenue is necessary to protect profit margins. IBISWorld, a market research firm, estimates that the industry's average profit margins will fall at 0.5% in the next five years without significant operational changes. Tesla can capitalize on this downstream trend by signing long-term data sharing and processing agreements with large insurers such as State Farm, Progressive and Allstate. These agreements would obligate Tesla to provide processed data about its drivers’ driving habits and driving locations in exchange for a fixed fee per car. Alternatively, the company could expand its existing Tesla Insurance offering to significantly improve the customer lifetime value of their drivers through ecosystem effects. Either way, Tesla’s car data will allow it to be a significant player in the $308.8 billion auto insurance market once the company settles on a way to monetize it.
Tesla's car data can also be used to inform hyper-targeted advertising that can be displayed to a captive audience through the vehicle's operating interface. Tesla can already record everything a consumer says, including in-car conversations, texts and calls. With some additional processing, this data could be easily structured and categorized to understand drivers' travel and consumption habits. Tesla would be able to target customers with highly personalized advertising and give them subtle location and time-based behavioural cues that traditional advertising channels could not. For example, if someone receives a text on their way home from work to get some milk, Tesla could recommend nearby places for the driver to do so and charge businesses a fee to be included on their list. Compounded with the advantage that Tesla has of a captive audience (similar to car radio pre-music streaming), we believe that the company has immense potential to monetize its car data through context-dependent advertisements.
If the car data market is so lucrative, what stops other car makers from entering it? One significant barrier to entry is customer trust. Currently, less than 50% of American drivers would be willing to share their car data if they knew other companies were using it. This figure may drop even further as data privacy becomes an increasingly contentious issue in the coming years.
Thus, it's unsurprising that competitors' forays into car data have not been well-received. In 2018, the Detroit Free Press reported that General Motors (GM) had gathered phone calls, text messages, and radio listening history data from over 90,000 American drivers to sell to radio advertisers. Auto industry pundits churned out negative story after negative story, with headlines such as "Every minute for three months, GM secretly gathered data on 90,000 drivers' radio-listening habits and locations" and "Take a Long Look in the Mirror" (asking both General Motors and GM drivers to reflect on the morality of their actions.)
While customer trust represents a barrier to entry for competitors, we believe that one of Tesla’s most substantial competitive advantages is an uncompromisingly loyal and enthusiastic fan base. Overall customer satisfaction ratings are over 90%, and a staggering 80% of first-time Tesla buyers end up purchasing another Tesla vehicle. The company also spends $0 on advertising. Yet, we hear about the company and Elon Musk on pretty much every single media outlet all the time. Stories are being brought about by many different sources, such as traditional news outlets, Elon himself, Tesla consumers, YouTubers, and celebrities. No other car manufacturer in the world receives the quality and quantity of attention that Tesla does. If they did, they wouldn’t need to spend billions of dollars on TV advertisements. The result is that consumers will be loyal to Elon and Tesla no matter the competition or alternatives, and we believe that this obsession is immeasurable through brand equity. Love for Tesla is being fueled through increasing accessibility to digital platforms for both creators and viewers. Tesla customers are not only drivers but also brand enthusiasts, in a way unmatched by any other carmaker’s customers. Thus, we expect that if the company were to implement our proposed data monetization strategies in a transparent, straightforward manner that protected consumer privacy and consumer choice, customers would react much more favourably than they did to competitors’ efforts.
McKinsey, a preeminent global consultancy, believes that recurring revenue from car data applications will reach between $450 and $750 billion by 2030. Given that Tesla is the undisputed leader in this space and enjoys notable irreplicable competitive advantages, we believe that the company stands to capture a sizable portion of business from this rapidly growing market. Tesla’s immense success in the car data space will undoubtedly benefit its shareholders; data-based companies often enjoy high margins and recurring revenues. But given Tesla’s ostensibly stratospheric valuation, is it still worth buying at current prices?
We believe so. Our price target for TSLA is between $496.13 and $830.58, with a base case implied share price of $622.88. This is derived from two analyses: a 10-year discounted cash flow analysis and comparable companies’ analysis based on enterprise value-to-EBITDA multiples.
Our valuation assumes conservative growth in Tesla’s core businesses and no success in its moonshot projects (robo-taxis, Tesla freight, etc.). In our models, Tesla only sells ~3.3 million cars in 2030, much less than many analysts are expecting. Despite its significant investments in research and development, its Energy segment grows only at the industry average growth rate, then begins to drop off even further by 2025. However, Tesla becomes the undisputed market leader in car data in the next five years, capturing a 1/3rd market share due to its proactive moves. In the spirit of conservatism, we estimated that market share slowly trails off for the next five years to 25% due to the entrance of hypothetical strong, well-capitalized competitors (although none yet exist).
With these assumptions, Tesla will generate $281 billion in revenues, $61 billion in EBITDA, and $37 billion in free cash flow by 2030. Assuming an 8.1% cost of capital and a 28% cash tax rate, our base case discounted cash flow estimates that the company should be worth $496 if the market correctly priced in the value of car data. If revenue growth is 1.5% and margins are 2.0% higher than expected, this figure jumps up to $629. Even if margins are 2.0% lower than expected, shareholders can still expect prices to rise to $435.
To sanity-check our discounted cash flow valuation figures, we conducted a comparable companies analysis based on today’s enterprise value multiples for more established car companies and Tesla’s 2029 EBITDA. We found that established car companies traded at around 16x EBITDA, which, when applied to Tesla’s forecasted EBITDA, actually generates a significantly higher valuation of $830 per share.
It’s clear that Tesla is an attractive buy at current prices. While skeptics think valuations are lofty, anyone who accurately understands the potential of Tesla to not only be a car company but one of the world’s largest data providers will think differently.
Tesla’s most important long-term project is the robo-taxi network; the theoretical ability for autonomous cars to pick up and drop off passengers on a truly scaled level, in which the entire network is optimized by millions of data points can revolutionize the mobility space forever. Tesla fans and critics alike have been waiting for advancement in autonomous capabilities for a long time. We are not ignoring the fact that level 5 automation is extremely hard to achieve and that this robo-taxi network may take decades to establish.
Yet, we believe that Tesla will be the first company to gain significant market share in the robo-taxi market and we are more interested in the long-term future cash flows rather than the timing of network introduction, even though back in April, Elon promised a robo-taxi network by the end of 2020.
Ubers (UBER) are usually taken in population-dense areas where network externality effects are extrapolated, as car-sharing works best when there many passengers and many drivers. However, once robo-taxi networks are established properly, "technically addressable miles" expands rapidly, as passengers will use the network for trips outside of the city. In the robo-taxi 3.0 development phase in the picture above, the Tesla robo-taxi network can leverage its already existing data assets in order to better understand how much consumers would be willing to pay to hail a ride to unusual destinations. By doing so, Tesla can lower the price enough for a consumer to be willing to take a long trip in robo-taxi, yet still earn a profit on each ride because it understands the opportunity costs of not having certain vehicles in the network at specific times, and a driverless fleet dramatically reduces variable costs. Therefore, trips to a cabin destination will theoretically be much cheaper during off-peak network times for good reason (i.e., times outside of 7-9 AM and 5-7 PM on weekdays). Moreover, since a large part of the Tesla robo-taxi network would potentially be owned by users who actually purchase a car, the incentive for buying any Tesla car will change; some may view the purchase as an investment.
A robo-taxi network is not just for passengers, as the potential for goods to be transferred is just as feasible. Tesla can potentially expand on this idea once the company establishes its autonomous trucking fleet. Transferred goods can include anything from international imports and exports of fruits and vegetables to cross-city small package deliveries. In fact, Uber has recently introduced a feature called Uber Connect for package transfers by drivers.
To conclude our report, we want to remind our readers that the share price appreciation like we outlined above is far from unprecedented. In fact, as recently as 2016, when skeptics were ripping Amazon (AMZN) stock apart after its historic bull run. Short interest was $5.3 billion at the time.
(Source: Amazon Stock Chart 2004-2016, MacroTrends)
Below is Tesla’s recent chart. Its current short interest was around $20 billion, which is a record for any stock. Although Tesla’s fundamentals are far off from reality, just like Amazon’s numbers many years ago, growth potential cannot be ignored in brand new markets where technology is a competitive advantage. In 2013, Amazon’s P/E ratio hovered around 1,000.
Many investors focused on Amazon’s biggest revenue stream at the time, which was the retail sector, and stated how dominance could not be sustained. Many also said that it was bound to lose market share, and other players would eventually find innovative solutions in the retail sector. The acquisition of Whole Foods proved to be extremely beneficial, as the physical locations are used partly to fulfill eCommerce deliveries.
Back in 2016, Amazon already started dabbling in the cloud computing market, and the company has grown that business line exponentially from 2016 until now. We believe that Amazon has long used its retail business as a cost leader mainly to collect data, and the company’s goal is to sustain net-zero figures. By building this e-commerce system, Amazon not only introduces customers to their other services in the B2C world, but its overall brand equity can be leveraged to provide B2B solutions. Today, the majority of Amazon’s income comes from its AWS services.
Much like Amazon in 2016, Tesla is beginning to dominate the total market capitalization of automotive producers, despite actually producing a nominal number of cars compared to all other car producers. In other words, the price/car for Tesla is quite insane.
However, Tesla has the potential to follow a similar path to Amazon. Tesla’s B2C electric vehicle revenue stream will most likely not be as profitable in the long run as more competition enters and rivals cut prices to gain market share. Yet, we believe that as long as the company doesn’t lose money from selling electric cars to consumers in the long run, it can leverage this car and data network to help build a stable revenue stream that produces high margins that will translate to significant share price appreciation, whether or not any of its moonshot projects succeed.
This article was written by
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Additional disclosure: Any information found in all our articles is not considered investment advice. Investors should consult with a registered financial advisor and perform their own research before making an investment decision.