To get a sense of how those numbers are assessed, I decided to focus on publicly traded companies in the tech sector. I then narrowed my lens down to companies that were deriving the majority of their revenue from selling large numbers of eyeballs to advertisers. This created a basket of 4 stocks that were:
- publicly traded
- receiving the majority of their revenue from online advertising
- trying to leverage the social network effect of large audiences
The final four companies were: Facebook, LinkedIn, Yahoo, and Google.
Because we are dealing with publicly traded companies, we have a large offering when it comes to numbers that we could use. In order to get some sense of normalization and comparable data, I decided to focus on the last quarterly financial report for each company, which allows us to roughly normalize data across 3 values: number of users the company had at the time of the report, revenue the company had, and its market capitalization on that day.
For the number of users, if it was not available in the annual report itself, I looked at reports on that number around the time the annual report for made. Because each company treat reporting of users differently, I went with the largest number they reported. For example, in the case of Google, the company and the media reported numbers of 450 million gmail users, 400 million Google+ users, 900 million Android users, and 1.3 billion Google search users. As a result, I took the 1.3 billion value as it is the largest of the set, possibly encompassing substantial overlaps with all the other numbers.
Revenues were announced by press release so I’ve taken those numbers straight from the reports the companies made. When it comes to those, I focused on the revenue directly attributable to the internet. This was only an issue with Google, where I removed the $998 million in revenue from their Motorola unit, because it largely comes from handset sales instead of the internet.
For market capitalization, I’ve taken the data from Google Finance on the most recent market date (yesterday). This means that those numbers are not fully aligned with the actuals on total number of users but should be directionally correct from an alignment standpoint.
Based on the values I gathered, I decided to estimate the value of an individual user by taking the market cap and dividing it by the number of users. I also decided to calculate the average revenue per user (ie. ARPU) by taking the revenue number and dividing it by the number of users. This gave us two indicators that can be useful in that it provides both the longer term expected value of a user as well as the current revenue per users, which is a more conservative measure.
All data included here was compiled from public sources, I did not use any internal information for any of those companies so you’re free to go and Google for similar data.
On to the data
With all the disclaimers above, it’s now time to take a look at the data.
|Market cap (in billions)||$100.56||$31.31||$27.67||$282.20|
|Number of users (in millions)||1,110||225||627||1,300|
|Revenue (in billions)||$1.813||$0.366||$1.135||$13.110|
|Per user valuation||$90.59||$131.55||$44.13||$217.08|
|Average Revenue per User (ARPU)||$1.63||$1.53||$1.81||$10.09|
Looking at this data, the first thing that one notices is that, with the exception of Google, most of the companies on the list have relatively low average revenue per user user. While ARPU in the internet space are generally thought to be decent if they are over $2, it appears that Facebook, LinkedIn, and Yahoo still have some ways to go before they get there. On the bright side, if they can convert those users to mobile users, they may have chances at strong revenue as the cost of user acquisition on mobile devices has recently risen to $1.80, giving Facebook and LinkedIn a fair amount of room for growth if they can find ways to present their audience to mobile apps.
Google has shown that its monetization engine is a finely tuned machine that generates money hand over fist and that appears to be represented in its overall valuation, which shows the company to be valued at more than Facebook, LinkedIn, and Yahoo combined.
Normalizing the data
Let’s now take a look at what happens when we normalize that data to get at average and median values. The idea here is to get a sense of who’s batting above average (the number clearly show Google is there but who else) and what are the long-term expectations investors have for the revenue generated on those users:
|Market cap (in billions)||$110.44||$65.94|
|Number of users (in millions)||818.75||868.5|
|Revenue (in billions)||$4.11||$1.47|
|Per user valuation||$120.84||$111.07|
|Average Revenue per User (ARPU)||$3.76||$1.72|
Based on this data, it is not all that improbable that the big players would generate between $1.72 and $3.76 per user per quarter (or between $6.89 and $15.06 on an annualized basis). What may be more difficult to entertain is those companies would hold on to users for the 8 to 16 years that would justify the current valuation based on forward revenue.
One thing that is clear is that the game of arbitrage currently happening on mobile platforms, where users are acquired at a certain price (currently around $1.80 per user) in order to return revenue over the lifetime value of the user (known as LTV) is going to have to change moving forward as acquisition prices will probably continue to increase when investors push those large companies to derive more revenue from their audiences in the mobile space.
Businesses focused solely on mobile should work on figuring how they can achieve LTV that move north of $2 in the near term and probably closer to $4-5 in the long run if they expect to survive in the long run.