My thesis is that Alphabet (GOOG, GOOGL) has an advantage because they have a culture that focuses on data driven decisions. This culture explains much of the success the company has had to date, especially with their dominant search engine and AdWords.
Executive Chairman Eric Schmidt communicates the importance of using data for decision making:
“Google is run by three computer scientists,” he said. “We’re going to make all the mistakes computer scientists running a company would make. But one of the mistakes we’re not going to make is the mistake that nonscientists make. We’re going to make mistakes based on facts and data and analysis.”
[ Googled Location 464]
Google's properties segment accounted for almost 71% of Alphabet revenue in Q2 2017 and much of the revenue in this segment is from AdWords. Top line revenue in this segment was $18,425 million compared to $15,400 million for Q2 2016 meaning year over year growth of 19.6%.
Rather than having internal ad reps set pricing, Google has ad market customers set more efficient prices by relying on data to make keyword bids. This change from fixed fee ads to auction-based ads occurred back in January 2002:
By then Schmidt had discovered that the ads priced through bids were collecting twice as much revenue as the ones that had been sold by the ad reps. It turned out that the reps were pricing the ads too low for the market. One of the beauties of Google’s ad system is that it automatically reaches exactly the price the market will bear.
[ The Google Guys Page 99]
One of the best things about AdWords is the decision to use click-through data to help keep the most relevant ads in place. This data driven decision ensures that the user experience is pleasant because irrelevant ads are minimized. The 2003 AdWords Guide shows an example where Advertiser B has the #1 position over Advertiser A despite the fact that Advertiser B bids just $0.40 for the keyword phrase while Advertiser A bids $0.65. The reason Advertiser B wins the match is because Advertiser B has a higher click-through rate of 1.8% compared to just 1% for Advertiser A:
Ad Position #1 ==> Advertiser B: $0.40*1.8% = 0.72 score
Ad Position #2 ==> Advertiser A: $0.65*1.0% = 0.65 score
Traffic Acquisition Costs [TAC]
Traffic acquisition costs continue to climb and put pressure on margins. However, it makes sense for Google to pay Apple billions of dollars a year to be the default search engine on iPhones and iPads. Lawrence Lessig explains the benefits Google enjoys as more searches are performed and more data is gathered:
“They have produced this amazing machine for building data, and that data has its own ‘network effect’”—the more people who use it, the more data generated, the more advertisers flock to it. “Everything sits on top of that layer, starting with search. Every time you search, you give Google some value because you pick a certain result. And every time you pick a result, Google learns something from that. So each time you do a search, you’re adding value to Google’s database. The database becomes so rich that the advertising model that sits on top of it can out-compete other advertising models because it has better data.
[ Googled Location 2,381]
This rising TAC expense is one reason why the bottom line is not growing as fast as the top line in the short run. However, I am sanguine about the disparity in the long run. Odds are the company will control costs such that bottom line growth becomes somewhat close to top line growth in the long run. The earliest earnings call transcript I can find is from Q3 2005. It is noteworthy that TAC as a percentage of web advertising revenue in that quarter was 34% while it was just 22% of advertising revenue in Q2 2017.
The $2,736 million European Union fine which hit the Q2 2017 financials is a real GAAP expense but it is myopic to view it as a recurring expense against owner earnings. As such, I back it out when looking at the earning power based on trailing twelve months [TTM]. I treat stock based compensation as a cash expense so I back it out of TTM adjusted free cash flow [FCF].
TTM Adjusted FCF/EV = $572,494 million/$20,256 million = 28
Note that the timing of stock based compensation has changed such that it will not be seasonally higher in Q3 and Q4 for 2017 the way it has been in prior years. This is one reason why I think the adjusted FCF will be higher in the near future.
Google's first 10-K for the 2004 year shows the following:
Revenue: $3,189 million
Adjusted FCF: $379 million [$977 million - $279 million - $319 million]
This implies an adjusted FCF of $125,455 per employee. Contrast the above to the 2016 10-K where we have the following:
Revenue: $90,272 million
Adjusted FCF: $19,121 million [$19,121 million - $36,036 million - $10,212 million]
This implies an adjusted FCF of $265,374 per employee.
The growth in adjusted FCF from just $379 million in 2004 to $19,121 million in 2016 is staggering. Also, the adjusted FCF per employee is now more than double as the company scales efficiently.
Given the data driven philosophy which contributes to robust top line growth, I think Alphabet is trading at a reasonable valuation for long-term investors in this low interest rate environment. I believe it will outperform the S&P 500 over the next five years. One of the main reasons for this is that the growth is reasonably priced and it has a long runway. eMarketer and others show that advertising continues to shift to mobile where Alphabet is extremely well positioned. This means current Alphabet investors along with new Alphabet investors who purchase shares at reasonable prices should be able to participate in the long run success of the company if they are patient.
Adjusted Free Cash Flow for Trailing Twelve Months In millions USD:
= 6M17 + FY16 - 6M16
= (16,951 - 4,012 - 5,339 + 2,736)
+ (36,036 - 6,703 - 10,212)
- (16,778 - 2,997 - 4,580)
= 10,336 + 19,121 - 9,201
Enterprise Value [EV] in millions USD:
328,347 (345,679,000*949.89) class A GOOGL 9/7/17
334,905 (357,824,000*935.95) class C GOOG 9/7/17
(79,002) marketable securities
Googled: The End of the World As We Know It by Ken Auletta
The Google Guys: Inside the Brilliant Minds of Google Founders Larry Page and Sergey Brin by Richard L. Brandt
Disclosure: I am/we are long GOOG, GOOGL, VOO.
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 material in this article should not be relied on as a formal investment recommendation.