First, let's discuss the idea of Graph Search. Graph Search provides a limited search tool for people, photos, places and interests. The results of the search will show pages that have been "liked" or checked-in. It allows users to search within his or her group of friends. Assuming one can trust his or her friends, this search engine can challenge Yelp. However, there are flaws to this search engine, and I will use an example of the results I received from Graph Search to demonstrate the fundamental reason that this feature is inefficient.
"Cafes nearby Union Square" or "Cafes that my friends in New York have been to"
(Just for clarification, I have over 1,200 friends and a third of my friends are in New York.)
Activity on pages — through check-in and "like" — is not the best indicator of value; users don't necessarily check-in or "like" a page because they liked (pun intended) the value of the good, service or place. For example, the individuals in my college and professional network provided a short and unattractive list of Cafes nearby Union Square or in New York. I tried this search on two other profiles to check that it was not just my profile. The incentives for users to check-in or "like" are not aligned with Graph Search. We can claim that there are individuals that simply check-in at places or "like" pages much more than average, while there are individuals that simply don't check-in or "like" very often or even at all. Therefore this list of recommendations of cafes was only created by a small group of very active users, which is very particular.
I took the liberty of comparing this Graph Search list to a list generated by Yelp for the same purpose. There was a massive difference in not only value but also the length. Yelp attracts a certain audience that is critical to the value of good or service, and the number of reviewers are vast. This is plain statistics; because not enough users that check-in or "like" exist, there is a large room for error. I plan to let the Yelp audience decide the fate of my coffee dates.
Graph Search also lacks the mobile application. According to Ben Starley, the vice president of social technologies for Rio SEO and Covario, "Industry research suggests that many consumers turn to specific mobile apps to conduct vertical searches." For restaurant recommendations, consumers turn to the mobile Yelp app. For local weather, consumers turn to the Weather Channel app. For directions, consumers turn to the Google Maps app. Therefore mobile applications are the perfect place for the use of Graph Search. It is a major setback that Facebook is unlikely to deliver Graph Search into its mobile applications in 2013.
Facebook's Graph Search is not a legitimate threat to Yelp yet. To say the least, any price fluctuations in Yelp caused by Graph Search are not justified, and Facebook's Graph Search may be the reason for its profit margins issues.
When it went public in May 2012, Facebook was exposed in scrutiny, especially after an incredible IPO of $38 per share. One problem that surfaced was its revenue model. Facebook had a great set up and its user base was continuously expanding (now at 1.1 billion), but it was not monetizing very well. In order to combat this issue, Facebook worked on some initiatives. The "promotion" feature (although I initially believed that this feature could be harmful in the perspective of regular users) is working well for page owners. Number of pages is growing and Facebook is providing a lot of options for page owners, including PageMetrics and reach data that show how many users have been reached. Application of Facebook Ad Exchange creates a more efficient way of advertisement. Ultimately, Facebook's mobile revenue is looking good due to aggressive focus on mobile advertising.
Their determination to monetize and improve has rewarded Facebook with more users and revenues, but it has also cost Facebook quite a bit. New ideas implemented by Facebook (mainly mobile advertising, Facebook Ad Exchange and Graph Search) grew revenues but also increased costs. In the fourth quarter, revenue increased 40% and expenses increased 67%, partially due to a 44% increase in employee numbers. The decline of Facebook's profit margin is becoming a pattern. Its rise in revenue was not achieved naturally, and the fundamental monetizing problem may still exist.
As I mentioned earlier, I believe that Facebook Ad Exchange and mobile advertising are positive directions, but Graph Search was an ambitious and risky move that will generate more costs than revenue (it aims to increase the value for its users without any monetizing plans). It should continue to focus on monetizing, because it has not solved the fundamental issue if its margins are suffering.
According to analyst estimates, the average earning estimates is 57 cents per share for the current fiscal year, and 78 cents per share for the next fiscal year. This suggests that Facebook trades at a current P/E of 49.31 and a forward P/E of 37.24, while its sector trades at 15.05 P/E. Given the recent decline in margins, I would even say that these analyst earnings could be generous. Compared to Google (GOOG) with a 16.91 PE or Apple (AAPL) with a 9.88 PE, Facebook is not the best bet.
For these reasons, Facebook is a short for the time being; its high PE ratio is not justified, as there is no genuine reason for investors to believe that Facebook can increase both revenues and margins.
However, I would keep a close eye on Facebook. It is possible that the rise in cost was attributed to fixed costs of development of the new improvements like Facebook Ad Exchange and mobile advertising, which means that costs should subside in the next year. If it can shows sign of spending maintenance (especially on risky ideas like the Graph Search) while mobile advertising and Ad Exchange prove to be rewarding, then I would invest in Facebook.