Latest developments

Google I/O conference offered a glimpse into GOOG’s vision for the “AI First” world. Google CEO Sundar Pichai kicked off his keynote with an update on the scale of Google’s core mobile/desktop products that have scaled to 1bln+ users (Gmail, YouTube, Search, Maps, Chrome & Play) and 2bln+ users for Android. Google is leveraging AI/ML to make tangible day-to-day benefits to end-users today. In addition, Google highlighted that many products are on their way toward 1bln users incl., Google Drive (800m users) & Google Photos (500mln users). GOOG has gradually transformed from digital advertising to also a leading mobile computing utility company.

I/O highlighted how the company’s products have begun the pivot from “mobile first” to “AI first”. Based on the demos shown, GOOG is well positioned to deploy its market leading advantages in AI/Machine Learning across a host of its products (Assistant, Photos, Home & Lens) as consumer cloud continues to move to the forefront of individual user mobile computing experiences & deepen platform engagement/stickiness. We view Google Assistant and its integration across multiple products as key to GOOG navigating to more personalized approach to search, information access and notifications including using speech.

Daydream VR (virtual reality) is still in early stages and GOOG is laying grounds for eventual mainstream adoption. While the infrastructure appears promising (headsets, phone line with VR capability), a relative dearth of VR content continues to be a limiting factor near-term. GOOG recognized the need for more free VR content trials to bolster consumer willingness to buy VR. The business case for GOOG is compelling with 3x more buyers/active user in VR relative to 2D apps, 32% more spend per active user.

Google revealed its second generation Tensor Processing Unit which is designed to accelerate its effort in machine learning and artificial intelligence. The processor is touted as Machine Learning utility for everybody. GOOG is aiming to offer its machine learning infrastructure to third parties through Cloud TPU, which will be available on the Google Compute Engine.

Google Marketing Next ’17 event emphasized number of moat-widening enhancements for advertiser including use of smarter targeting through improved data access and machine learning. Google continues to roll out targeting capabilities that incorporate deeper and broader intent signals generated by a user’s past searching behavior. This is a blending of behavioral targeting (search and website browsing) that has not previously been offered to marketers.

GOOG is extending AMP (accelerated mobile pages) to search landing pages in efforts to improve the mobile web user experience. AMP is also being automatically extended to display ads across the Google Display Network. Improvement in ad loading times and landing page experiences are aimed at improving CTR (click-through rate) and downstream conversions.

Risks

Modelling itself after Berkshire-Hathaway, as the only known successful conglomerate, Alphabet holding company was restructured in order to ensure that next Google is invented within Alphabet umbrella. Single biggest existential thread to technology companies is obsolescence and technology substitution. Management has recognized this risk and is actively pursuing number of “moonshots” with a clear intent to disrupt from within. No major technology company went out of business due to overinvestment, rather that opposite, many technology giants faded because they “missed the turn” on the unpredictable road of technology innovation. We are encouraged by GOOG’s management determination to avoid this mistake. Successes may be few and far in-between, however pay-off may be very significant (remember how YouTube and Android started).

The key risk for GOOG in the short term is changing nature of human interaction with the rise of voice-based search input thru devices such as Amazon’s Echo and Google Home. This could impact GOOG’s ability to display ads. GOOG has began to experiment with visual responses to voice search such as display on user’s smartphone or TV. Voice in our opinion will supplement visual searches.

Valuation

Valuation of company like GOOG is very challenging. Analyst would need to reliably estimate the rate of growth, duration of which the persistently high growth can be sustained and terminal value of company after the growth moderates. It is also prudent to base the estimate on “as is” situation based on known facts about the business today, and without including any future uncertain revenue from moonshot bets (such as self-driving cars).

GOOG is selling on forward PE of about 25 ex-cash, adjusting for stock based compensation (by adding it back to income and instead increasing the number of shares to arrived at fully diluted EPS of about $45-$50).

The key question therefore becomes as follows – is there enough market share to add another GOOG and does GOOG have the necessary products to capture this share?

Digital ad spending (including mobile) will increase by 20.3% to reach $194.60 billion in 2016, making up 35.3% of total media ad spending. By 2020, spending will top $335 billion and represent over 46% of total media ad investment.

Assuming GOOG maintains its current market share, it is reasonable to assume that it’s revenue will increase proportionally with the market i.e. by circa 50% by 2020 from 2016 base. This translates to $73bln revenue in 2016 to projected $110bln by 2020. It is also reasonable to assume that with GOOG will capture disproportional share of this incremental revenue given the faster-than-market growth of it’s core properties (Android platform, YouTube, Maps). So we’d assign incremental $20bln of revenue to GOOG, bringing estimated total revenue to $130bln by 2020. This means net $57bln of additional revenue by 2020.

Maintaining existing operating margin profile, $130bln of revenue would generate around $56bln of pro-forma adjusted net income, which over 710mln shares equates to $80 EPS per share. Assuming 15 PE multiplier, stock would be trading at $1,200 per share + $300 of cash ($220bln over 710mln shares) = $1,500 per share. Discounted back by 3 years to end-2017 at 10%, gives estimated value of $1,100.