Google (GOOG) DCF Analysis

Introduction:

Google was the first company I've ever valued, back then when I valued this company I remember being excited that I had finally created my first financial model without any components of my excel blowing up. Every single number wasn't a "Hmm 5% looks good." And I thought that my DCF was airtight. I posted it onto Reddit and the comments thrown me back down to reality. "These numbers make absolutely no sense" and "I suggest you look more into dcf analysis". My reaction: 😔😔. But, I marched on and 6 months and 7 DCF later, I revisited my GOOG DCF. My first reaction was "It looks like what a toddler does with a calculator pressing random numbers." So to retackle and improve my DCF again was definitely a fruitful lesson. Perhaps I may revisit this 1 year from now!

REVENUE:

Cloud

%Rev, Cloud is an area gaining massive traction due to how much convenience it adds, And the switching cost of cloud is massive, having to port over the entire database into competitors and retraining employees, so the loyalty of Cloud customers are guaranteed.
So, I’d argue that Cloud starts becoming a big part of GOOG’s identity.

Y/Y, Cloud grows at CAGR of 19% according to (SOURCE). This seems about right given how the cloud market is huge and relatively young.

Advertising

%Rev, Advertising is still going to be a big part of GOOG’s identity, however with cloud gaining traction Advertising plays a smaller role. 

Y/Y, Advertising will see its Y/Y tapering off rather than taking off. I’d argue that the growth of AI related technology like ChatGPT may render GOOG’s search useless given how ChatGPT seems to be an enhanced Google Search. Bard is trained on Audio data whereas ChatGPT is trained on text data, so the effectiveness of these AI is dependent on how the user inputs data for the AI to process. Ultimately, which AI will take off is dependent on which modal of communication consumers prefer. 

Recently, GOOG has announced its plans to launch Duet AI, AI to help augment the experience on both Cloud and Search. It’s definitely a step forward in the right direction, Duet AI could be complementary to Google’s already dominant search as not every search will likely be using AI due to how long that would take. 


Others

%Rev, With so many components in Others, there may be less focus placed on this segment of the business so it’ll take a smaller pie of GOOG’s revenue.

Y/Y, I opted to use historical average as granularity seems to be inaccurate here.

REVENUE MODEL: [SOURCE]

COST:

TAC

Given the competitiveness of Competing technology against GOOG’s main Traffic generator, I’d argue that it could be significantly costlier to acquire traffic overtime.


OTHERS

GOOG has lumped Content Review, Content Acquisition and Data Centre together in Others.

1. Content Review: Needing Employees to manually sieve through content for compliance. As the service gets more popular, more content means needing more employees. (Variable Cost)

2. Content Acquisition: GOOG has stated it uses a cost price model for determining the amount of content acquired. (Variable Cost)

3. Data Centre: Fixed infrastructure in place, but more of Data center used means GOOG needs higher bandwidth which means higher cost (Variable Cost)

Since these are variable costs, I’d argue the extent that GOOG can reduce these costs to improve margins are limited.


R&D

R&D the cornerstone of GOOG’s business philosophy will always retain a fixed % of revenue. As evident from historic data where the spread of R&D with respect to Revenue was rather small.

So, R&D maintains a fixed % with respect to revenue. But eventually when GOOG matures, I’d argue that R&D tends downwards.


Sales & Marketing + G&A

Sales & Marketing + G&A also followed the same historic patterns of R&D where they always occupied the same % with respect to revenue with a small spread.

So, Sales & Marketing + G&A occupies a fixed % with respect to revenue. But eventually when GOOG matures and develops a strong branding relies less on marketing so it tends downwards a little.  COST MODEL: [SOURCE]

COST OF CAPITAL:

COST OF EQUITY

RFR (3M Average) = 3.53%

4105.02 = [4.58% x 4105.02] x (1+5%) / (1+R) + ([4.58% x 4105.02] x (1+5%)) x (1+3.417%) / R - 3.417% / (1+R) ^2
R = 8.635%
RFR (US) = 3.417%
ERP = 5.218%

Beta = 1.1 (SOURCE)

COE = 9.2698%

COST OF DEBT

COD = 4.54% (SOURCE)

WEIGHTAGE

GOOG did not break down their debt by maturity so we take a ballpark estimate. 

Date of maturity taken to be between 2024 and 2060, at 2042.

Effective I/r taken to be between 0.57% and 3.38%, at 1.975%

Interest paid = 292.636M

MV Debt = 9204.58M

Shares O/S = 12807M

Class A (6M Avg) = $107.50

%Class A = 46.5%

Class C (6M Avg) = $106.47

%Class C = 46.61%

We don’t have a market price for Class B, so we can observe from A and C that investors paid 0.972% premium for 1 voting share, so I took 0.972% ^ 10 and got 7.54% as my premium from Class C price for Class B price. (Class B worth 10 voting share)

Class B = $114.492

%Class B = 6.89%

MV Equity = 600843.17M

% Debt = 1.51%

%Equity = 98.49%

% Tax = 21%

WACC = 9.18%

CONCLUSION:

GOOG is priced at $138.94, GOOG’s recent innovations have been made only in response to competitors. It’s more reactive rather than proactive which may be a bad thing given how strongly ChatGPT has since established its dominance over GOOG. For GOOG to improve its valuation it needs to peer deeper into the AI realm and look towards augmenting AI to compliment its advertising segment e.g. Using AI to help advertisers or to manage Ad Inventory.  All in all, my pricing previously was at $300 whereas my current pricing is at $138.94. Definitely a stark difference. Attributable firstly to incorrect revenue assumption, I was forecasting 20% growth even all the way till terminal year. WACC of 6.71% which is definitely impossible under the CAPM method of calculating because RFR is at 3+% Beta ~1% so COE alone is almost 9%. Weightage of capital was completely wrong because I used all liability instead of interest bearing debt only. But, this journey so far has been amazing! I've finished Damodaran's valuation class and an Undergraduate module into financial management which allows me to more accurately value things rationally, I'd like to think that I've went from an Irrational investor who wrongly appraises all available information on a firm's risk and returns on future cash flow into a slightly less irrational investor!

NEW DCF: [SOURCE] OLD DCF: [SOURCE]

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