Tag: facebook

Quantitative Modeling for Arbitrage Positions in Ad KeyWords Internet Marketing

Assume you treat an ad keyword as an equity stock. There are slight differences in the cost for advertising for that keyword across various locations (Zurich vs Delhi) and various channels (Facebook vs Google) . You get revenue if your website ranks naturally in organic search for the keyword, and you have to pay costs for getting traffic to your website for that keyword.
An arbitrage position is defined as a riskless profit when cost of keyword is less than revenue from keyword. We take examples of Adsense  and Adwords primarily.
There are primarily two types of economic curves on the foundation of which commerce of the  internet  resides-
1) Cost Curve- Cost of Advertising to drive traffic into the website  (Google Adwords, Twitter Ads, Facebook , LinkedIn ads)
2) Revenue Curve – Revenue from ads clicked by the incoming traffic on website (like Adsense, LinkAds, Banner Ads, Ad Sharing Programs , In Game Ads)
The cost and revenue curves are primarily dependent on two things
1) Type of KeyWord-Also subdependent on
a) Location of Prospective Customer, and
b) Net Present Value of Good and Service to be eventually purchased
For example , keyword for targeting sales of enterprise “business intelligence software” should ideally be costing say X times as much as keywords for “flower shop for birthdays” where X is the multiple of the expected payoffs from sales of business intelligence software divided by expected payoff from sales of flowers (say in Location, Daytona Beach ,Florida or Austin, Texas)
2) Traffic Volume – Also sub-dependent on Time Series and
a) Seasonality -Annual Shoppping Cycle
b) Cyclicality– Macro economic shifts in time series
The cost and revenue curves are not linear and ideally should be continuous in a definitive exponential or polynomial manner, but in actual reality they may have sharp inflections , due to location, time, as well as web traffic volume thresholds
Type of Keyword – For example ,keywords for targeting sales for Eminem Albums may shoot up in a non linear manner after the musician dies.
The third and not so publicly known component of both the cost and revenue curves is factoring in internet industry dynamics , including relative market share of internet advertising platforms, as well as percentage splits between content creator and ad providing platforms.
For example, based on internet advertising spend, people belive that the internet advertising is currently heading for a duo-poly with Google and Facebook are the top two players, while Microsoft/Skype/Yahoo and LinkedIn/Twitter offer niche options, but primarily depend on price setting from Google/Bing/Facebook.
It is difficut to quantify  the elasticity and efficiency of market curves as most literature and research on this is by in-house corporate teams , or advisors or mentors or consultants to the primary leaders in a kind of incesteous fraternal hold on public academic research on this.
It is recommended that-
1) a balance be found in the need for corporate secrecy to protest shareholder value /stakeholder value maximization versus the need for data liberation for innovation and grow the internet ad pie faster-
2) Cost and Revenue Curves between different keywords, time,location, service providers, be studied by quants for hedging inetrent ad inventory or /and choose arbitrage positions This kind of analysis is done for groups of stocks and commodities in the financial world, but as commerce grows on the internet this may need more specific and independent quants.
3) attention be made to how cost and revenue curves mature as per level of sophistication of underlying economy like Brazil, Russia, China, Korea, US, Sweden may be in different stages of internet ad market evolution.
For example-
A study in cost and revenue curves for certain keywords across domains across various ad providers across various locations from 2003-2008 can help academia and research (much more than top ten lists of popular terms like non quantitative reports) as well as ensure that current algorithmic wightings are not inadvertently given away.
Part 2- of this series will explore the ways to create third party re-sellers of keywords and measuring impacts of search and ad engine optimization based on keywords.

Does the Internet need its own version of credit bureaus

Data Miners love data. The more data they have the better model they can build. Consumers do not love data so much and find sharing data generally a cumbersome task. They need to be incentivize for filling out survey forms , and for signing to loyalty programs. Lawyers, and privacy advocates love to use examples of improper data collection and usage as the harbinger of an ominous scenario. George Orwell’s 1984 never “mentioned” anything about Big Brother trying to sell you one more loan, credit card or product.

Data generated by customers is now growing without their needing to fill out forms and surveys. This data is about their preferences , tastes and choices and is growing in size and depth because it is generated from social media channels on the Internet.It is this data that can be and is captured by social media analytics.

Mobile data is also growing, including usage of location based applications and usage of Internet from the mobile phone is leading to further increases in data about consumers.Increasingly , location based applications help to provide a much more relevant context to the data generated. Just mobile data is expected to grow to 15 exabytes by 2015.

People want to have more and more conversations online publicly , share pictures , activity and interact with a large number of people whom  they have never met. But resent that information being used or abused without their knowledge.

Also the Internet is increasingly being consolidated into a few players like Microsoft, Amazon, Google  and Facebook, who are unable to agree on agreements to share that data between themselves. Interestingly you can use Yahoo as a data middleman between Google and Facebook.

At the same time, more and more purchases are being done online by customers and Internet advertising has grown much above the rate of growth of other mediums of communication.
Internet retail sales have the advantage that better demand predictability can lead to lower inventories as retailers need not stock up displays to look good. An Amazon warehouse need not keep material to simply stock up it shelves like a K-Mart does.

Our Hypothesis – An Analogy with how Financial Data Marketing is managed offline

  1. Financial information regarding spending and saving is much more sensitive yet the presence of credit bureaus alleviates these concerns.
  2. Credit bureaus collect information from all sources, aggregate and anonymize the individual components accordingly.They use SSN as a unique identifier.
  3. The Internet has a unique number too , called the Internet Protocol Address (I.P) 
  4. Should there be a unique identifier like Internet Security Number for the Internet to ensure adequate balance between the need for privacy as well as the need for appropriate targeting? 

After all, no one complains about privacy intrusions if their credit bureau data is aggregated , rolled up, and anonymized and turned into a propensity model for sending them direct mailers.

Advertising using Social Media and Internet

https://www.facebook.com/about/ads/#stories

1. A business creates an ad
Let’s say a gym opens in your neighborhood. The owner creates an ad to get people to come in for a free workout.
2. Facebook gets paid to deliver the ad
The owner sends the ad to Facebook and describes who should see it: people who live nearby and like running.
The right people see the ad
3. Facebook only shows you the ad if you live in town and like to run. That’s how advertisers reach you without knowing who you are.

Adding in credit bureau data and legislative regulation for anonymizing  and handling privacy data can expand the internet selling market, which is much more efficient from a supply chain perspective than the offline display and shop models.

Privacy Regulations on Marketing using Internet data
Should laws on opt out and do not mail, do not call, lists be extended to do not show ads , do not collect information on social media. In the offline world, you can choose to be part of direct marketing or opt out of direct marketing by enrolling yourself in various do not solicit lists. On the internet the only option from advertisements is to use the Adblock plugin if you are Google Chrome or Firefox browser user. Even Facebook gives you many more ads than you need to see.

One reason for so many ads on the Internet is lack of central anonymize data repositories for giving high quality data to these marketing companies.Software that can be used for social media analytics is already available off the shelf.

The growth of the Internet has helped carved out a big industry for Internet web analytics so it is a matter of time before social media analytics becomes a multi billion dollar business as well. What new developments would be unleashed in this brave new world is just a matter of time, and of course of the social media data!

Free Tibet

We should all ask China to free Tibet because of the following reasons-

10 Reasons to Free Tibet

1) Replace a system of governance which is giving 12% GDP growth with a 1000 year old belief that one old guy is really a reincarnation of GOD

2) Because it is a romantic idea

3) The average Tibetan is much better economically than most other countries in Asia and Africa. Still freedom is messy- Donald Rumsfield.

4) So we can sell beer, Facebook ads, Internet Pornography to Tibetans which do not have the liberty to do so currently

5) So we can explore that area for mining and minerals

6) Damn it. We need one more ally for the free world. So we can invade more non free countries.

7)  Tibetans girls are hot.

8) Dalai Lama is cool. and he doesnot charge by the hour unlike other yoga Gurus.

9) We need to encircle China just like we did in the 19th Century and Opium Wars

10) So artists like Ai Wei Wei can blog freely

1 Reason not to Free Tibet

1) Tibetans want to be free. If we give them democracy- they will be disappointed to know that the bullets just get replaced by the pepper spray. How silly is that? The desire to be free- when there is no such thing as free anymore.

(This was an article in Sarcasm and meant as literary and not a pseudo-intellectual political article. I have no training in Politics. For details see http://en.wikipedia.org/wiki/Sarcasm

Should you buy Zynga or Wait for the FB IPO

I am going to make a case for whether to buy or not buy  Zynga, and waiting to buy Facebook instead. Of course if Mark Pincus offers you a deep discount, and Mark Zuckenberg totally goes over the top with his P/E multiple, all bets would be re-valuated.

In the interest of your time, and my personal happiness, I am going to use a fairly standard way to measure attractiveness of both these companies- notably the Porter’s Five Forces Model. I will also review the recent experiences of Groupon and LinkedIn valuation to underscore what subtle differences in culture, and reputation of founders can affect the eventual value creation or destruction in an IPO.

(to be continued)

A Brief Overview of Open vs Closed in Computing

1984 – IBM   (Big Brother) vs Apple  (Computing opened for individuals)

1988- Apple (Closed Hardware and Software) vs Microsoft (  Licensed to all software)

1998- Microsoft (Source code is closed but licenses to all) vs Linux (Open Source Code)

2008- Apple (Closed Hardware and Software) vs Google (Android/Linux) -(Free and Open Source)

2010 – Google (Web open to search) vs Facebook (Closed to search)

2018 (?)-Google (Code is open for all non revenue generating software, but search engine algorithm is closed) VS       TBD

Statistics on Social Media

Some official statistics on social media from the owners themselves

1) Facebook-

http://www.facebook.com/press/info.php?statistics

Date -17 Nov 2011

Statistics

People on Facebook

Google Plus Gaming vs Facebook Gaming

After a few hiccups, Facebook has gotten the notifications scrolling back and much better than Google Plus. This gives it a cleaner advantage in social gaming interface – even for the same game. and of course many more gamers!

Clearly the games stream is much more efficiently designed in FB, probably because they need to earn some ad revenue- that forces you to think more optimally for space. FB interface is also bug free compared to the constant error in G+ (error changing circle membership– ideally I wanted to create one gaming circle for all gaming friends)

See this  – not just compare the games stream/notifications only

vs