1. Make a facebook page
2. Promote it with Facebook ads > get fans
3. Use page status updates to drive traffic to your site > monetize the landing page
4. Invest the earnings in more Facebook ads > goto step 3

This basic cycle is possible with with any form of advertising, but does it work any better on Facebook than it does with TV ads or Adwords? The big difference is that once you have earned a Facebook fan, you can reach them many times until they unsubscribe from your page. This makes Facebook page marketing more like time-tested email marketing.

Facebook social games are a great example of a similar cycle. The addictive games keep users returning daily, and monetize this traffic with virtual currency and often scammy offers. The cycle is reinforced with paid Facebook ads and social advertising (mostly personal status updates).

But these games are social, interactive, and fun. The tight integration between the game platform, social platform, and ad platform has lead to domination of online gaming. So how fast can a Facebook page grow, if it only monetizes weakly through a non-interactive landing page?

Facebook page growth: not good

The below graph is one possible answer to "how fast can a page grow" with this strategy. After an initial $100 investment in Facebook ads to build a starting fan base, you can expect to be making US$800/month in ad revenue after two years. Of course, all this would be plowed back into Facebook ads, and you’d still be out $100. The calculation parameters are explained further below.

In this base case, each fan will "pay" for their acquisition cost after 6.3 months, or after 100 status updates have been made (at the rate of 4 per week). The characteristic (doubling) period is 18 weeks.

Better cases

I graphed a rather pessimistic case so that nobody is even tempted to actually try this. But like all cases of exponential growth, the outcome is highly dependent on the factors that determine the exponential growth rate. Here, those factors are cost per fan, CPM of the external site, and fan clickthrough rate.

If you reduce your cost per fan from 15 cents to 13 cents, the fan growth rate would double. Or if 20% of the fans clicked-through instead of 15%, you would make $4000/mo in ad revenue instead of $800. And of course if you extended the base case to the 3-year mark, ad revenue would hit $5,380/mo.

The most likely improvement is in landing page monetization. The assumed $5 CPM is possible with a good general-content site, but a site for a more lucrative market can bring much higher CPM through higher CPC ads and affiliate programs. According to this model, a site with $10 CPM would make $80,000/mo by the 2-year mark.

This model is probably reasonable for under $1000/mo revenue. Beyond that, the cost per fan would escalate since you simply wouldn’t be able to buy enough ad impressions at that low price ($0.12 CPC) to maintain exponential growth.

Base case parameters

eCPM – How much you can earn per thousand visitors to your landing page. Depends entirely on your visitor demographics an interests, and resulting from your Facebook page targeting and fan page topic. Assume $5 CPM and 2 pageviews per visitor, making US$10 per thousand fan visits.

CTR – Click-through rate of your status updates. Depends mostly on how intriguing your content is. I’ve seen between 5 and 30 percent of total fans click-through to a status link. Assume 15 percent.

CPA – Cost for acquiring one Facebook fan. While it might cost about $0.12 per click with a fan conversion rate of about 40% (meaning $0.30 per fan), social actions (Facebook page recommendations and status updates of joining fans) can at least double the value. Assume overall cost per fan of $0.15. I’ve also assumed a fan attrition rate of 0.2 percent per week.

Amazon developed the system in 2005 to crowdsource the job of categorizing its own products, mostly CDs. It’s been open for public use (in Beta form) ever since.

I’m writing about it because mTurk has remained impressively unknown over the years, even among techies. But for entrepreneurs trying to build web systems fast (and gain users, content, discussion, etc.), it can be a powerful secret weapon.

The Idea

Mechanical Turk bridges the gap between completely automated tasks (such as counting the words in a book), and creative tasks that require human thought (such as writing the book). The mundane tasks that live in this gap are not quite doable by machines yet. An example is re-writing a book, paragraph-by-paragraph, to retain the original meaning but with a different wording (as with avoiding duplicate content penalization).

How it Works

1. Break your crazy task into many micro-tasks (called “HITs”: Human Intelligence Tasks”).
2. Design your HIT on mTurk: describe what each “Turker” must do, how they submit the answer, and how much you will reward them.
3. Submit your HIT, and wait…
4. When the work is done, approve it so the Turkers get paid.

Read their FAQ to learn the rest.

Who does these tasks?

Turkers seem to come from every country, with most from the US and India. In fact it’s surprising there aren’t more in India considering the state of Elance, ODesk, and other crowdsource-ish markets. The last I checked, Amazon only direct-deposited earnings into bank accounts or paid Turkers in Amazon credits, which would work best for North Americans. In any case, you can specify which countries are eligible to complete your HITs.

How much do I have to pay?

You can set any prize for your HITs but since it’s a free market, you need to set a reasonable price to get any work done. Many HITs are priced at only $0.01 for simple tasks like image tagging, while others are over $5 USD. I try to keep the effective hourly rate for my hits between $8 and $12 per hour.

Example Uses

My first useful task for Mechanical Turk saved me days of work and hundreds of dollars. I had a video aggregation task; I needed metadata and embed codes for one thousand YouTube videos which met certain criteria. I planned to employ some of my friends for this task and pay them very fairly, which would have run a bill of about $500 and taken about a week. Instead, I broke it into 100 HITs of 10 videos each and posted it on mTurk. To my amazement, the next morning (7 hours later) I had one thousand videos indexed as needed for a quarter of the planned cost.

Other great mTurk uses include:

• Tagging content (photos, videos, articles, etc.)
• Rating and sorting content
• Writing comments, making posts
• Writing reviews, answering simple questions
• Surveys
• A/B page testing
• Aggregation (eg. building a directory)
• Research (eg. finding competitors)
• Clicking ads, Digging articles (just kidding! Totally against TOS, but you were thinking it, weren’t you…)

Surveys

My main use of mTurk has been rapid market research in the form of surveys. In five minutes you can make a basic survey using mTurk’s native forms, or you can link to your own survey system (I prefer PHP-based LimeSurvey).

How fast and how much? About $0.03 per survey question equates to a fair wage, and if you need less than 50 responses (such as with a pilot survey) you won’t wait more than half an hour for all your responses. Of course there is some selection bias with these surveys that you’ll have to consider.

And remember, Turkers are customers too! If you are doing a market research survey for your new widget-thing, why not allow the Turkers to opt-into a mailing list so they can hear when you launch? In the last big survey I did, about 20 percent of respondents gave their email for just that purpose, meaning the survey can pay for itself in leads. It worked for Pixlin.

One problem

When I last checked a month ago Mechanical Turk was still not available to Canadians, but I’m sure you’ll find a way around that.

For sites serving a passionate niche market, fan pages are an excellent investment because:

• You can build you fanbase quickly using Facebook’s very targeted ads
• You can gather quality community feedback
• You can encourage fans to interact directly with your site (increasing site traffic and user-generated content)
• Pages provide tools that your site may not have (discussion board, wall, photo albums, etc.) to better engage your users

In this short post I’ll discuss the level of fan engagement you might expect from your page. My experience is mostly drawn from building the pages for the video site FightTube, which include: FightTube, FightTube – Taekwondo, FightTube – MMA, and others. The main content on these pages are links to FightTube videos, updated frequently.

How Pages Deliver Value

Initial Contact and Exploration

When someone discovers your fan page they’re likely to click-through to your site if they’re presented with engaging content. I found that about 85% of new fans clicked a video link to our site on the same day they became a fan. Other engaging content could be links to photo albums or to full articles. Visitors could bounce off your fan page if your content becomes buried between fan comments, so setting the “Default View for Wall” to “Only Posts by Page” will keep things clean. You can also showcase your most engaging content by creating an FBML tab for it, and setting that tab as the landing page.

Fan Updates

You can "send an update" message to all fans, which goes to the "Updates" section of their inbox. This isn’t terribly useful in my opinion because I don’t think most people check their "updates", and I’ve had poor response rates using this.

Page Status Updates

When you update your page’s status (the "what’s on your mind?"), it can potentially reach the news feed of all of your fans. Of course it won’t reach them all, because:

• Some fans won’t visit Facebook in time (other content will bury your status)
• Some fans may use filters that exclude it (page status updates are seen under the filters "News Feed" and "Pages", but not "Links" or "Status Updates").

So how many fans can you reach with a status update? That’s a great question; I don’t know because there’s no direct way to measure it. For short statuses featuring a video link (and video thumbnail), I’ve measured about:

• 5 to 15 percent of fans click through to the video
• 0.1 to 2 percent of fans "like" the status
• 0.1 to 1 percent comment on the status

The chart below shows interactions for one particular fight video. This link was posted at 2 P.M. on a Sunday, but I feel the optimum time of day for a page update (assuming North American and Western Europe fans) is 3 P.M. from Monday to Thursday. The graph illustrates how about 80% of interaction occur in the first eight hours.

Photos, Videos, Events, Links, and Notes

These can also be used to reach your fanbase, but I don’t use them so I don’t have much to say here. Note that videos are special: any videos a page uploads to Facebook will have a "become a fan" button permanently attached to it. If the video becomes widely spread (using "share"), it could win you many new fans.

Next posts:

The value of a fan: Monetizing Facebook Pages

The cost of a fan: Growing Facebook Pages

In this article you will learn how to:

• Extract infinite energy from a vacuum
• Manipulate gravity and undergo interstellar travel.
• Apply cheesy Star Wars quotes to a serious topic.

The force is strong within you

Imagine a renewable energy source so dense, a cup full could vapourize all the oceans on Earth!  While this idea sounds even too bold for Star Trek, it is one possible consequence of the zero-point radiation field (ZPF) [1].  The ZPF is a uniform photon flux which permeates the entire Universe, existing even in total vacuum.  It is not casually detected because the ZPF exists everywhere uniformly; perceiving it would be like a fish perceiving the water it swims in.  Although the existence of ZPF is widely known and accepted by most physicists, the implications of the field and its role in the universe remain a matter of speculation.  Physicists have identified four technologies the ZPF may yield: tapping ZPF energy, manipulating inertia, altering gravitation, and generating forces (propulsion).  All four technologies have theoretical merit, and with expanded research and scientific attention, all four will likely be achieved.

The purpose of this essay is to convey the present state of zero-point radiation research and highlight areas of high potential for ZPF-based technological advancement.  An effort was made to simplify the often complex physics inherent to the subject, and present it in terms agreeable to engineers and general scientists.  Several interesting ZPF-related phenomena have been excluded from this essay in order to limit the mathematical content.  Please see the references for more detailed discussions.

You Must Unlearn What You Have Learned

What do you get when you remove all matter from a volume?  “A vacuum” may be the obvious answer, but this is not entirely accurate.  Prior to the 19th century, it was thought a vacuum was attainable by removing all visible matter and gas.  With the development of the electromagnetic theory, it was realized that attempts to create a perfect vacuum are foiled by the presence of radiation [2].  This was not particularly disturbing to scientists since most forms of radiation could be shielded from the vacuum, and even thermal radiation could theoretically be eliminated by cooling the immediate surroundings to absolute zero.  The vacuum was nothing special at that time; it was rather boring even.  The development of quantum theory in the early 20th century alerted physicists to how interesting vacuums still are [2].  Far from empty, the vacuum is witness to such curious things as the spontaneous creation and destruction of matter and antimatter.  Additionally, a photonic radiation field which cannot be suppressed exists in the vacuum [2].  This is called the zero-point radiation field.

The theoretical basis for the ZPF is simple and widely accepted.  The Heisenberg uncertainty principle asserts there is a fundamental limit to our knowledge of any particle’s state.  The more precisely one measures a particle’s position, the less accurately its momentum (mass times velocity) can possibly be measured.  This does not describe a flaw in measurement technology, but rather a fundamental condition of the Universe [3].   Consider now an ideal one-dimensional harmonic oscillator, such as a mass on an ideal spring moving back and forth.  For a small enough mass (such as an electron), the Heisenberg uncertainty principle dictates the oscillator can never come to complete rest, since this condition of zero momentum is forbidden (the uncertainty in its position becomes infinite).  Furthermore, the oscillator is limited to possessing only particular states with energy levels of E_n = (n + 1/2)hf, where h is Planck’s constant and f is the oscillation frequency.  The system’s energy can be raised and lowered in units of n, but when the kinetic energy (temperature) becomes zero, n becomes zero, leaving a residual energy of  hf / 2 [1].

Electromagnetic radiation such as radio waves, X-rays, and light can be thought of as waves traveling through space at the speed of light.  In many ways they behave as harmonic oscillators, each carrying an amount of energy proportional to its frequency.  According to Heisenberg’s uncertainty principle, the average minimum radiation energy of any given frequency is  hf / 2.  While this is a minuscule amount of energy, the number of possible frequencies is tremendous, yielding a very high theoretical energy density [3].  This universal sea of radiation is called the zero-point field.  The magnitude of the energy flux depends on the radiation cutoff frequency, which is believed to be 1043 Hz, since space itself is thought to “break-up” at the corresponding wavelength distance of 10-33 cm.  Assuming this cutoff, the zero-point energy density is 1070 Joules per cubic meter – 110 orders of magnitude greater than the radiant power at the centre of the Sun [3, 4]!

Is the zero-point field real, or just a curious mathematical by-product of the uncertainty principle?  In the year 50 B.C., the Roman poet and naturalist Titus Lucretius Carus recorded his observation of metallic plates sticking together in a peculiar way.  Exactly 2000 years later, Dutch physicist Hendrik Casimir showed the phenomena was a theoretical consequence of zero-point radiation.  As conducting plates are moved together, zero-point radiation between them is reflected between their inner surfaces.  Boundary conditions at the plate surfaces allow only certain radiation frequencies to be reflected, and those with wavelengths greater than the plate separation are quickly damped-out.  The result is an imbalance of the radiation pressure between the inside and outside of the plates, causing a net attractive force between the plates.  The Casimir Effect was proved experimentally in 1996 with high correspondence between results and theory.

How can such a powerful energy field be nearly undetectable?  A common dismissal is that we cannot sense it because it surrounds us and penetrates us – it is the “dead state”, upon which all other energy is measured.  The light we do see is over and above the background zero-point field.  The homogeneity and uniformity of the field mask it from casual observation.  As suggested by the Casimir Effect, matter is continuously interacting with the zero-point field, but the effects of radiation pressure always cancel due to the uniformity of the field.  Even objects moving at constant speed are unaffected by the field, since the field is proven to possess the special property of being “Lorentz-invariant”, meaning it appears uniform in all directions to objects moving within it [5].

Use the Force

While the existence of the zero-point field is a proven fact, the ability of the field to do useful work is controversial. How can energy be extracted from such an elusive and uniform medium?  The situation has been likened to the impossibility of extracting work from a uniform thermal reservoir, but this is not quite the case.  The zero-point field is not itself a thermal reservoir, and possesses very different properties [5].  The Casimir force forms a basis for the application of thermodynamic theories towards developing an energy extraction machine.  Despite several creative attempts, no Casimir engine can operate beyond its first cycle – as the plates perform work and collide, they require an equal amount of work to be separated to repeat the cycle [6].  Although impractical as energy generators, Casimir devices are conceptually significant.  They demonstrate it is possible to extract some energy from the zero-point field.

Many promising variations on the Casimir engine have been proposed.  One such derivative involves allowing a charged plasma stream to “condense” under the Casimir force.  After an initial energy input to overcome the plasma’s coulomb barrier, particle condensation should release enough energy to drive the cycle with a net energy gain.  Although a highly speculative design, several countries are reportedly exploring this technique on an experimental basis [6].

Patented zero-point energy collector

In 1996 a historic patent (#5,590,031) was granted to Dr. Mead of the United States Airforce.  The subject of patent is a system for “converting high frequency zero point electromagnetic radiation energy to electrical energy” [7].  Unlike a Casimir engine, Dr. Mead’s device has no moving parts.  Two conductive spheres resonate at their natural frequencies as they are excited by incident zero-point radiation (Figure 1).  The spheres are of slightly different size, and resonate at different frequencies.  Secondary radiation emitted by the spheres interfere with each other, producing a beat frequency oscillation in an antenna positioned between the spheres.  The collected signal is then electronically rectified and used for work [7].  There is no word on whether this device works, possibly because of the difficulty distinguishing between zero-point radiation, and other sources of radiation.  Dr. Mead realizes that smaller spheres would yield more energy, since they resonate at higher frequencies, and the energy density of zero-point radiation is proportional to the frequency cubed.  Consequently, the smaller this machine is, the better it becomes, implying the use of microscopic, or even single particle resonators like protons and neutrons [8].  Clearly there is great potential for this invention, and many more clever devices are expected to follow.

Although the most obvious thing to do with an infinite energy field is to extract energy from it, the ZPF may present some significant fringe benefits also.  Already mentioned is how the zero-point field is Lorentz-invariant, and thus undetectable by any means (such as by Doppler shift) by observers at rest, or moving at constant velocity.  Upon acceleration however, an asymmetry develops in the zero-point field, the magnitude of which is proportional to the acceleration of the object [5].  Physicists Haisch and Rueda have succeeded in deriving Newton’s second law of motion, F=ma , as a consequence of the zero-point field – a significant accomplishment given the second law was previously considered an underivable postulate [5]).  Their conclusion is that “matter resists acceleration not because it possesses some innate thing called mass, but because the zero-point field exerts a force whenever acceleration takes place” [5].  Four years after their initial publication, Haisch and Rueda arrived at the same conclusion using a completely different analysis, but this time deriving the complete relativistic version of Newton’s second law.

A consequence of the zpf-inertia theory is the idea of inertial modification through manipulation of zero-point radiation.  Between closely spaced conductive plates (a “Casimir cavity”), the zero-point field is slightly anisotropic, being weaker in one direction than in others.  Under these conditions, inertial mass should also become directional.  Unfortunately, the change of mass as a function of direction would only be on the order of 10-22 percent under experimental conditions – a little too small for practical use [5].

If inertia is a zero-point field phenomena, then what about gravity?  Einstein’s principle of equivalence requires gravitation to have an analogous zpf-related cause, which would neatly unify inertial and gravitational mass [3].  Manipulation of zero-point radiation might then lead to anti-gravity technology, a concept not as far-fetched as it may seem.  Antigravity has long been a proposed as a necessary mechanism to explain the current structure of our Universe.  Recent astronomical observations indicate the Universe is actually accelerating apart, likely resulting from zero-point influence [8, 9].  Promising work is being done to explain gravity as a long-range effect of zero-point radiation, although a complete theory has not yet emerged [5].

The fourth major technological hope for the zero-point field is propulsion.   If inertia and gravity are zero-point phenomena, then an asymmetric interaction with the field could provide a propulsive force.  Although purely speculation at this time, the concept is exciting as a future mode of space travel.  It is currently the only remotely viable idea for providing reliable thrust in the vacuum of space – an essential requirement for efficient space travel.  A review of our best current and theoretical propulsion technologies reveal no other practical technology for interstellar travel [10].

Other phenomena now attributed to zero-point radiation are Van der Waal forces, diamagnetism, the Lamb-Retherford Shift, explanations of the Planck blackbody radiation spectrum, quantum noise, the stability of the ground state of the hydrogen atom from radioactive collapse, spontaneous emission from excited atoms, and recently observed cosmological antigravity [4, 8].

Do or Do Not … There Is No Try

The zero-point field presents vast opportunities for technological advancement.  The realization that zero-point radiation not only interacts with ordinary matter, but is also the very cause of inertia and gravity will soon catalyze a paradigm shift in physics.  Suggesting that zero-point radiation will result in such “sci-fi” technologies as efficient space drives, and inertial and gravitational manipulation may sound naïve.  However, for the first time we have the theoretical basis to consider these and other possibilities.

Our current situation can be likened to that of electromagnetic radiation research in the late 18th century – the basic laws were understood, but no one had yet applied them to build a radio.  As professor Wesson states, “research into the ZPF is justified because it is of fundamental academic importance and of potential importance to technology” [11].   Continued exposure for zero-point theories and additional funding for theoretical research is recommended, as the number of physicists active in this field appears small.  Including zero-point energy as a potential renewable energy source is also recommended.  Especially given today’s global energy concerns, it would be irresponsible for the scientific community to disregard any possible energy solution.

References

1.         Yam, Philip. “Exploiting Zero-Point Energy,”  Scientific American, December 1997.

2.         Boyer, Timothy H. “The Classical Vacuum,” Scientific American, pp. 70-78, August 1985.

3.         “An Introduction to Zero Point Energy,” California Institute for Physics and Astrophysics, May 2002.  Internet Site: http://www.calphysics.org/zpe.html

4.         Millis, Marc G.  “Some Emerging Possibilities,” May 2002.  Internet Site: http://www.grc.nasa.gov/WWW/PAO/html/warp/possible.htm

5.         Haisch, Bernard and Rueda, Alfonso.  “How to Abhor the Void While Loving the Quantum Vacuum,” Mercury Magazine, Vol. 29, No. 5, September 2000

6.         Puthoff, H.E., PhD.  “The Energetic Vacuum: Implications For Energy Research,” Speculations in Science and Technology, vol. 13, no. 4, pp. 247-257, 1990

7.         United States Patent #5590031. “System for converting electromagnetic radiation energy to electrical energy,” Mead, Jr, December 31, 1996.

8.         Valone, Thomas, M.A., P.E. “Understanding Zero Point Energy,” Integrity Research Institute, 1999.  Internet Site: http://users.erols.com/iri/ZPENERGY.html

9.         Glanz, James. “ASTRONOMY: Cosmic Motion Revealed,” Science Maganize, Vol. 282, No.5397, pp. 2156-2157, Dec 1998.

10.       Haisch, Bernard and Rueda, Alfonso. “Prospects for an Interstellar Mission: Hard Technology Limits but Surprising Physics Possibilities,” Mercury Maganize, Vol. 29, No. 4, July/August 2000.

11.       Wesson, Paul S. “Zero-Point Fields, Gravitation, and New Physics,” University of Waterloo.  Internet Site: http://www.calphysics.org/articles/wesson.pdf

Additional Resources:

12.       Stenger, Vic.  “The Phantom of Free Energy,” Skeptical Briefs, 1999.

13.       Haisch, Bernard.  “Brilliant Disguise: Light, Matter and the Zero-Point Field,” Science and Spirit.  Internet Site: http://www.science-spirit.org/articles/articledetail.cfm?article_id=126

14.       Corey, Powell S.  “Unbearable Lightness: A New Theory May Explain Why Objects Tend to Stay Put,” Scientific American, Vol. 270, No. 5, pp. 30-31, 1994

This map is courtesy of Google Insights for Search and Inside Facebook (original screenshots with commentary). The geographical diffusion of an innovation is difficult to predict in itself, but its aggregate effect is captured by growth models like the logistics equation. This specific type of growth is classified as contagious diffusion.

The graph indicates relative search volume, not Facebook members or site traffic. Search volume might correlate better to membership growth than total members because I would guess new members are more likely to search for information about Facebook than current users are.

The map suggests that after an initial surge in search volume in a region, volume drops and then slowly builds again (California is a good example). This is just Google normalizing the data for total search volume; the Insights graph below shows only growth in California.

Canadian Facebook growth – finished already?

Various mathematical models exist for explaining population growth. The logistic function is a natural model to apply here. It describes a system where the population rate of growth is proportional to:

1. the current population (facebook members), and
2. the remaining resources (non-members who will eventually join)

Differential form of the logistics equation:

N(t) = number of Facebook users at time t
r = rate of growth
K = saturation level

Initial logistic growth is nearly exponential, which applies if site growth is driven mostly by referrals (one person tells two friends, who each tell two other friends, etc.). Followed by a nearly linear period of rapid growth, growth slows to reach a saturation value. At this point everyone who is willing and able to join has already done so.

The graph below shows the basic logistic function fitted to actual Facebook member data. The best fit results in a saturation value of 11,069,190 members, or 33.0 percent of the Canadian population. It clearly suggests Facebook membership — currently at 32.9 percent — has little remaining growth potential.

Facebook Market Estimation

The 33 percent saturation value represents everyone who is both:

1. technically capable of joining, and
2. sufficiently influenced to create a membership.

The first requirement can be considered a technical coefficient. 78 percent of Canadians are “current internet users” (CIP study), accessing the internet at least once in the past three months. 72 percent of Canadians fall between 13 and 64 years of age, where 13 is the lower cut-off for registering on facebook. The below graph of age distributions show that Facebook has low popularity with the 60 to 64 age group, so 64 will be considered the maximum age of potential  members. The current technical coefficient becomes 78% * 72% = 56.2%.

The second component is a social coefficient. This represents the fraction of the entire population who would like to register, either because they feel it would benefit them (internal motivation), or because of recommendations by friends, family, and media effects (external influence). The social coefficient can be found assuming a national saturation value of 33 percent:

Market Potential = (Technical Coefficient) * (Social Coefficient) * (Population)
(Market Potential) / (Population) = 33% = (56.2%) * (Social Coefficient)
Social Coefficient = 58.7%

A Facebook saturation levels of 33 percent implies a social coefficient of almost 59 percent. This value will rise if Facebook develops a higher perceived-value among non-members (which will happen due to network utility effects), or if external influences increase.

What if everyone wants to join Facebook? A social coefficient of 100 percent means the technical coefficient is the only limitation, and Facebook saturation might occur at 56.3 percent of the Canadian population.

Canadian City Projections

Edmonton, Alberta – a nice city

We can’t be certain that members of a Facebook city network actually live in the stated city, making a meaningful comparison of users to city population difficult. This is especially true with large metropolitan areas and where city boundaries meet. Edmonton makes a good sample city, being a large but isolated city with a greater metropolitan population of 1,081,300.

Growth in Edmonton differs fundamentally from the national growth data. The initial growth rate is very high, and no exponential growth is seen in the data. Exponential growth may have happened prior to the first point (April 24, 2007), however the inflection point — the point where accelerating growth becomes decelerating growth — also happened before the first data point. Consequently the growth is not S-shaped, and a logistics function cannot model it.

Instead we’ll use a model where growth rate is proportional to:

1. a constant value, and
2. the remaining resources (non-members who will eventually join)

Differential form of simplified NUI model:

N(t) = number of Facebook users at time t
a = rate of growth
K = saturation level

This is actually a special case of the Bass model for diffusion of innovations, and it fits the available data very well. The significance is that the member-proportional growth term r which causes initial exponential growth represents word-of-mouth effects, something seen when a product or service is spread predominantly by personal referrals and recommendations through existing social channels, as we might expect in the case of Facebook. Replacing this effect with a fixed-rate growth term (a) means that external influences dominate the growth. External influences typically models advertising; the more advertising, the higher the growth rate a. But it can also reflect “buzz” in a population, where everyone “knows” about something because of multiple rapid and pervasive communication channels. This model suggests that Facebooks’s rapid growth in Edmonton may have been due more to buzz (since Facebook hasn’t engaged in traditional advertising) than to interpersonal social interaction.

The Bass diffusion model also helps us predict Facebook saturation. The best-fit curve has a steady-state value equal to 55 percent of Edmonton’s population.

Halifax, Nova Scotia – most penetration, rapid growth

Of the 23 Canadian cities examined, Halifax leads the pack in Facebook penetration. 71 percent of the population appears to belong to the Halifax network, and its average population-adjusted growth rate was second-highest (slightly behind the smaller city of Kelowna, B.C.).

71 percent penetration seems impossibly high. Halifax’s age distribution leans slightly younger than the national average, with 74 percent between 13 and 64. Therefore the opt-in rate (“social coefficient”) is 96 percent (compared to the national 58.7 percent) assuming every resident has internet access.

The Bass model predicts that 85 of the population will eventually become members. This would require every resident age 10 to 75 to join.

Toronto, Ontario – biggest network

Toronto is currently the largest Canadian city network. The Greater Toronto Area encompasses several city networks, so the difficulties with matching members with their actual cities of residence are particularly bad here.

Because the earliest data point was already at half a million members, it’s possible a strong exponential growth occurred prior to that time. A different function that can model exponential growth was applied to test that theory. The resulting, albeit brief, “exponential” growth is seen in the graph at the lowest membership levels.

The modified logistics function (with exponent q) is commonly called the Non-Uniform Influence model (NUI). For 0 < q < 1 it represents a variable word-of-mouth effect; one which is important at first, but diminishes as member-base grows. Here, q = 1/5

N(t) = number of Facebook users at time t
r = rate of growth
q = growth exponent
K = saturation level

Although Model 1 (Bass) fits the available data better, both models predict the same saturation level of 30 percent.

Montreal, Quebec – untapped potential

For its size, Montreal had far slower initial growth than any other examined city. Early growth exhibits clear acceleration, suggesting that word-of-mouth referrals played a bigger role than in other cities. Buzz may have been less, possibly because the French media gave less Facebook coverage than English media.

Montreal is currently near its peak Facebook growth rate. Despite Toronto having 50 percent greater population, the model predicts Montreal will become Canada’s largest city network by July 12, 2009.

Provincial Penetration

Could some provinces be far ahead of others in Facebook adoption? Since provincial data should be more reliable than city data (less ambiguity regarding networks borders), these trailblazing provinces could be a strong indicator of where the country is heading.

Yukon is clearly in the lead, with 67.5 percent of its 31,530 population having facebook profiles. While examining the possible reasons for this are beyond the scope of this casual analysis, we can rule out Yukon’s age distribution as a factor. While 76.5 percent fall between 13 and 64 (higher than the national average of 72), that distribution is heavily skewed to the right.

On the other end is Quebec with only 21.5 percent penetration. If Quebec follows Montreal, this French province will be a significant growth market within Canada. One barrier may be the 15 percent gap in internet access between English-speaking and French-speaking Canadians. Furthermore, a 2007 study concludes that social networking sites in general have a greater appeal for English-speaking Canadians (43%) than for French-speaking Canadians (24%).

Conclusions

Using a logistics model applied to limited data, the Canadian Facebook saturation level was found to be 33 percent. However this data is a superposition of all city data; when cities were examined individually a saturation level above 50 percent was common. Three provinces were found to have current penetrations greater than 40 percent, with Yukon at 67.5 percent. This raises the possibility that national saturation could eventually reach such levels.

Quebec was found to have a very low penetration, but strong growth potential. Despite a smaller population, Montreal should surpass Toronto as the largest network by the summer of 2009.

About the Data

Facebook doesn’t publish membership numbers on the city or provincial level, so the data in this article was culled from various other sources. Because of the uncertainty of the data (low resolution, network counts versus facebook.com/advertising numbers) this casual analysis focuses more on trends than absolute numbers.

Historic provincial data: http://www.canadianmarketingblog.com/archives/2008/02/facebook_stats_primer.html
Historic city data: http://www.thoughtballoons.net/index.php/2008/04/28/one-year-look-facebook-growth-canada/
Historic Canadian data: http://blog.facebook.com/blog.php?post=2398302130
http://themeaningofweb.com/facebook-user-profile-canada-2008/
All current data: http://www.facebook.com/advertising
Population data: Wikipedia

Upcoming related articles:

• The social network adoption curve
• What’s powering your network: network utility functions

• How fast can my website grow?
• How long will it take to make good money on traffic?
• What are the most important factors for website traffic growth?
• How much should I spend on website advertising?

Over my next few posts I’ll develop a practical method for modeling website traffic that can answer all of those questions, and more!

The web is barren of information on traffic prediction, maybe because it’s so challenging. The main problems are:

• It’s difficult to model the qualitative aspects of a site: quality of content, site appearance, navigation, domain name, etc.
• Visitors can arrive in different ways and for different reasons
• Small inputs can have a large effect (’digg effect‘, viral content, etc.)

The number of unknown and unquantifiable variables makes accurate prediction impossible, especially in a site’s early life. But there are still benefits for trying, including:

• Insight regarding important parameters for site growth (should I advertise more, focus on loyalty, or encourage referrals?)
• Rapidly testing ‘what if’ scenarios (what if conversion rate is half the expected value?)
• Planning infrastructure (when will I approach my bandwidth limit?)
• Something to show investors

The Easy Way

Probably the easiest way to predict growth of a new website is to look at other sites. Find one that offers a similar product/service in the same market, and see how their traffic has grown (try Alexa or Google Trends for websites). For many small sites (ecommerce, online directories, blogs, etc.) it’s reasonable to assume that if you do what they did, you could get similar results. If you know what they’ve done in the way of advertising and link-building you’ll know how much effort is required to approach their traffic level.

This approach takes little thought and no math, but has two drawbacks:

• There may not be a comparable website
• It doesn’t help you understand the growth

In Part 2 I’ll review basic growth models and how to extrapolate your existing traffic!

This was done, and by late summer the new lawn was laced with pathways of trodden grass, connecting building-to-building and building to outside. “The paths followed the most efficient line between the points of connection, turned easy curves rather than right angles, and were sized according to traffic flow. In the fall, the architect simply paved in the pathways. Not only did the pathways have a design beauty, but they responded directly to user needs.” (from mindpower)

Isn’t this a elegant organic design philosophy? Can we program applications that respond so naturally to the users’ needs?

I don’t think picking a ‘great’ name is so important; the real meaning of your name will be crafted by your branding efforts. But there are a few show-stoppers to avoid, especially if your company will live mostly online. In order of importance, some naming considerations to mull over:

1. Brandable. Before building a brand, you need to know you can own it. Without a trademark you have little claim to the brand you build, but in my experience this is often overlooked by web entrepreneurs. Because it is a bit costly (roughly $1500 USD for a US or Canadian application, depending who you see, and much cheaper if you brave it yourself) you could delay the application until you actually launch. What cannot be delayed is doing a thoughral trademark search in the jurisdictions you plan to do business. Make sure your name is different enough (not ‘confusingly similar’) with other trademarks in your proposed class(es). Start your US search here,  your Canadian search here, and your UK search here. Remember that common words aren’t easily trademarkable (the process would be harder, and enforcing your trademark rights would be difficult).

2. Available. You need that domain! You can see what’s available and some of what’s for sale here at godaddy. Your name should also be available in the mind of your customers, so you might want to avoid certain common words which already have a strong meaning.  Existing names may have negative associations by some population segments, cultures, or languages. If foreign-language traffic will be crucial, consider running the name past native speakers.

3.  Short and Simple. For dealing with search engines and typing URLs, its very important people can spell your name. Avoid tricky spellings (silent letters, words foreign to your market, misspellings). The reason domains with just a single hyphen are worth much less than their non-hyphenated siblings is because they’re harder to explain (”that’s ‘youtube’ with a minus sign, between the you, and the tube”). Sites like del.icio.us and Flickr.com have done well despite this, but I think it’s a mistake. Google is a misspelling, but at least it’s an intuitive, phonetic spelling of a word nobody knew anyway. Of the top 25 brands in 2008, the average name length is just over 7 letters.

4. Descriptive — or not. I think this depends heavily on your market and growth plans. If you plan to exist in a niche market, a descriptive name can get your message across quickly, and be memorable. So a search engine for cars could be called carsearch.com, and potential visitors would instantly know if it’s what they’re looking for. Search engines can also give priority to descriptive URLs that contain the search terms, but I wouldn’t weight that too heavily. A danger with descriptive names (aside from sounding cheesy, sometimes) is being pigeon-holed — forever locked to your original product/service. Carsearch.com might have a hard time even extending to motorcycle search. In contrast, abstract names are the raw marble you can chisel your brand image from. A name like Yahoo! could fit nearly any business (except maybe medicine, psychology, law, etc.) and extend its brand a long way. The problem with abstract names is they are born without meaning, so you must work hard to build it. They work best where you’ll have plenty of opportunity for brand reinforcement, like with ads and event sponsorships. Of the top 25 brands, only 4 names describe their product, service, or industry. Instead of using an existing little-known name (maybe derived from Greek mythology, or city names, etc.), consider inventing a new word, which will return no competing results in a search engine. Try this web 2.0 name generator if you’re not feeling creative.

5. Emotional. This is about how the name makes you feel when read or heard. Some words are clearly emotionally-charged (red, safe, smiling, etc.), but I think most ‘neutral’ words also have a subtle feel to them. Combine words to craft your emotional message, or at a minimum avoid negative words.

When I worked at a large engineering consulting firm, every minute of my working day had to be attributed to a current project. I worked on various large projects for different clients throughout the day, but by 5 PM my time had to add to 8.0 hours. If a project had too many hours it would go over budget.

Since there was no category for ‘walking around’, ‘chatting it up’, or even ‘misc work’, it encouraged a productive, task-oriented mindset.

Hey you have projects too? Then why not give the system a whirl… I’ve even attached my blank 2009 calendar to make it easy! It’s based on the calendar template from the good folks at www.vertex42.com. The best time-management tools I’ve found yet is a simple to-do list. This spreadsheet marries a to-do list with a daily scheduler, and a monthly planner.

Quickly jot down the task you're working on (or plan to work on), and block it off with cell colour formatting.

Through 2008 it not only helped me plan (budget), it also showed me the truth about how many hours I actually work in the day (time spent entirely on my priority projects). Although I try to work all day, it turns out I only mange to hit 8 hours (my target) two or three days per week. I don’t feel too bad about it since various studies show that many employees only work 2 to 6 hours in an 8-hour day. And apparnetly actually ‘working at work’ improves productivity also!

In the lower frame is the to-do list. Crossing off tasks (ctrl + 5) gives a fuzzy warm feeling.

Excel file: 2009-calendar

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