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This is a bittersweet moment.
On the one hand, both Shayan and I are stepping down from our day-to-day roles at Zoosk, an amazing company that we worked really hard to build from the ground up for the last 7 years. On the other hand, our star CFO and COO, Kelly Steckelberg, has agreed to step up as our new CEO. This makes me incredibly happy. I cannot think of anyone better fit for the job. I have worked with Kelly for more than 3 years through many strategic decisions. We have long known that she will make a terrific CEO, and she has the vision and execution abilities to take the company to the next level. While Shayan and I are not involved in the day-to-day operations of Zoosk anymore, we’ll continue to support the company and Kelly as advisors and board members.
The mission continues.
Earlier today I was checking out the latest featured success story on our company’s blog. A couple from New Jersey (who met on Zoosk) got engaged while on vacation in Mexico last summer. They’re getting married next summer. They sent us a photo of themselves on a beach, grinning from ear to ear for the camera. Nothing has driven me to make Zoosk succeed like looking at the impact of our work. And our company’s blog is the best place to get a taste of it. Click! An inspiring Miami couple who survived cancer together while dating, and got married. Click! Story of a soldier stationed in Fort Hood, Texas, who met the love of his life on Zoosk. Click! A smiling twenty-something year old from England who says he fell in love the moment he saw a beautiful woman’s smile on Zoosk. That woman is now his wife. Through all these years, through all ups and downs and lefts and rights, all I had to do to remind myself and our team why we came to work every day was to refer to our customers’ stories. No wonder our company’s Facebook page has 14 million fans. And no wonder it’s been surprisingly easy to recruit top talent to join our team. If you have a heart you love our company’s mission.
An incredible team.
I’m so proud of our team! More than 200 strong. Talented. Motivated. Hard working. We couldn’t have asked for better people. With great people comes a great culture. And a company with a great culture creates great products that people love. That’s been our only secret to growth and success. Nothing more, nothing less.
Our baby has grown up. Time to walk on its own.
Shayan and I watched our original idea evolve and grow to become the incredible company that it is today. We worked hard and enjoyed every second of it. But it was time for a professional executive to take over – someone with a proven track record of success building this business and prior companies. Someone we know will be able push the company forward to achieve its next goals. One that, while staying true to our founding mission and values, has the vision and skills to continue improving upon what we’ve created so far.
When Kelly joined us in 2011, she brought a wealth of strategic and operational experience to our team. As the divisional CFO for Cisco’s Consumer Segment and for WebEx, she was well-versed in building large-scale consumer subscription businesses. She also firmly believed in our core mission, becoming a champion for customer-centric decision making. As her role expanded to COO, she took on more areas of responsibility throughout the company from user ops to setting the agenda for marketing. So when we arrived at the right point in our company’s growth path to make a transition, the 3 of us — Kelly, Shayan and I — were all on the same page. Kelly is the right person to lead the company forward through its next phase of growth and development.
It’s not a goodbye. It’s a new chapter.
Given our amazing team, our company’s universally-loved mission and the new CEO that’s carrying the torch, I have no doubt that tomorrow’s Zoosk will be even better than the Zoosk of today. It will lead to many more fulfilling relationships, and innovate within the dating space. This is yet another step forward in a long journey for a company that’s destined for greatness.
Shayan and I feel personally grateful to all those who believed in us… those who joined us, invested in us, or otherwise helped us build the great company that is Zoosk, Inc. We don’t know what we did to deserve it. You have a special place in our hearts.
Thank you all! And here’s to new beginnings…
First, let me say that there are plenty of reasons to avoid starting a consumer internet company (low barrier to entry, shortened founder lifespan due to excessive stress etc.) But there is one major factor that makes it all worth it IMO:
It’s a lot of fun! Running (or working for) a consumer web company is like playing a video game. You press a button on the controller and something positive (or negative) happens in the game almost immediately. You win a video game by constantly pressing the buttons while trying to maximize your good moves and minimize your mistakes. It’s fast-paced and fun!
Now imagine there was a 6-month lag between pressing the controller’s button and seeing your gun fire in a video game. That pretty much describes any other kind of business.
Good or bad, it often amazes me how relatively slowly things change when you look outside consumer internet companies. Watching them compete is particularly amusing. It’s a bit like watching three-toed sloths get into a fist fight.
It’s incredible how often I’ve heard people say that a company “hit the inflection point of an exponential growth curve and took off!” I’m writing this post so that I can give people a URL instead of arguing with them in a loud bar until foam comes out of my mouth.
Dude, an exponential growth curve does NOT have an inflection point! It simply doesn’t. And if a growth curve has an inflection point (in which case it cannot be exponential), you certainly don’t want to hit it.
If what I just said wasn’t readily obvious, please continue reading.
An inflection point is a point at which the second derivative of a curve changes sign. That is, it goes from a bowl to a dome, or vice versa. An exponential growth curve looks like this:
Do you see an inflection point? Me neither. So stop the shenanigans! The only time you are allowed to use “growth curve” and “inflection point” in one sentence is when you’re referring to a market saturation or S-shaped adoption curve, which looks like this:
But reaching the inflection point of this curve isn’t a good thing, is it?
Now what I suspect most people are trying to say when they bring up the inflection point shenanigans is an area of the curve where the growth curve appears to start accelerating (sometimes called the knee of the curve, as shown here).
Ummmmm…. I have more bad news for you guys: An exponential growth curve does NOT have a knee either! It’s all a matter of scale you used to plot the curve. You can make it look like the actual takeoff happened anywhere along the x-axis by manipulating the scale on the y-axis. Depending on your definition, an exponential growth curve is “always hockey-sticking” or “never hockey-sticking”.
In short, no point on an exponential growth curve is special! Your eyes are tricking you!
PS. Ok Let me answer couple of questions I got so that I can put this thing behind me and sleep well tonight :)
Q: Is the point where the derivative of the curve crosses above 1 special?
A: No! The x-axis measures time while the y-axis shows revenue ($) or units sold. Apples and oranges. There is nothing special about the derivative reaching a value of 1 because it depends on the units you chose. Switch units ($1/$1000/1cent for the y-axis and 1 1hour/1day/1month for the x-axis) and you get vastly different points for where the value of the derivative crosses 1.
Q: How about the point where the curve achieves a 45 degree slope?
A: Same as above. Absolutely not! You can make ANY point on the curve have a 45 degree slope by changing the scale on the y-axis!
Q: But visually, there is a point where the curve suddenly slopes up.
A: Yes, I also have a photo on Facebook that shows me holding the moon in my hands. Not real. That takeoff point on the curve is purely a function of the scale used to plot the curve. Choose $1 or $1000 as unit for the y-axis and it gives you completely different “knees”. Check this out for an awesome visualization: http://www.abarry.org/knee.htm.
Like any other startup, we are constantly trying to solve ill-defined complex problems. Sometimes I spend weeks and weeks just trying to figure out what I’m optimizing for, let alone how to do it. Then it hits you. You have that awesome moment of clarity! You draw it on a whiteboard, snap a photo of it with your iPhone. Think about it a bit more later that night. Re-draw it on a piece of junk mail on your kitchen counter. Snap another photo of it. And voila… the next great idea is right there staring at you!!! You run to the office the next day. All excited to get the project started. It’s developed, tested and released to a percentage of users in a sprint or two. I should feel good once it’s launched, right?
Wrong! That first part was actually the best part. The shitty part is about to start. When rubber hits the road, you face one of the following 4 scenarios — sorted from the most likely to the least likely:
Scenario #1– The idea falls flat. Complete failure.
Scenario #2– The idea doesn’t quite work but you still have a tiny sliver of hope — because of an unexpected twist. That is, customers are doing something quite different than what you originally imagined. And that new direction might be slightly net positive.
Scenario #3– The idea doesn’t quite work but you still have hope. This time, you feel like your original hypothesis might still be correct. But you don’t know the correct combination of parameters to make it work. Even worse, you are not sure whether that combination exists.
Scenario #4– The idea works exactly as intended.
#4 happens so rarely that I won’t waste much time on it. And in the unlikely event that it in fact happens, you probably know how to celebrate! Even if some optimization is to be made, believe me, it’s a million times easier to optimize something that is already working.
Scenario #1 is the most likely scenario. Unlike popular belief, this is the easiest scenario to deal with. There is nothing to be done except to deal with your own emotions. If you’re a pro, you know the drill: Go home. Get yourself a glass of scotch on the rocks. Wrap yourself in a blanket (or do whatever you need to do to look miserable). Pity yourself. Sit in the dark and watch some cheesy reality TV show on hulu until you fall sleep. Tomorrow is another day. You’ll get over it. I always have.
Scenarios #2 and #3, however, kill me! You’re not getting much traction on the first version of the product but you can feel that there’s a tiny opening to push your way in a new dimension. The idea didn’t quite work but it’s not dead yet. You just have to continue examining it! Cannot… let… this… thing… go… yet!
This is mentally taxing for two reasons:
1- You don’t know for sure that there’s something there. You just have a hunch. And continuing to push yourself and others based on just a hunch is difficult. “Am I beating a dead horse?” Like I said, it’s a lot easier to work on something that’s already getting traction!
2- Most of the time the problem is so large and there are so many parameters/conditions to play with that it becomes mentally intractable. You cannot possibly test all possible combinations. Even worse, it’s never a smooth continuous function so that you can “hill-climb” your way out of it. You’re walking on a non-continuous surface in a large multidimensional space. You move one parameter slightly in one direction and all of a sudden it changes paradigm. And you will never know if you have fully optimized the system. How would you? What is it that you’re optimizing exactly? Is there a god? Where do babies come from?
Now to make matters worse, add the fact that you cannot simply move on from the problem either (like you would in scenario #1). Scenarios #2 and #3 are where most of the real progress is made. I would say at least 80% of overall forward movement. This is the stuff. So what do I do?
My first thought is to crawl into a ball and cry. But that won’t get me anywhere.
So, over the years, I’ve manufactured some rationale to make me feel better. And when I make myself feel better, I can continue to push in the dark. And more often than not, when we continue to iterate on a half-alive idea, we end up finding a bright solution — to my own surprise most of the time. Here’s what I say to myself. They work on me — sugar pill or not:
– I DON’T have to reach the optimum point!!! Most real-world problems are too big to ever be fully comprehended and solved. You’re not even sure if you’re seeing the full picture, or if you’re solving for the right variables. But here’s the good news: I just need to find a configuration that works slightly better than what we had last month! Who cares whether or not I’m digesting the whole picture? Or how much better it can get? All I should care about is to find ONE configuration that works slightly better than before. Just squeeze a tiny win out of it. Then move to that new point even though it’s a tiny negligible win. The next step will reveal itself to you magically! It always does.
– If we’re hurting our brains trying to scratch the surface of a problem, even if we find some sub-optimal approximate solution, we might still be light years ahead of our competitors. Yes, I cannot fully solve that problem. But over the years, every time we have talked to other companies who are facing similar problems, we were always surprised how much deeper we attempted to dig into those problem than others.
So here’s the key: A problem doesn’t have to be fully understood, dominated, and solved for you to succeed. Just push your brain until it hurts! Other people are probably not pushing themselves that hard. People don’t like hurting their brains!
Today ^DJI closed above 13,000 for the first time since May of 2008. 13,000 is a nice round number and you shouldn’t underestimate the psychological impact of breaking a resistance level like that. But when I took a quick look at the chart, it turned out that the advances of the last few days actually happened on relatively low trading volume (you can visually see this on the volume bar at the bottom of the chart). This is not a good sign. A quick look at RSI and OBV, those short term technical indicators don’t look too good either. In other words, we have a “price-volume divergence”. The price might drop again in short term.
So is this a secular bear market rally (“dead cat bounce”)? My guess is “no”. The support line I drew on this chart (the red line) seems to have held up quite nicely since July of 2009. In other words, every time price dropped down close to that support line, it bounced back up again. The common technical trader wisdom is that if this bouncing action repeats a few times on high volume, you normally end up with a solid reliable support line (an uptrend in this case). So even if DJI drops down a bit, I think it’ll bounce off of that support line and the uptrend will continue. Or maybe I just woke up on my optimistic side this morning, who knows?
PS. And yes, with some stretch of imagination you can see an upside-down head-and-shoulders pattern in early 2009 right before this uptrend started — further confirming a change in trend from downward to upward.
One thing I learned about myself long time ago: I can stay intensely focused on my goals (whatever they might be at that point in my life) but once in a while I fall off a cliff for a short period of time. During those short periods of self-sabotage, I’d negate some — but not all — of what I built in the previous productive period. Then, one morning I wake up to rediscover my productive self again. And the cycle continue. Here’s a chart! :)
This is Part I of a 2-part series. In Part I, I’ll describe my best guess for what might happen to the market in the near future. I’ll probably look like a fool if none of this actually happens… but whatever :) In Part II, I’ll describe my selection of currency, investment instruments, and tactical positions if Part I actually comes true.
My hobby of analyzing market data to speculate its next move has been yielding some interesting results lately. Couple of weeks ago, I decided to step back, re-formulate my macro view and then engage with the market on the short side. Regardless of whether or not my new macro view survives the reality test, it’s a mind-bending exercise to try to predict the outcome of a complex chaotic process. Some might call it a fool’s errand. Time will tell.
What’s the nature of this crisis?
There are at least two forces working simultaneously: 1- Sovereign debt crisis and particularly European debt issue, 2- Global recession caused by our stagnant consumption.
I think sovereign debt will be a big problem down the road but not right now. The cost of servicing US debt is small and we have no problem rolling over our debt for now (I’ll give more specific reasons for this in Part II). Europe is in a much worse shape but even that can be controlled for now by massive money printing by ECB. The second issue, however, will cause a massive exporter-led meltdown soon.
The Crystal Ball
The scenario would look like this:
Prelude: Per my previous post, I strongly believe the total demand from US and other developed nations will be stagnant. We might experience a really long but somewhat mild recession. It won’t be catastrophic. Consumption and income will be flat and unemployment will be high regardless of what Obama and the Fed do.
The First Act: China, however, will be hit really hard by declining exports. The so-called decoupling (Chinese consumption picking up as US consumption vanishes) has clearly not happened. To keep renminbi undervalued and exports up, PBOC over the past decade has been injecting tons of currency into the economy by buying dollar and dollar-denominated assets. The excess liquidity has overheated their economy and created a massive asset bubble, including bubbles in real estate, stocks etc. I know this might sound unbelievable to some but much of China’s growth recently has been driven by this asset bubble and related economic activities such as house construction. After the US housing bubble burst, in the face of declining exports, PBOC further increased the money supply to maintain their bubble and prevent a crash. They have also instructed their banks to relax their lending standards for real estate loans (anyone remembers sub-prime mortgages, liar loans, ARM during the real estate bubble in US?) Furthermore, they have started massive infrastructure construction projects. This has further inflated the bubble. Beijing has one of the most expensive real-estate markets in the world relative to the income of its citizens (WSJ article). The average price of an apartment in Beijing is now worth 57 years of savings by an average worker. The current bubble in China is eerily similar to the US real estate bubble. It is clearly unsustainable, and in my opinion, a bubble of magnificent proportions that is about to pop. And the continued decline in demand from US and the rest of the developed world will, at some point, trigger a spectacular downward spiral.
The Second Act: This will immediately hit resource exporting countries (Brazil, oil exporting countries etc) in a major way because China is their biggest customer. Capital will fly out, their currencies will weaken, followed by recession and unemployment. Their central banks will have to defend their currencies and control rampant inflation by deleveraging (selling their assets to drain liquidity). This will further push them into recession. China’s popping of the bubble will also hit major exporters of capital goods (e.g. industrial machinery) such as Germany and Japan but the impact will be somewhat less pronounced (mild recession maybe). Commodity prices (copper, oil) will drop sharply.
The Final Act: The final act is less pronounced and may or may not happen depending on how badly this hurts the German economy. Germany is currently playing superman in Europe by effectively bailing out the periphery countries. This will be the end of that. In other words, even though for now the European debt crisis can be managed, once China falls, Germany hurts and all bets are off. Some of the GIIPS countries (Greece, Ireland, Italy, Portugal, Spain) might default as the German exports and therefore its ability to absorb a relaxed monetary policy dwindle. If I wanted to guess, I would say that might be the final death blow to Euro. Australia and other more diversified exporter economies will be hit too but the impact will less than the blow to Brazil, Venezuela, and middle eastern oil exporters. The funny thing is, as I’ll explain in Part II, US might come out of this stronger than before!
In summary, this will be an exporter-led crash caused by a popping bubble in China, followed by recession in Brazil and other resource exporting countries. The further you go down the chain, and the less diversified an economy, the harder the impact of this crash. So for example, Brazil will probably be hit harder than China. As a side effect, Germany gets weaker and Euro might fall apart and some of the periphery countries might default on their debt. But like I said, sovereign debt default will not be the original cause, just a potential side effect. And if it happens, it will be limited to highly indebted countries on the peripheries. US will come out of this almost untouched.
Do others agree with this prediction?
Well, obviously if the majority of people agreed with me, the bubble had already burst. But more and more people are getting worried these days. There are the bearish economists who are predicting doom and gloom (Nouriel Roubini a.k.a. Dr. Doom, Garry Shilling etc). Economists from the so called Austrian school of thought mostly believe that this will be a US-led implosion caused by our looming national debt and a weakening dollar. They argue that our Feds two rounds of quantitative easing combined with real-negative interest rates will debase dollar and create inflation in US that will lead to our economic collapse. While there might be some truth to that in the long run, in the short term I think the exact opposite will happen. USD will stage a rally against other currencies (more on this in Part II). Furthermore, I think US debt issue has no part to play in this current crisis.
A few days after I established my short positions, this really interesting memo leaked from Goldman Sachs:
It’s an interesting analysis of the state of China and Europe with supporting research (good summary at Zerohedge). I agree with most of their conclusions but some of their currency bets strike me as really odd. The memo was written before SNB pegged CHF to EUR couple of days ago. But still, even if SNB didn’t actually peg its currency, they should have known that CHF was already stretched.
Coming up next: My view on future currency moves and speculative profit opportunities. (Spoiler: I think USD will stage another strong rally just like it did in 2008. Brazil’s stocks and Chinese REITs might do a massive correction.) Now only if I find some free time to actually write it all up…
Disclaimer: This post is a summary of my current and near-future positions in the market. I’m not a financial adviser or an expert and this is not meant to guide anyone’s investment decisions. This post is highly speculative and risky. You should not treat any opinion expressed here as an inducement to make a particular investment or follow a particular strategy, but only as an expression of my opinion.
In the past few years, we’ve all seen the impact of technology on jobs: It kills many (average-paying) jobs to create fewer highly-skilled and high-paying new jobs. That is, technology is a net job killer. A few days ago, in a great post titled “The jobless future”, Jeff Jarvis claimed that
Our new economy is shrinking because technology leads to efficiency over growth.
In other words, technology is killing jobs and don’t expect those jobs to come back. I couldn’t agree more. Then Paul Graham of Y Combinator started a great discussion about this on Hacker News by asking the following question:
“why now? Technology has been killing (but not net killing) jobs for centuries. It’s possible that technology could start to net kill jobs. But why now, when it hasn’t in the past?”
And that’s what I’d like to answer here. But first, here’s my take on technology as a job killer.
Create a job, destroy two.
There are two ways that new technology transformations impact incumbents and jobs: 1- By fundamentally destroying value in the sector (think of the disappearing newspaper industry), 2- By offering more labor-efficient ways to provide the same value. I would argue that #1 is actually less relevant to net job loss in the long term because if you don’t have to buy newspapers to get your news fix, that’s more dollars left for you to spend on some other goods or services that create jobs. That is, in the long term, these kinds of disruptions shift jobs around (unless of course that new sector of the economy where you’ll shift your spending to is less labor intensive).
#2, however, is the heart of the issue here. Amazon can provide the same value to me as other brick and mortar retailers (buy my favorite items) in a much more labor efficient way. There isn’t much value destruction here but fewer jobs are needed to provide the same value. If you find this obvious, please skip to the next section to see why I think these job losses are permanent. Otherwise, read the rest of this section for more explanation.
Labor productivity (worker’s real output per man-hour) has been monotonically increasing for many many years. Here’s the labor productivity of the nonfarm sector from the Bureau of Labor Statistics — indexed to 100 for year 2005. You can download the raw data here:
The common wisdom is that this is happening due to technology and outsourcing. Sounds great, we are becoming more effective workers. But that can cut both ways. What if the total output doesn’t grow as rapidly or stays constant? Then fewer workers are needed to create the same output, hence more structural unemployment.
Here’s another way to think about it. As a proxy for output per employee, think of sales or revenue per employee per year. Interestingly, if you look at that metric for large successful companies in the consumer internet sector, it turns out that most of them fall somewhere between $0.5M-$1.5M per head per year. This is amazingly high! Think Zynga ($0.25B quarterly revenue divided by 2000 employees(?) times 4), Amazon ($5.4B quarterly domestic sales divided by 34,000 employees times 4), Google ($9B quarterly revenue divided by 29000 times 4). I’ve been guestimating this metric for various tech startups of different sizes for a while now and I can tell you with certainty that it is trending towards even more efficiency.
So what happens when you have a stagnating total output with a growing and increasingly efficient tech sector? For every dollar that the consumer spends to get something on Amazon.com or buy a tractor on Farmville, a dollar is not spent somewhere else in the economy.
Don’t fool yourself… Stagnating total output in the past few years has essentially made this a zero sum game!
What is the alternative to buying something online? Get in your car or get a taxi and go to the mall (car maintenance, parking garage fee, taxi fare), and then pay your local retailer. All those players are losing your business and they are a lot more labor intensive than, let’s say, Amazon. Take Macy’s, for example.
Depending on which ratio you believe is more relevant, at $5.8B quarterly net sales with 180,000 retail employees, Macy’s is at least 3-5 times more labor intensive than Amazon. So as long as Amazon’s top line is growing at the expense of Macy’s top line, we are losing 3-5 retail jobs for every job that Amazon creates. This is a massive net loss!
And it’s not just ecommerce. That $10 that you spent on Farmville means you have $10 less to spend at your local bowling alley (which is more labor intensive than Zynga). This is happening across many verticals, every day.
Why now? What is different this time?
In a great post, Tom Murphy calculates that economic growth cannot grow at a sustainable exponential rate (say, a fixed percentage every year) because the “physical” sector of the economy (i.e. the part that requires energy to do things, such as transportation, manufacturing etc.) depends on gains in energy efficiency to continue growing. If we stop gaining energy efficiency, “the energy growth rate in any form of technology leads to a thermal reckoning in just a few hundred years (not the tepid global warming, but boiling skin!).” The bad news is that energy efficiency is bound by laws of physics and cannot drop below certain theoretical thresholds. And even worse, in many areas we are already close to these theoretical limits. (If you are a science geek like me, please read the article it’s a fascinating read.)
So the only way for the total economic activities to grow is to grow in the “unphysical” sectors, i.e. those activities that require little energy input. But then he argues:
The important result is that trying to maintain a growth economy in a world of tapering raw energy growth (perhaps accompanied by leveling population) and diminishing gains from efficiency improvements would require the “other” category of activity to eventually dominate the economy. This would mean that an increasingly small fraction of economic activity would depend heavily on energy, so that food production, manufacturing, transportation, etc. would be relegated to economic insignificance. Activities like selling and buying existing houses, financial transactions, innovations (including new ways to move money around), fashion, and psychotherapy will be effectively all that’s left. Consequently, the price of food, energy, and manufacturing would drop to negligible levels relative to the fluffy stuff. And is this realistic—that a vital resource at its physical limit gets arbitrarily cheap? Bizarre.
So how does this relate to permanent job losses? Let me create an imaginary world where economic activities are cleanly divided it into two pieces: physical and unphysical. And let’s assume that there are a fixed number of people in this world who can work in either sector and can easily transition between the two. Yes, in real world there is friction in the labor force. But if the timescale is long enough, shifts will eventually happen in the real world just the way I’ll describe for this imaginary model. The size of each circle shows the size of the total economic activity in that sector.
Now let innovative minds invent mass production, robotic manufacturing, better transportation and energy grids etc. What happens?
Stage 1 – There’s an explosion in the physical sector. As the red circle expands, so does the productivity of each worker in this sector. That is, each worker in the physical sector is generating more value and therefore more wealth. As those workers become richer, they consume more unphysical services. Therefore the unphysical sector grows accordingly. Think of this as the beginning of the industrial revolution. As labor efficiency in the physical sector continues to grow, the unphysical sector grows in response. Some workers migrate from physical sector (which is becoming more labor efficient) to the unphysical sector. Total economic activity is growing really rapidly in both physical and unphysical sectors. This is what we end up with:
Stage 2 – Physical sector is limited by its most important input, energy. As the demand for energy goes up, physical sector relies more heavily on energy efficiency gains to grow. So it grows somewhat slower. In the meantime, it becomes more labor efficient due to technology (and outsourcing in real world.) Still there is huge demand for unphysical services so that sector grows faster than the physical sector. Even though the productivity in the unphysical sector starts to increase thanks to the invention of computing devices, the growth in the demand for those services outpace labor efficiency gains. In summary:
– Physical sector is growing somewhat slower but its continued albeit sluggish growth is allowing the unphysical sector to continue its rapid growth.
– In the physical sector: Labor efficiency gains starts to outpace the growth of the sector. So there is net job loss in this sector.
– In the unphysical sector: Labor efficiency gain is still less than the growth in the sector. So there is net job gain in this sector. More workers migrate from physical to unphysical sector.
And that’s what happened in the last two decades of the 20th century (plus outsourcing which you can lump together with technology because they both cause labor efficiency.)
Stage 3- Growth in the physical sector really slows because energy efficiency gains slow. If you buy the argument that the unphysical sector of the economy is hinged to the physical sector (i.e. you cannot have an economy where only 1% of the economy is physical stuff and the remaining 99% is people selling things to each other or babysitting each other’s kids), that causes the growth in the unphysical sector (which has ballooned to become a big chunk of the economy) to slow down as well. In the meantime, labor efficiency gains continue to increase in this sector of the economy thanks to the Internet. At some point, labor efficiency gain outpaces the growth in the unphysical sector and people become unemployed. This is structural unemployment. This is what has been happening in the past decade.
And that’s what’s different this time. In the past, every time there was a sector where labor productivity outpaced growth to create structural unemployment, we were dealing with a physical sector. That is, we were losing farmers, manufacturing workers, construction workers etc. Those kind of job losses were being offset by a faster growing unphysical sector. In the past decade or so, however, the slowdown in the unphysical sector of the economy (because the unphysical sector is tied to a physical sector which cannot grow forever due to real world limitations and laws of physics) along with the continued growth in labor productivity in this sector has created a situation where we are net losing workers in the unphysical sector of the economy as well. We are talking bank clerks, retail jobs, journalists, paralegals, etc. And you cannot really expect this trend to reverse anytime soon unless there is a huge paradigm shift in the physical sector, e.g. we start populating other planets, which will in turn kickstart another period of fast growth in the unphysical sector and create new jobs.
The physical sector of our total economic activity is bound by laws of physics. Even if you find new sources of inexhaustible energy and invent new technologies, you are still bound by theoretical limits of efficiency (again, please refer to Tom Murphy’s article for further explanation.) As labor productivity increased in this sector in the past, we offset that by creating a fast growing unphysical economy. But now, since unphysical economy is hinged to the physical economy, the growth in that sector has also slowed down and cannot be expected to pick up again (because it is tied to the physical economy and that sector won’t grow at the same pace it was before… ever!). In the meantime, the explosion of computing and the internet has significantly increased the labor productivity in the unphysical sector. And the resulting unemployment is permanent.
Invention of new technologies, new services and industries, or discovery of new sources of energy or other resources will not reverse this trend. In another post, I’ll discuss a few thoughts on how to deal with this.
If you show me one example of a repeatable and successful model for social advertising, I’ll eat my shoes (Non-repeatable one-off success stories don’t count.)
I have spent a good chunk of my time in the past year working with all major social ad networks as both a publisher and an advertiser. Social media marketing has been the main talking point for almost two years now. In virtually every conference and workshop that I’ve attended, social networks, social apps and social advertising companies brag about their ability to “leverage the social graph” to promote products better and more efficiently than is possible on the web. They are also very proud of their ability to “hyper-target” an ad to a very specific customer demographic. Yet, in the same breath they complain about low CPMs (payoff per 1000 impressions of an advertisement.) They will then put the blame for low CPMs on old-school marketing managers in brand companies for not understanding and appreciating this new phenomenon. “It’s just a matter of time,” they’ll claim. On the flip side, if you talk to brands you’ll see a completely different picture. Brands are actually quite aware of the rapid growth of social networks and bring up social media advertising in virtually every internal meeting. They even allocate some play money (or as theycall it: “exploring new marketing channels”) to experiment with this new phenomenon. The problem is, brand advertisement through social media-focused ad networks simply doesn’t pay off. So the experimental budget for social media advertising quickly disappears.
The bottom line is, no one has been able to effectively monetize (or profit from) the traffic on social networks. At least not yet! So the CPMs are low. There are no old-school evil marketing managers sitting in dark rooms plotting against poor publishers. The economy of social advertising simply doesn’t work, period.
As always, the real reason is very simple. A few people have already alluded to it, but the reality is too grim for most social media-focused companies to accept. So they simply deny it and keep repeating the same lame stories. Here’s the naked truth:
There are three general categories of online marketing campaigns: Direct Response Advertising, Branding, and Niche Marketing.
- Direct response advertising yields a low CPM on social networks because the ratio of page views to unique visitors is very high (there are way too many page views per each individual visitor.)
- Brands aren’t really attracted to social applications because of their limited reach and lack of prime advertising zones built into their layout. Except for maybe MySpace, most social networks aren’t that attractive for brand advertisers either for similar reasons.
- Niche marketing doesn’t really work because unlike popular belief, social networks do NOT have the ability to target profitable niches.
Let me dig a little deeper into each category:
Direct Response Marketing: These ads encourage users to take a quantifiable and measurable action, for example, sign up for a subscription service or order a get-rich-quick DVD online. The objective is sales, NOT branding. Go to any Facebook application of your choosing that is running a social ad network. Look at one of the ad units. What do you see? Keep refreshing the page multiple times. See what ads appear. I bet you see the following: IQ Quiz, Crush or Love predictor, Make Cash Quick, Run Your Car on Water etc. Shayan Zadeh wrote about this type of advertising a while ago. The fact of the matter is, the majority of revenue from social advertising comes from Direct Response Marketing. I know mobile offers alone generate 70% of advertising revenues for Facebook applications. Overall, I estimate at least 80% to 85% of the overall revenue of Facebook applications come from direct response marketing. I don’t know the numbers for Facebook itself, but judging from the frequency of this type of ads showing on Facebook sidebar, I would say at least 60% of Facebook’s revenue comes from such ads. There are two things wrong in this picture:
- a) Direct Response Marketing offers the lowest CPM of all. In fact, most major publishers (such as myspace) with direct sales force, try to sell whatever inventory they have to Brands directly at high CPMs. They then turn to ad networks to fill in their remnant inventory, which may include direct response ad campaigns.
- b) Unlike branding campaigns, direct response marketing works best if the users churn quickly! For example, you see an ad that says “Pay $250 for a kit that will make your car run on water instead of gas”. If you don’t fall for this ad the first time you see it, it is unlikely that you fall for it after seeing it 10 more times. In other words, this type of ads “burn out quickly”! They need fresh eyes. This is one area where social networks’ main strength, stickiness, works against them. There are too many repeat visitors and therefore, the CPM of direct response marketing is low.
To sum up, not only a larger than normal portion of social advertising comes from low quality direct response offers, the CPM of such offers is further downgraded because of the repeat users. Double whammy!
Brand Advertising: The days of spending big money on branding campaigns without measuring results are gone. Budgets are shrinking every day as the economy dives deeper and deeper into the recession. The impact of this is doubly obvious for social publishers:
- Social applications are simply not a good place for brand advertising, period. Brands are looking for prime real estate. The canvas page for social apps is too small. Also, the app canvas is framed by the social network chrome from the top and often one side. To make the matter even worse, most social networks (with the exception of Bebo) show their own ads on the application page.
- Social networks, on the other hand, have some potential for brand advertising because they are sticky. Brands follow the “3 impressions” rule. They need to repeat their message to the same user at least 3 times. Social networks can deliver this. There are a few downsides though. With the exception of Myspace and Bebo, other major social networks such as Facebook have not dedicated prime real estate to brand advertising in their design. Their design principles are too puristic and centered around their own brand. There are also the issues of demographic, reach and target county which I’m not going to dive into.
To sum it up, social apps shouldn’t be hopeful to get a good chunk of brand advertising anytime soon. Social networks, however, could have benefited from this had the economy not shrunk. MySpace’s and Bebo’s homepage advertising (where they skin the homepage for a brand) and Facebook’s branded gift campaigns are the only good example of branding on social networks that come to my mind. Too little for the size of this market!
Niche Marketing: This is really surprising. All major social networks that I’ve worked with drop the ball on this. Have you tried to create ads targeted towards the African American population using Facebook Social Ads? I have. Facebook doesn’t have ethnicity targeting, can you believe it? Let’s talk about targeting by interests. Go to Facebook Ads. Then create an ad and target it to Male users of any age who are interested in, let’s say, the game Halo (enter the word “Halo” in the keywords section.) Facebook estimates the number of such users to be a mere 116,000 (there are a total of 56 million users from US on Facebook). You have a much much better chance of reaching Halo fans through a video game site. People simply do not fill in the interests section or other parts of their profiles. In fact, I can dedicate a whole article to how Facebook is dropping the ball by not collecting the very essential information that it needs in order to become the leader in niche marketing. And Facebook is perhaps the best among all other social networks (that I’ve worke with) in terms of its ad targeting ability. The only rather useful targeting on Facebook Ads is across the age dimension (Have you seen the ads for the 30+ dating site?) But even that is rather limiting because most Facebook users do not enter their year of birth. Zoosk is one of the very few large social applications that make it mandatory for users to enter their age and ethnicity. It will allow us to do niche marketing in ways that no one else has done before.
In sum, social media marketing is an empty promise in its current form. Yes, you could potentially do creative things by leveraging the social graph (or so I’ve heard, I still have to see a solid success story.) But this alone will not compensate for all the negative factors that I mentioned above. Add a shrinking GDP to the mix, and you are guaranteed to see an underwhelming performance for social media-focused ad companies for years to come.