Tumblr’s Growth May Not Be As Fast As Predicted
Disposition of finding: Negative
Tumblr, Inc. is one of the fastest growing social networks in the world. It’s been included in many of the darlings of social websites, including Facebook, Twitter, LinkedIn and so on. However, I’m not seeing the kind of growth that people are suggesting it is supposed to have.
If you look at Tumblr’s homepage it says “221.5 million blogs” as of the time of this post. That would imply a huge growth rate, and would actually be plausible even though the company is only 8 years old. But there are some concerns here. Firstly, I’m only seeing a growth on the order of thousands per month, not hundreds of thousands or millions per month. Now my sample size might be slightly off, but I doubt it is many orders of magnitude off. At this growth rate I’d expect there to be millions of sites, but not hundreds of millions.
In attempting to fact-check this, a Google search like site:tumblr.com which includes a lot of duplicates seems to turn up only 100 million links. Even if they missed a certain set of poorly linked sites, that still seems extremely low. That said, to be fair, Tumblr does have a feature to point domains at their sites but even counting those domains it still doesn’t equal even one percent of their total claim so it can be discounted as a rounding error.
My guess, based on what I can find, is that their growth rate is at most half as much as claimed, and maybe considerably less. This might be due to the fact that they must remove spammy Tumblr accounts and they may not remove old accounts from the total blog count. It’s unclear, but without a sitemap or a list of all accounts it’s difficult to be certain. It could also be inflated numbers completely devoid of reality, but it’s impossible to know for sure.
Either way, I don’t see exponential growth, but rather a linear growth that would make it less likely to be as dominant as other social networking companies in the future. Typically an exponential growth is required for a large exit, and most executives would be wary of exiting a company that couldn’t demonstrate an exponential growth curve.
Obligatory legal disclaimer.
Insights for ClickBank
ClickBank sees sudden affiliate growth.
Disposition of finding: Positive
I’ve used ClickBank
before as an affiliate program and had never really thought much about it until I happened across some information that shows just how rapidly things are changing.
In just the last month they have grown north of 200%. That’s a huge increase in affiliate links in a relatively short amount of time. It’s difficult to be certain what this means, but it could point to some interesting things.
It is possible that this massive change may be an increase in people moving into affiliate marketing after the new year. It’s also possible that such an increase might be an increase in spam affiliate marketers or individual marketers marketing additional products than they had previously. Either way, the way that ClickBank works, it doesn’t matter much which. This growth ultimately means more links, whether valid or invalid, which means more possibilities for consumer purchases. ClickBank is not penalized much by abusive affiliates unless the publisher stops using ClickBank completely. Typically an increase in links means more money for the affiliates, and therefore more money for ClickBank as a result.
My main concern with OutsideIntel has always been about setting expectations about what we can and cannot see and what sorts of information we think are likely to be found amongst the huge volumes of data I must search through. It’s important to set expectations. OutsideIntel can’t guarantee that there won’t be external factors that are outside of our control or ability to analyze – indeed, that happens all the time. Like when GoPro’s shares tanked more than 10% in a day because their mounts were allegedly related to an F1 driver’s brain injury caused while skiing. OutsideIntel can’t predict risk factors that we can’t see. However, what we have found is that barring external factors the data is very reliable, useful and unique. So using this data in context with other signals is useful when doing buying/selling, for M&A and for competitive analysis. When making a decision, the more useful data you have the better – and that’s what OutsideIntel’s technology provides.
Examples Of Signals We Often Can See/Do Take Into Account (currently)
- Corporate growth/recession
- New product/feature launches
- New/Existing Vendors
- New/Existing Partners
- Customer lists
- Geographic expansion
Examples Of Signals We Often Can’t See/Don’t Take Into Account (currently)
- Consumer sentiment
- Lawsuits, including Copyright/Patents infringement
- Weather/Force mejeure
- Confidential IPOs
- Human Resource issues
- Brick and mortar attributes/sales/P&L
Almost twenty years since I first came up with this market stock intelligence idea, I can now deliver valuable output that gives our investors a unique vision into companies that is otherwise totally invisible, except to the most sophisticated analysis. Rather than having to be an analyst yourself, I’ve made stock tips easy to digest, easy to prioritize and most importantly, actionable. You don’t need a doctorate in computer science to understand OutsideIntel results.
And now for a brief but important note from my lawyer to further set expectations:
The financial research information provided by OutsideIntel is for informational purposes only. It should not be considered legal or financial advice. You should consult with an attorney, financial adviser or other professional to determine what may be best for your individual needs. OutsideIntel does not hold itself out to the public as an investment adviser and does not otherwise act in the capacity of an investment adviser. OutsideIntel is strictly a research publishing firm and falls within the publisher’s exemption of the definition of an “investment adviser” and the information it provides is of a general and regular circulation.
OutsideIntel does not make any guarantee or other promise as to any results that may be obtained from using our content. No one should make any investment decision without first consulting his or her own financial adviser and conducting his or her own research and due diligence. To the maximum extent permitted by law, OutsideIntel disclaims any and all liability in the event any information, commentary, analysis, opinions, advice and/or recommendations prove to be inaccurate, incomplete or unreliable, or result in any investment or other losses.
Years ago, prior to Y2K, I had a meeting with an acquaintance who was a small-time broker in Northern California. He had built a “system” designed to watch fluctuations in stock price. His theory was that if you bet on a small upwards curve followed by a small dip it would naturally go up – like an sine wave of increasing amplitude. Even at the time, I knew his system was nothing more than guesswork, and when Y2K hit a few years later, it hit that broker and his clients extremely hard. Lesson learned.
Even though my broker acquaintance was betting on pure speculation, I sensed that the major reason he was wrong wasn’t that there aren’t discernible patterns, but that he wasn’t actually looking at the data or patterns that mattered. Looking at a graph is good for many things, but using them without context is prone to failure. What if I could provide a lot more context? Or even better, what if I could forgo the boring analysis part on behalf of clients and only deliver context?
For almost two decades, I pondered how I could build something like this, using a unique skill set that I had amassed from a career in computer security, and Internet-scale data. It wasn’t until 2013 that the technology to perform advanced internet analysis became readily available, drive speeds had increased to the point that they were useful for real-time analysis and costs of drive density fell far enough to make this dream a reality. So drawing on decades of Internet, security and business experience, I finally began developing the corporate intelligence tool I had been dreaming about for my entire adult life.
Early on, as I was developing a prototype, I wondered what this company would be – is this company a hedge fund, is it a research tool where clients perform their own research, or is it something else? In a bit of a Field of Dreams moment, I had to wonder if I was building something that anyone would even use. Sure, I knew it was useful, but maybe no one would understand my vision. When I talked to VCs, they said I was on to something and that I should sell my company to a hedge fund – but the multiples were low on a deal like that and the VCs wouldn’t invest (not that I needed the money anyway). The idea was good, just not something they’d invest in, which was great validation but hardly cause for a ticker-tape parade!
When I talked with hedge funds they all agreed that the data was incredible, and many said that I should start my own hedge fund; but having never done it before, that was daunting concept. Alternatively, others said that the data was incredibly useful and that I shouldn’t give it to anyone, lest it become less valuable over time. I saw right away that they were telling me that they wanted the data for themselves. That gave me a total addressable market of one hedge fund – a non-starter. Don’t get me wrong, I would have sold for the right price, but I don’t think we were even in the same ball-park, to continue my Field of Dreams analogy.
Then I talked to several accredited individual investors who also agreed the data was amazing, but the analysis part was daunting for an individual investor who lacked the experience that I had. They recognized that it was useful, but even the more savvy technically competent investors who were shown my prototype analysis engine interface told me, “No one should ever see this interface, it’s just too complex.” Meanwhile, they spent the rest of the meeting looking through the data, doing the same analysis that I would do. So if the data is useful, and people want it, but they can’t understand it, where does that leave my budding prototype, I wondered.
I was left with the next logical choice – build a service that does the hard work for my clients. That is how OutsideIntel was first born. Finding insider quality information from the outside – legally. I was naturally concerned about the legality, but as I probed, I found more and more mounting evidence that what I was doing was simply great research.
At one point I even had an agent of a three letter agency look at my tool and he remarked that it was amazing, asked me to look up some companies for him that were “of interest” and asked me to please make sure that I never gave any of the raw “.gov” or “.mil” information out to any unscrupulous parties – he feared that the data was so good that it verged on national secrecy issues. But the good news is that it’s legal, and for corporate intelligence, hugely useful in lots of cases.
When I had had a chance to improve my prototype after shopping it around, even my Wife remarked how unbelievably scary the data was when I ran it against some companies and found their client list, how they were evolving, which areas they were growing in, and so on. It’s always a good pressure test to get the thumbs up from the Wife. And the best part is that I was just getting started.
However, one thing I worried about a great deal was explaining to people the types of sites that were most well suited to this type of intelligence. I felt a great deal of anxiety about having customers ask me for information on companies that are primarily brick and mortar or stagnant. Even if my technology is sound, the last thing I want to do is let people down and field angry feedback. So I decided to change the whole concept to being a simple, but powerful blog to demonstrate stock and corporate intelligence using a platform of my own design.
This blog will be a place to highlight just what this intelligent system is capable of providing. Eventually, I aim to sell the technology and data to an interested party, but for now, anyone who finds this information of value can get previews into the technology. Down the road, should a financial investor, hedge fund or private investor purchase this technology, I cannot guarantee what this blog will become. But for now, I hope you enjoy OutsideIntel – the corporate stock intelligence platform!
Robert Hansen – OutsideIntel corporate and stock intelligence platform author