Recent research: SeatGeek – using data to empower customers and alter industry dynamics

Last week I wrote about The Hipstery, focusing on the concept of using data to create and leverage “blind spots”. This week I’m going to talk about SeatGeek – a relatively new start-up that uses existing data to empower customers, and potentially alter the dynamics of the secondary ticket industry.

What SeatGeek does is gather information from hundreds of different secondary market sites for event tickets, and apply an algorithm to it in order to predict where prices for individual events will go. The company asserts that it is directionally correct about 80% of the time (currently limited to MLB games and music concerts). The value for customers is rather obvious here – if prices are going to go down, you wait; if they’re going to go up, you buy.

How SeatGeek itself will perform is unclear – there are a number of business model challenges and contradictions I discuss in my research paper. But there’s one particularly important long-term implication, which spans industries, that’s worthy of more attention – the role of data in regards to the customer relationships.

In many traditionally B to B to C marketplaces, the Internet (among other things) is allowing the “middle B” to solidify their hold on the customer relationship, and leverage data to become ever-more popular. The challenge for the “first B” in many industries is to gain access to that data for their own competitive advantage. There are a variety of different ways to do this that my research team is currently exploring.

In SeatGeek’s case, professional sports teams, various musicians and others are the event originators – the “first B”. Companies like TicketMaster are the “middle B”. In the long-term, it may well be that SeatGeek (or a company like them) empowers the event originators at the current intermediaries expense. I’d hypothesized we might see the same process / battle play out in, say, the book industry as the Kindle (and other such devices) grow in popularity. This morning I was reading the Economist, and I found the following quote from “a Hulu for Print” quite interesting…

Publishers are irked at the prospect of formatting content for multiple devices with slightly different requirements—a problem that will worsen. They are even more irked at the current market leader, Amazon, which returns as little as 30% of the sale price of a digital magazine to publishers and provides less detail about customers’ reading habits than they would like.

For further reading on SeatGeek on the web, I recommend this, this, and this. An interesting overview of the secondary ticket market is here.

Recent research: The Hipstery – creating and leveraging Johari blind spots

My job as executive editor at nGenera Insight involves doing a lot of research about new business models and start-ups tied to the Web 2.0. Over the next few weeks, I’m going to be sharing a high level overview of some of the work I’ve been doing recently. Today I’m going to start by talking about the story we see emerging from a little company called The Hipstery.

The idea behind The Hipstery is simple. Instead of offering a bunch of t-shirts for customers to pick from, the company invites customers to fill in a survey. They then take these results, apply an “innovative style algorithm technology” to them, and select a t-shirt that seems to suit the customer. Think of it as a way to surprise yourself with a gift.

We’re cautious not to overstate what The Hipstery is actually doing here – the humorous tone of the site makes it appear that the algorithm might be part of a joke. But there’s no reason it need to be. We think the idea behind it points towards an interesting opportunity popping up all over the web.

Without getting into the details of the framework (which is where the Johari Window, among other things, comes in), the idea is to create “blind spot” – things you can no about your customers, but they don’t know about themselves – and capitalize on them. Doing so requires data, and analytical capability. We’ve already seen this happen in online dating – while sites like Facebook offered certain advantages over services like Match.com, it’s eHarmony that captured the blind spot opportunity (and found a business model). If you squint a bit, you can make the argument that The Hipstery model is to Threadless in the clothing industry what eHarmony is to Facebook in online dating.

There’s of course much more to the story than that. But the overall message is that The Hipstery is a very interesting company to check out, and many organizations should consider looking for their own “blind spot” opportunities to exploit.

StickK: I love this idea, partially because I also came up with it

Very early in my career, I was told there are very few new ideas out there – if you’ve thought of it, somebody else probably has as well. What’s rare is for people to actually do something with the idea. So I find it quite amusing when I see people get all upset about somebody “stealing” there idea, when “stealing” is defined as “I wrote / blogged / tweeted about this once, and person or company X has clearly stolen based on all of these things they did which I already thought of.” In some cases, admittedly, the complaint is valid – but in my opinion most are not.

I was reminded of this when I stumbled upon StickK today. I’m always fascinated by online business models where making people pay for something creates a better experience for them than offering it for free. I’ve seen these properties in dating sites, job searches, and a variety of others. Then I got to thinking about how many people have goals they want to acheive, but need an incentive to actually follow through. In turn, what if you set-up a service where people voluntarily offered to cough up some of their money if they failed to achieve a goal they set for themselves? And what if you had most of that money going to charity, so they’d actually not feel that bad about it.

That seems to be exactly what StickK is. I know they didn’t steal it from me – notably because the site started before I’d ever thought of it, and I can’t remember if I ever wrote about the idea anywhere anyway. But even if I had wrote about it, and the company emerged after that, AND I could make a compelling case that my ideas drove the whole thing (again, that’s clearly not the case), I wouldn’t be upset about it anyway. I would have thought “hey, I shared my thought – good for them putting it into action.” And I’d realize that there were probably many, many other people that had thought about it before.

Of course, then when I went to the site, I realized I wouldn’t ACTUALLY pull the trigger on taking part. Anyone have any thoughts on whether this idea is a good one – and how the site is doing?

Seeking out new ideas, and why being open isn’t always better

I do research for a living. A lot of it tends to centre on the Web 2.0. And the Chairman of my research group wrote Wikinomics. So I spend quite a bit of time out looking for new companies and business models, with a particularly keen eye for things that are “opening up”. But to be honest, there are quite a few situations where it becomes obvious that being open isn’t always a great thing.

For example, one easy technique for locating new “lighthouse case study” ideas is searching through various contests that are floating around out there. Two of the more well-publicized ones recently are the TechCrunch 50, and the Mashable Open Web Awards. The first provides a nice list of start-ups to consider, and the various stories swirling around them point to many more. Great resource. I also had high hopes for the Mashable Open Web awards as a pointer towards great case studies. But thus far have been mostly disappointed.

The reason is that I suspect the system is being gamed, and I don’t know what to make of many of the results I’ve seen. For example, I was really interested in “Twitter user of the year”, particularly since there are many, many interesting Twitter users out there. I watched the updating list for a few hours last week. @ivetesangelo proved quite popular. In fact, my rough count indicated @ivetesangelo was getting about 60% of the votes. @sookiebontemps and @tommcfly were also quite popular. I greatly suspect that the system was being gamed. I scanned through a variety of other lists, saw voting patterns that defied all logic (at least in relation to what the contest intended), and moved on.

In some ways it’s not really fair to compare the two directly – but since both are seeking to identify the “best” in a relatively similar space, I think the difference between the two experiences is important. By applying some structure, expertise, and filtering, TechCrunch provides a lot of value to me; by being almost entirely open, the Mashable Web Awards are left open to gaming, and various different interpretations of what’s going on. I have a hunch of some expert panel had narrowed down a list of the best things going on out there (perhaps guided by voter input) and let people work from there, the output would be more interesting – and useful.

I see this kind of thing pop up a lot. In general, I find open to be good – to a point. But there’s a reason things like hierarchies emerged out of self-organizing systems.

Localbacon: improving the customer experience by making them pay

In most cases, getting something for free is preferable to paying for it. But now always. One example I’ve always found intriguing on this front is online dating sites. If you’re (say) a very attractive female, it’s HIGHLY likely that you will be inundated with messages from potential suitors. But by making the suitors pay to send messages, not only is the experience better for the person receiving the messages (less noise), it’s also better for the people that really want to ask her out (and have a chance). And importantly, a real business model is born.

With that in mind, think about most online job sites. The way most operate is to (in relation to the above example)  make the very attractive female pay to post her ad, while allowing any suitor to send her “applications” for free. It sounds rather absurd when you think about it that way, but that’s exactly how most work.

LocalBacon is a new job-search site (profiled at the TechCrunch 50 conference) that’s trying to do it the other way around. Employers can post jobs for free, and applicants must pay something to apply. Now there are a lot of wrinkles to iron out around pricing, and various other interesting features that might be worthy of discussion, but I just want to focus on the simplicity of the general idea. Stop making one customer pay, make the other customer pay, and increase the value for both parties… while perhaps creating a sustainable business model in the process.Nice.

Would love to hear examples of other businesses / industries such an approach could work in…

 

 

Stigmergy, community building, and social media

On Monday my colleague Naumi Haque sent me a link to an interesting article by Professor Francis Heylighen titled “Why is Open Access Development is so successful? Stigmergic organization and the economics of information“. It provides a great overview of open access / self-organizing systems in relation to traditional economic theory, but the part I found most interesting was in relation to the two different types of stigmergy.

I will now admit that I didn’t actually know what that word meant before reading the article. According to Wikipedia, “Stigmergy is a form of self-organization. It produces complex, apparently intelligent structures, without need for any planning, control, or even communication between the agents. As such it supports efficient collaboration between extremely simple agents, who lack any memory, intelligence or even awareness of each other.” More simply, Heylighen says “a process is stigmergic if the work done by one agent provides a stimulus that entices other agents to continue the job.”

You can start seeing the link between stigmergy, community building, and social media from that description. But to highlight the difference between direct and indirect stigmergy, Heylighen used termite and ant examples.

Direct stigmergy: exemplified by termite hill-building, it is the “work-in-progress” itself that directs subsequent contributions.

Indirect stigmergy: exemplified by the way ants create trails of pheremones that direct other ants to food sources. The trails are left as “side effects” of the actual work being performed.

I thought about these differences, and how they might relate to companies in terms of community building and social media strategies. It occurred to me that building a community is primarily driven by direct stigmergy, while the use of social media is the indirect stigmergy that draws people to you.

The reason is simple. In the termite (direct) example, the little critters go around dropping bits of mud randomly, and where the heaps are formed stimulate other termites to add to them – causing them to grow and grow. By definition, the termite can’t add to the heap without being there. So while no centrally controlled plan is needed, the community must already be there. In an organizational context, the company /moderators start by dropping little heaps of information here and there, hopefully others do to, and where the heaps “pile up” emerge as the key focal point.

The challenge (from an organization context) is, obviously, that this approach doesn’t work if you don’t have a critical mass of termites. You can drop all the heaps you want, but if no one else is there, they’re not going to grow. This is where the indirect stigmergy / social media tie comes in. Using platforms like Facebook, Twitter, WordPress, etc., organizations (and early contributors) leave “trails” that direct people back to the (in the ant case) the “food source”.

So it’s obviously a little bit awkward trying to elegantly merge the termite and ant examples together – right now I’d end up with a bunch of ants piling in to eat the Termite hills. But if you squint a bit I think you’ll see what I’m saying. Organizations need to think about direct stigmergy principles in order to build up their own community from within, and indirect stigmergy principles in order to draw people to them. It’s a subtle, but important, distinction.

The Sports Guy, using statistics, and the gambler’s fallacy

Today my favorite writer – The Sports Guy – wrote an excellent column about Bill Belichick’s “reckless” call to go for it on 4th and 2 when his team was up by 6, on their own 28 yard line, with just over 2 minutes left to play. Much of the article goes into great detail on the problems inherent with relying on statistics in such a situation (see: Insane angle #1: Statistically, it was right move). But in Insane angle #2, he can’t help but pull out his own statistics to “justify” why the Pats shouldn’t have gone for it.

Unfortunately, The Sports Guy made an all-too-common mistake while doing so – providing a reminder that however dangerous putting blind trust in statistics can be, the problem is that much worse if you don’t understand them properly.

His argument was simple. Indianapolis had already completed two long touchdown drives in the 4th quarter. By punting, New England would have forced them to do it a third time. So, to “prove” his point, he asked someone to crunch the numbers on “the number of times a team started and completed three touchdown drives in the fourth quarter to erase a double-digit deficit and win an NFL game since 2005.” The answer he found was 4 – it happens less than once per season. He then started banging his head on his desk.

It sure looks like a perfectly reasonable, statistically-based argument, but there are some major flaws. The one I’m going to focus on here (another big one is switching from %s to a raw count of a known rare situation, which is almost always an easy but meaningless thing to do) is tied to what’s called the “Gambler’s fallacy” – the belief that deviations from expected behavior in the past are likely to be evened out by opposite deviations in the future. The common example is coin flips, but I’m going to use a basketball analogy – since that’s the Sports Guy’s favorite sport.

Let’s say your playing the Cleveland Cavaliers, and for no obvious reason whatsoever they run a play to get a three-point shot for Shaquille O’Neal – who has only even attempted one such shot in the last decade or so. The defense is so confused by this that they foul him, and he steps to the line. Even though he’s only a 50% FT shooter, he hits the first two. What are the odds of him hitting the third?

Twitter popularity and Marvel Comics: an interesting difference between follower and list counts

As part of my ongoing research, I’ve been paying close attention to developments around Twitter’s “list” feature (launched in October) – “A great way to organize the people you follow and discover new and interesting accounts.” Yesterday I stumbled upon an interesting finding (that has me scratching my ahead a bit) in relation to follower vs. list counts as a measure of popularity.

One would think that there would be a very high correlation between the two – if a lot of people follow you, you are likely to make a lot of lists. While I haven’t actually run a regression to prove that, as I’ve looked around it generally seems like a fairly safe assumption. But there’s one interesting anomaly I’ve found recently – @Marvel vs. @Agent_M.

@Marvel is “the official Twitter for Marvel Comics, Movies, Games and More.” Agent_M is the “editor for Marvel.com. Writer, blogger, loves tacos, tattoos, comics…” I’ve been watching these two accounts with interest for some time, because the former has about 43 thousand followers, and the latter has about 1.4 million. This would seem to say something important about relative popularity, and it’s interesting when the editor is more widely followed than the content.

But the “list” count tells a slightly different story. @Marvel has been added to 1,467 lists, while @Agent_M has been added to 1,234. So even though Agent_M has 0ver 30 times more followers, his account has been added to fewer lists. Divide lists Marvel is on by total followers you get 3.4%; for Agent_M you get 0.1%. ; Why is that? And what does it mean?

Twitter, and the challenge of innovating while having an open API

I was just reading about the Trouble at Twitter – how U.S. visitors were down 8% in October – on Tech Crunch. The CEO mentions that they’re hoping a “slew” (currently a couple) of new features will help revive growth on the site – such as the retweet button, lists, and geolocation features. It very well might – but it got me thinking about a peculiar competitive position they are in.

For most of the last year, Twitter has done very little innovation directly. But thanks to their open API, that doesn’t mean innovation hasn’t been happening – all kinds of new tools and applications have been constantly emerging. My question is centered around how they’re going to manage this ecosystem, as the company itself starts innovating more. There are more and more data points emerging that indicate, to me, that the line between partners and competitors is blurring.

Coming at it from one side, TechCrunch highlighted in September how StockTwits is growing up and away from Twitter, as they develop their own desktop app. To quote the article, “Yes, StockTwits is slowly breaking away from the service that inspired its name.” What should the company do if StockTwits, slowly but surely, starts to compete with them directly? On the other side, Lists are a step towards Twitter helping users sift through information directly – something TweetDeck already does (in a different, and more advanced, way). If Twitter continues to innovate on this front, what are the competitive implications?

It’s a question I constantly struggle with in our research – and it seems particularly relevant when a company is facing slowing growth (or a decline) in users, before they’ve found a business model. Could the ecosystem implode on itself? Or will they find a way to keep working with each other? What do you do if a current “partner” looks like a future competitor – and what implications does it have for prospective partners / the innovation cycle?

 

Outvesting: A peculiar combination of localism, prosumerism, and capital allocation

Every once in awhile I come across a story that, while interesting, makes absolutely no sense to me. Outvesting, which I discovered through Springwise, is just such a story. What the site has managed to do is raise $5,000 in seed capital, through 100 donations of $50 each, for a yet-unchosen Irish start-up to use. Those that have provided the capital will get to vote on who gets the money. Twitter has been a big part of how they’ve managed to accumulate the funds.

If I stop right there, it sounds like an interesting story of using prosumers to provide (an admittedly small) amount of venture funding, which is clearly targetted at people with a little Irish pride. But where I find it weird is in relation to the term outvesting. As the site clearly defines it, investing is “The act of committing money to a business while expecting income or profit in return.” Outvesting is “The act of committing money to a business while expecting to get nothing in return, other than the satisfaction of giving a leg up to Irish entrepreneurs.”

So the natural question, of course, is what exactly is the benefit of outvesting over investing? Obviously from the perspective of whoever ends up with the money, it’s pretty clear – they get money for free. But is that really a better model? Will it lead to better innovation? After all, the basic premise of investing is that the incentive to earn a positive return leads people to allocate capital to projects they deem most likely to succeed. With that incentive not in place, won’t more capital get wasted if an approach like this scaled at all?

Like I said, I find it interesting – but right now I just don’t quite get it. I’d much rather see a more traditional model here – using Twitter, micro-capital-contributions, etc. to allow people to invest in small, promising start ups. But am I just missing something here?