The Coming Economics of Big Data

by Josh Patterson ~ June 23rd, 2008. Filed under: Business, Data Portability, Linked Data.

True free and open data interop is not bad, its different. The walled gardens of Big Data (yahoo, google, facebook, etc) will not work long term because the terms they are currently pushing for 3rd party usage of your data are designed to artificially control your behavior. These artificial barriers will not hold long term and are losing strategies as there are cracks in the walls of the garden already. The economic model of linked web data will shift, but in ways that have been historically observed and we will adapt our business models likewise.

Forcing artificial constraints on a market tends not to be a winning strategy when the barriers to entry are low, especially in a market where change is right around the corner. Some of the information that has come out of Big Data generally wants users to be able to have access to their data via third parties, but only in very limited conditions. I would classify these limitations as “artificial constraints” simply because you wouldn’t accept using Quicken if you could not export your financial data in a file, and you certainly wouldn’t accept any desktop application’s constraint that limited where you could use the data once it was exported. The reason a user will not accept these conditions from Quicken is because the expectations for a desktop application at this point at set at a level such that if a desktop application were to impose such limitations the user would simply find an passable alternative. The current reasoning (read: excuse) for these limitations is that they say they need to make sure they can protect your data for you. Isnt that what OAuth does? We also have to take into account that user expectations for the web with regard to user data rights are very low right now, but that can quickly change.

Generally passable alternatives aren’t available in very new markets or markets that have a very high barrier to entry. At this point with LAMP stacks, open source, and a highly decentralized nature, the internet has a very low barrier to entry which is one of the things that makes it one of the most continuously innovative platforms possibly of all time. Given this fact, passable alternatives to Big Data are prevalent across the internet and any undue restriction on data usage will result in users trending towards more open alternatives that will allow their data to be completely inter operable with other third party applications.

As I mentioned before, the music industry has long made a living off of forcing artificially constructed constraints on the record industry, and now as the mechanics of distribution radically change, they are falling apart. Trent Reznor is a prime example of how the music industry is evolving due to changing conditions. Reznor has taken the middle man out of the equation and is simply giving his CDs away for free or whatever price the fan decides that the music is worth. This is made possible by the mechanics of media distribution via the internet, which created massive shifts in how media could get from publishers to consumers. As market conditions and mechanics shift, some previously held positions and strategies began to crack, shift, and dissolve — just as when the internet began to become entrenched in our culture, the hold the recording industry had on artists and consumers alike began to slip and crumble.

The so called “freeconomics“, or the economics of free, is another example where a market had some established norms and then a company came in with a “free” product that others were charging for one some level. A very specific example of this is when gmail was introduced (for free) which posed a severe threat to Yahoo’s entrenched web email brand. Gmail was made free with a lot more storage capacity and Yahoo was forced to respond or face the growing trend of user migration towards the best value for their data, which was gmail. The customer wins when this happens because it forces companies to dig deep down and find new and innovative ways to bring their product to market for the least price.

A long standing tenant in business is that in a truly competitive market profit tends towards zero because any entity that tries to push an unbalanced value to price ratio will be looking at a negative trend in market growth numbers. I say profit “tends” toward zero, but it doesn’t quite reach zero because companies have to be able to stay in the black at least part of the time to keep cash flow positive and shareholders happy. In the case of Gmail, google simply could afford to give that much product away for “free” because it was offsetting its losses twofold; they we’re growing their market share and they were moving a lot of ads on their web email application as well. They ended up giving away a little more to the customer in order to drive sales for other business units, raising expectations and setting the bar for the market — this will come into play later on as I discuss how I see the next evolution of the economics of linked data playing out.

Google did not invent the market penetration strategy of giving more to gain market share. There are plenty of other examples where the cost of gaining or maintaining market position is tied to a loss leader type operation; razor blades, copper mines, gas stations, cell phones, coffee shops, restaurants, gaming consoles, printers and so on. As my friend Jonathan Nation put it,

“It really is just a standard deal with a concept of a marketing funnel, you have low profit stuff that gets people in the door and then work on getting them down the funnel to higher commitment & profit items.”

Not all of these business models occurred from day one in their markets, but evolved over many years of cooperation and competition between competing entities. Markets evolve over time, but they are also very subject to even the slightest change in how the basics of the market work. In our present case, the new shift in web data is how data is linked together among disparate sites and applications. As more and more of these sites begin to have an open agreement to simply allow data to interop without any constraints, once again the bar for market expectations will be set and all players in the arena will either adapt or be left behind. Just as in the market shift of free web mail with virtually unlimited storage, as linked data slowly comes online each company will face market share loss if they don’t meet the standards of user expectations.

So this brings us to what I call the New “Free” Shift. Data will become more interlinked, not less, as time goes on, and as more applications like FriendFeed come online, user expectations will shift towards that level of utility. Some say we may have gone too far with free, with customers and their expectations — I disagree. The market will dictate its own rules and any free market will not be ruled by the few. From what I’ve seen in the business world, it simply won’t get any easier to compete that it does today, and more often than not it will be tougher to compete in a market tomorrow. Data will be secure, it will be free to move from app to app, and users will dictate those terms, not Big Data. Our next shift of free will move towards another business model similar to (don’t laugh just yet) — gas stations.

With a gas station, Big Oil is supply, automobile owners provide demand and the gas stations is the middle man. Here the supplier, Big Oil, dominates the middleman and sets their prices as gas stations generally cannot set their own prices for gas but have to stay with whatever price that their supplier dictates. They make little to know money (read: 1 to 2 cents) on selling a gallon of gasoline, interestingly enough. I’m sure your next question is “well, how do they make money then?”, as this doesn’t seem like a very equitable deal for the middle man in this equation. Gas station operators make their money from being along veins of the right kind of traffic, selling the right mix of product at a higher than normal margin. People pay more for bread, milk, and beer because of the convenience of its location relative to where they are going, enough so that if the variable costs are controlled closely enough the operator can make a solid profit on a good unit. So we’ve talked a little about the basics of gas stations, but how does that relate to web data?

With web data, the user is both supplier and consumer of data, they don’t need Big Oil Data to provide them with a steady supply. Facebook, yahoo, and google ( in fact, anyone holding linked data) are the data gas stations, which really makes them the middle man in this setup, ironically enough. If we, as a collective, are our own supplier, and we can move our business elsewhere as we see fit, then what power does that really give the middle man long term? Not much. However, we still need someone to be there by the side of the road when we need our data ready to dispense it, and there is still value in that. I think thats the future of web data walled-gardens — as gas stations on the information super highway. As time goes on and consumer expectations with respect to web data rights and usability rise, the artificial constraints surrounding how you can use your own data will fall away and Big Data will be forced to evolve its policies. However, they can still make a large amount of revenue from simply being Super Deluxe Gas Stations, serving ads, and being a place that people feel comfortable leaving their data. If they can do that, then they will be able to serve ads (read: milk, bread, and beer) to those who stop for the convenience of filling up on their data along the information super highway.

Gas stations also make a good metaphor here since we are talking about traffic, but in two different contexts. In both contexts, location is key; in the physical world a gas station needs to be positioned along not only a trafficed route, but one that has the right kind of traffic (ie, “I’m on my way home from work”). Web sites are no different, they need the right kind of traffic as well, since the audience demographics are key. Their physical location may not be relevant, but their virtual positioning, their connectedness via the right type of links relevant to their content is key. This creates their virtual position along the information super highway and can greatly influence success of failure. An example of this is owning the right keyword in AdSense so that google sends your site the most relevant traffic.

I believe that simply holding data will be the next phase of the web data walled garden evolution, as long term they can’t keep the genie in the bottle (sorry, not even google). However, holding data is not a losing strategy, although it will require adjustments. The holder of data can drive traffic towards specific inherently installed internet apps, which will create more pageviews and can create revenue similar to how adwords creates revenue for google — by being the default web application/service provider for that type data (think of how google the default search engine in firefox).

Although this may not sound nearly as rosy to Big Data as having a captive audience, I think history tells us that once the walls crack, you simply won’t fix the dam. Companies like Facebook will have problems keeping their captive audience since the dam already has some cracks. They will face external pressure that another Big Data neighbor might offer less restrictions before them, which would cause them market share loss as well. Internal pressure on Facebook will also occur from mounting user unrest due to rising expectations of data utility, just like AOL did with the growth of the internet eroding away its user base in the mid nineties. AOL survived, but it required a massive overhaul in how they could impose control on their user base.

It remains to be seen how well Big Data can handle the coming challenges to their position, but there is still money to be made with freely moving linked data.

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