Mercury's Blog

One of the best things about London is the kinds of one-off opportunities for concerts, art galleries, speakers and the like. Last evening I was able to take advantage of one of those, by going to the opening of John Maeda’s exhibition at the Riflemaker Gallery in London’s SoHo neighborhood.

For those of you not familiar with him, John Maeda is an MIT professor and a world-renowned graphic designer and artist. He wrote a book last year titled “The Laws of Simplicity,” and maintains both a personal website, a studio website and a website associated with his book. The exhibition was intriguing, and the fairly small space was packed with people. I hope to go back when it’s a little less busy.

Going to the exhibition got me to thinking about his book on simplicity (which I HIGHLY recommend), and how the concepts he discusses can be related to the field of prediction markets. Specifically, there is a lot of work to be done in making markets simple.

I believe that a few of his Laws of Simplicity are particularly relevant to prediction markets. The first law strikes home in many contexts: “The simplest way to achieve simplicity is through thoughtful reduction.” Take a look at the prediction markets currently deployed: all of them could use application of this rule. Think about what MP3 players looked like before the iPod came around; the iPod’s interface was stripped down to the bare minimum necessary, and yet even with this simple interface was a very powerful MP3 player. When a user arrives in a market, they should not be distracted by extraneous information. It doesn’t have to disappear completely, but should be pushed far away.

The fourth law, “Knowledge makes everything simpler,” is very important to me. I am on a bit of a mission to help develop prediction market sites that let a very novice user make simple trades, and then grow into an experienced trader as they become more comfortable. Very little is done these days to help traders, and what is there is insufficient. (I plan on expanding on this in a future post.)

The fifth law is “Simplicity and complexity need each other.” Markets and prediction markets are inherently complex when operating efficiently. Just because they are complex doesn’t mean they can’t be made simple, but neither should that complexity be obscured. John discusses this using the concept of rhythm: too much simplicity or too much complexity becomes a droning experience, but a diversity of concepts keeps us excited and interested. This is a more difficult concept, but when a prediction market site is designed the user interface should reflect both the simple and the complex nature of the markets.

The final law is perhaps the most important, and even John Maeda calls it “The One.” The law states: “Simplicity is about subtracting the obvious, and adding the meaningful.” This straightforward statement sums up what we all need to be concerned with when designing markets. Each of us needs to go to the core of what we are trying to do with each market interaction, and focus on that core.

Simplicity isn’t simple, but it is important. As the first line in the book reads, “Simplicity = Sanity.” If prediction markets are a sane place to trade, they will be a popular place to trade.

I’ve recently been thinking more about how Tradesports/InTrade and BetFair approach their versions of prediction markets, and specifically betting markets.

The key difference between Tradesports and BetFair is their psychological approach to betting markets.  What I mean by this is that BetFair approaches the markets from a betting perspective because they compete with “high street” bookmakers, while TradeSports approaches the markets from a financial perspective, presumably to distance themselves as much as possible from being seen as a bookmaker.  This difference defines the interaction throughout a user’s experience.

BetFair

BetFair has positioned itself as competition to the traditional bookmaker in the UK.  They are also currently running an ad campaign promoting their exchange as a place where you can trade competitively against other bettors.  Due to this strategic positioning, the interface on BetFair is based on odds instead of percentages.  (Specifically decimal odds, which are more standard here in Europe but far less so in the US.)  This means they use the terms “Back” and “Lay” instead of Buy & Sell (Bid/Ask).  In the express view of a BetFair market, it simply shows the best Backing odds for each contract in a market.  The full view of the market shows the best three Back and Lay odds for each contract in a market, with a value of how much money can be bet on those odds.

With the difference between Express and Full view, BetFair essentially uses some of the ideas that I’ve discussed previously on this blog.  Namely, that users should be able to interact with the markets according to their skill levels.  Seeing the Back and Lay order books for each contracts could potentially confuse novice traders; the Express view is ideal for simple understanding.  Specifically, it is the same interface that most bettors use at the high street shops.  Instead of betting on Manchester United to win the Premiership at odds of 2/1, they choose to back Manchester United at 3.  (Or really, 3.3 or something like that, as you get better odds than a traditional bookmaker.)

TradeSports/InTrade

TradeSports and InTrade have positioned themselves as a futures market for events.  This has driven much of how the site operates for the user.  Instead of using betting terms such as Back and Lay, they use financial terms like Bid and Ask.  Users on the site purchase or sell event futures contracts, so there the quantity displayed is not a dollar value but a number of contracts traded instead.  Perhaps most importantly, the probability implied by the contract price is explicit.  Users don’t have to convert traditional or decimal odds to determine the probability of an event occurring.  (This is likely why TradeSports is so often quoted in the US, where popular press of betting odds is virtually unheard of compared to the UK and Western Europe.)

Presumably the TradeSports/InTrade approach is setup like it is because it distances them psychologically from being a betting shop, and more like a futures market.  Additionally, some people can more easily understand probabilities than odds, and their markets take advantage of that bias.  Their website is also a bit less elegant and more “market-like,” though that is likely just due to design and implementation issues.  Overall, it allows for very explicit pricing and perhaps has the benefit of encouraging additional trading, as users can sell their contracts that have increased in price for a locked-in profit.

Summary

BetFair and TradeSports/InTrade are two very different ways of approaching a real-money prediction market.  While BetFair has positioned themselves as competition to a standard bookmaker, TradeSports has positioned themselves as a futures market in events.  Both sites offer essentially the same service – a market that allows you to trade with others on the outcome of events.  However, the manner they approach that service can significantly alter the user’s experiences on the site.  Both are interesting and valid approaches, though they cater to very different audiences.

First of all, welcome to the new subscribers of this blog.  If you aren’t a subscriber, it’s very easy to do.  (You can use any RSS reader you like, even Firefox or Safari; just click here.)  Please feel free to comment, or alternately e-mail me with questions you’d like to keep private.

I’ve been thinking about prediction markets recently in terms of their usability.  Alex Kirkland has done some interesting work and research in this space, and I’d recommend his blog if you’re interested in more in-depth analysis.  For a prediction market to be successful, it should be both easy to trade, and easy for traders to do complex operations.  These are two ends of the same scale, and unfortunately, there’s little between them.

Kathy Sierra at Creating Passionate Users talks a lot about user experiences.  One of the things that I’ve picked up from her work is that it’s easy to make something simple for users, and it’s easy to make something powerful for users.  The hard (but key) part is to develop a solution that is easy for beginners to understand and get started with, while also allowing them to gradually discover more and more powerful features and turn them into expert users.  Currently, the prediction market industry does both ends of that spectrum well, but the middle is ill-defined.

Why do I bring this up on a blog that’s focused on using prediction markets in modern business?  Well, it’s because user interface design of prediction markets is really important.  Most people when confronted by the user interface of something like Iowa Electronic Markets (IEM) will simply not trade at all; a reaction like this will certainly hurt the quality of your markets.  However, the market potential and power behind something like the IEM is strong, and your company may want those aspects in its prediction markets solution.  In that case, you’ll simply need to train your employees to use a more complex system, (and likely hold some “fun” markets for them to get used to the ideas and terminology of trading).

Alternately, Inkling is a very easy interface to understand, and this may be your overriding concern.  You likely will need little or no training for employees to use it and understand the concepts.  However, for those employees that can understand the concepts of the trading “book” and limit orders, an interface like Inkling’s may be too basic.  Since most trades and prices are set by a minority of highly active traders, this could prove difficult as they aren’t able to effectively use their more advanced skills.

So where does that leave your organisation?  Well, as always, for a market to be well-designed and therefore useful, it needs to match your company’s culture well.  Is most of your potential trading population too busy to learn trading skills or too scared by complexity?  Or is most of your potential trading population very competitive and math/finance oriented?  Where your organisation falls on that spectrum helps dictate your needs when in comes to choosing a software vendor, but also in the training you may need to make prediction markets successful.

Any of the major software packages could work for any organisation; but good design and user interface is an important element to consider when creating your prediction markets.  You don’t want your employees to not even try the markets because they look complex and don’t understand them, but neither do you want advanced, market-moving traders to get frustrated at getting held back by too-basic interfaces and technology.