He takes social scientist Scott Page’s diversity prediction theorem (collective error = average individual error – prediction diversity) a step further to identify the three conditions which must be in place to know when crowds will predict well: diversity, aggregation and incentives:
Each condition clicks into the equation. Diversity reduces the collective error. Aggregation assures that the market considers everyone’s information. Incentives help reduce individual errors by encouraging people to participate only when they think they have an insight.
If you think about it, this is one of the core ways we derive value from the web. Consider:
- The most interesting social areas of the web (especially but not exclusively horizontal networks) have diverse userbases.
- Popular platforms aggregate by design – or if they don’t – external parties are building technologies on top of them to allow for easy aggregation (think TweetMeme for Twitter, Technorati for blogs, Google News for news, etc).
- There are multiple incentives for participation – either personal branding, a passion for the subject matter or desire to build permission with an audience.
The web brings diversity, aggregation and incentives together in a way that is instantly accessible. But what exactly does this allow for as a marketer, an artist a business or anyone else looking to spread their ideas?
Simple: it allows you to form a basis for what will succeed tomorrow based on market data that exists today. I’m not saying you can predict the future with 100% accuracy – that would be impossible. But you can get close in cases where the problem is complex and specific rules cannot solve it.
This is a key for developing successful media, marketing or PR: use the larger patterns in the noise to your advantage. In a world where all media are marketers, and all marketers are media (there’s far too much choice for it to be any other way) gaining an edge against competitors is necessary. Attention is finite. And, the crowd may be more powerful than your own intuition as a predictor of where attention will flow in the social web.
Specific advice for leveraging networks where diversity, aggregation and incentives are present:
For those engaged with content marketing or creating media that will resonate: research established networks to form the basis of what the most popular content will be. You can discover content archetypes that work and use them to your advantage.
A quick example – by doing a search of 204,096 technology-related stories on the network Digg (a place where diversity, aggregation and incentives live) we can see that the top 5 most popular stories on the network have to do with either breaking news or product announcements/scoops. Any expert in technology media could have told me that. But I didn’t need them when I have open access to a network of technology geeks. The data is at our fingertips:
Defining a messaging strategy: look at the messaging/tone/style that resonates highest and let that form the basis of your messaging. This needs to be just one element of your larger audience acquisition strategy.
For an example of this, look no further than the icanhascheezburger network. They found a messaging strategy that sticks and used it to create additional, similar networks. TechCrunch reports on the efficacy of this:
We all know about Cheezburger, which surpassed 1 billion page views last month. But FAIL blog went from zero to 10 million page views-per-month in just 90 days, and the recently launched ThereIFixedIt.com has matched that pace.
It’s important to point out that icanhazcheezburger was an almost completely unoriginal idea. They ripped it off from the (relatively) underground message board culture of previous years. Yet all of their sites follow similar messaging strategies, and for it they are successful: they found a formula that worked and stuck with it. The formula was what the crowd reacted to, and they knew it.
Creating the next hit product: you can leverage networks where diversity, aggregation and incentives are present to quietly discover the next hit product. When we conducted the java beta test of more than 1,500 bloggers one of the items noticed was the most common response to the question of “if you could invent a new coffee flavor, what would it be” – was an extra bold, highly caffeinated blend. This was useful data to create a new product based on the feedback of a diverse audience with aggregated data and an incentive involved.
Conclusion
It’s not that you can’t come up with an original idea as a creative individual that will be successful: you can. But if you are able to conduct research in an area where diversity, aggregation and incentives are present you may able to discover valuable data that will be predictive of whether your idea will be successful or not. It could either support your decision or help you rethink it – but either way, leveraging crowds as predictors of outcome is now possible for everyone.