User participation often more or less follows a 90–9–1 rule:
- 90% of users are lurkers (i.e., read or observe, but don't contribute).
- 9% of users contribute from time to time, but other priorities dominate their time.
- 1% of users participate a lot and account for most contributions
The problem is that the overall system is not representative of average web users. On any given user-participation site, you almost always hear from the same 1% of users, who almost certainly differ from the 90% you never hear from. This can cause trouble for several reasons:
- Customer feedback. If your company looks to Web postings for customer feedback on its products and services, you're getting an unrepresentative sample.
- Reviews. Similarly, if you're a consumer trying to find out which restaurant to patronize or what books to buy, online reviews represent only a tiny minority of the people who have experiences with those products and services.
- Politics. If a party nominates a candidate supported by the "netroots," it will almost certainly lose because such candidates' positions will be too extreme to appeal to mainstream voters. Postings on political blogs come from less than 0.1% of voters, most of whom are hardcore leftists (for Democrats) or rightists (for Republicans).
- Search. Search engine results pages (SERP) are mainly sorted based on how many other sites link to each destination. When 0.1% of users do most of the linking, we risk having search relevance get ever more out of whack with what's useful for the remaining 99.9% of users. Search engines need to rely more on behavioral data gathered across samples that better represent users, which is why they are building internet access services.
- Signal-to-noise ratio. Discussion groups drown in flames and low-quality postings, making it hard to identify the gems. Many users stop reading comments because they don't have time to wade through the swamp of postings from people with little to say.
How to Overcome Participation Inequality
For example, when early adopters promote a technology they are enthusiastic about, we are hearing only from 1% of the online population.
9% of the population occasionally comments that they are interested in that technology but are taking a "wait and see" approach.
90% of the population might actually think that the very same technology is too complicated or unsuitable to match their needs.
IT vendors that sell the aforementioned technology conveniently tout the feedback from the 1% as a solid indication that the market is ready for mass adoption.
This is why technologies that are promoted as game-changers sometimes end up as colossal flops.
- market trends (and, occasionally, history)
- emerging technologies and deep tech
- startups and venture capital
- corporate strategy and business dynamics
- product development and marketing
- finance and (mainly behavioral) economics
- cognitive psychology and neuroscience
- the future of work and career
I occasionally add a personal note to them.
The whole collection is available here.