Chris Anderson's newest book FREE: The Future of a Radical Price received some attention this summer, but I've actually been meditating on principles he laid out three years ago in his blog post, Scaling up is good. Scaling down is even better. In that post he marveled at Google et.al.'s ability to scale down, to run themselves efficiently enough to serve users who generate no revenue at all. Anderson's principles are guidance on approaches to conducting business such that even if only a tiny percentage of ones visitors "convert" into paying customers, by ensuring this small percentage is of a very large number one can still achieve big-time profitability.
My goal with this post is to consider how these ideas might be applied to the domain of Linked Data, and specifically how they pertain to the provision of unique data that adds real value to the greater "Web of Data."
In his blog Anderson gives us four keys to scaling down: Self-service, "Freemium" services, No-frills products and Crowdsourcing...
1. Self-service: give customers all the tools they need to manage their own accounts. It's cheap, convenient, and they'll thank you for it. Control is power, and the person who wants the work done is the one most motivated in seeing that it's done properly.
"Self-service" applies to linked data services in oh-so-many ways! Self- service in this case is not as much about support (see "Crowdsourcing," below) as it is about eliminating any and all intervention customers might need to customize or specialize how services perform for them. In principle, the goal should be to provide users with a flexible API and let them figure it out, with the support of their peers. Ensure that everything is doable from their side, and step out of the way.
The (negative) corollary is this: if you "baby sit" your customers by providing specialized services that require maintenance, then you own it and must eat the cost. By making the specializations a user-side function, then they own it. But they won't be alone; they'll have the support of their community!
2. "Freemium" services: As VC Fred Wilson puts it, "give your service away for free, possibly ad supported but maybe not, acquire a lot of customers very efficiently through word of mouth, referral networks, organic search marketing, etc, then offer premium priced value added services or an enhanced version of your service to your customer base." Free scales down very nicely indeed.
There are any number of ways providers might apply this concept to the linked data world:
| Free Access | Premium Access |
| Restricted vocabulary of assertions | Full access, all assertions |
| Limited query rate | Unlimited query rate |
| Limited query extent | Unlimited query extent |
| Limited data | Unlimited data size |
| Read-only | Term upload capability |
| Narrow reuse rights | Broad reuse rights | Community support | Private/ dedicated support |
| ... | ... |
3. No-frills products: Some may come for the low cost, others for the simplicity. But increasingly consumers are sophisticated enough to know that they don't need, or want to pay for premium brands and unnecessary features. It's classic market segmentation, with most of the growth coming at the bottom.
In the linked data world, achieving "no frills" would seem easy because by definition it is only about the data! For linked data a "frill" is added data complexity that serves no purpose or detracts from the utility of the service. Avoid any temptation to "add value" on behalf of customers, such as merging your core graph with others in an attempt to "make it easy" for them. Providers should also avoid "pruning" graphs, except in the case of automated filtering in order to differentiate between Freemium and Premium services.
4. Crowdsourcing: From Amazon reviews to eBay listings, letting the customers do the work of building the service is the best way to expand a company far beyond what employees could do on their own.
By now it is not only obvious, but imperative that providers should develop communities around their services. Usually communities are about evangelism, and this is certainly true for linked data provides, but increasingly service provides realize well-groomed communities can radically reduce their service costs.
Linked data providers should commit themselves to a minimum of direct support and invest in fostering an active community around their service. Every provider should have a means for members of their community to support each other. Every provider should leverage this community to demonstrate to potential adopters the richness of the support and the inherent value of their dataset.
Finally: In a thought-provoking post Linked Data and the Enterprise: A Two-way Street Paul Miller reminds the skeptical enterprise community that they, not merely their user community, will ultimately benefit from the widespread use of their data, and when developing their linked data strategy they should consider how they can "enhance" the value of the Web of Data, for paying and non-paying users alike:
...[A] viable business model for the data-curating Enterprise might be to expose timely and accurate enrichments to the Linked Data ecosystem; enrichments that customers might pay a premium to access more quickly or in more convenient forms than are available for free...
I've purposely avoiding considering the legal and social issues associated with publishing certain kinds of enterprise data as linked data (see also this), which I'll address in a future post...
Posts
