You Can’t Get There From Here

There are lots of great business ideas that won’t work because YOU CAN’T GET THERE FROM HERE.  Conversely, some great business successes happened because the founders did figure out how to get from here to there.  Two reasons why I’m thinking about how to get from here to there.  If you figure out either one, you’re rich (assuming, of course, that you execute well). If you want, you can skip down to the bottom of this post for the challenges now and skip the rest of my pontificating.

Skype is a great example of here-to-there success.  Lots of us VoIP types said “it’s really gonna be great when everyone has one of our clients because then they’ll all be able to talk to each other free.”  Some communities like Free World Dialup reached group critical mass.  Most communities stayed very small so – according to Metcalfe’s law – the value of their networks was very small.  New users didn’t have sufficient reason to join because there was small chance that they would find anyone else they wanted to talk to in the group.

Skype piggybacked on the download distribution model and caché of Kazaa.  Soon there were a critical mass of people with clients.  “Skype” became a verb and the rest is history.  All because the founders figured out how to get from here to there.

Del.icio.us is another good example.  “Wouldn’t it be great if a bunch of people tagged interesting things so other people could find them.”   Right.  Problem is that the first visitors won’t find anything tagged for them so why should they come.  In fact, tagging has to go on for a while before it is socially useful.  The genius of the del.icio.us founders was to make tagging useful as a way to find stuff you’d run across on the web and might want to find again.  This is useful to the very first visitor.  But, after people tag things for their own use for awhile, then there is a critical mass of tags and the site becomes socially useful.  Network effect takes over.

It’s all about giving the early adopters a reason to adopt – which may not at all be the same reason your product or service will eventually be a great hit.  If you are depending on network effect for value, it’s almost certain that you’re going to need some strategy other than what will eventually make you rich and famous to get there from here.

This is a lot like evolution.  Whatever led up to the evolution of the eye, for example, had to be useful for something other than seeing how exquisite a sunset is.  Could have been – probably was – just a little photosensitivity which was useful for cluing the organism to get in or out of the sun as appropriate. Whatever the predecessor trait was, it wouldn’t have been “adopted” by evolution just because it was going to lead to something better: it had to be immediately useful.  Same thing at every stage of your new business.  Users only do what is immediately useful to them.

The Opportunities

1. Hydrogen cars.  Everybody knows they’re the future of personal transportation.  Save the planet from global warming.  Save us from sending too much money to the unstable Middle East or into the retirement plans of oil execs.  But not very practical to have a hydrogen car if you can’t go somewhere to top off your fuel cell. And you’d be lonelier than the Maytag repairman if you opened the first top-er-off station for fuel cells.  How do we get from here to there? I did post that China might get there first since they have to build a transportation infrastructure from start.  We don’t want that to happen, do we?

2. Dynamic peer clusters. Huh, you ask? These are the groups which are going to replace traditional gatekeepers – book publishers and book critics, for example.  You don’t have time to sample every book in the world.  If you don’t rely on official critics who, in turn, rely on publishers, to be gatekeepers, how do you find new stuff to read with a reasonable chance of success? 

You don’t want just a one-dimensional report of just what’s popular  because, given your tastes, you probably won’t like what’s popular anyway.  Amazon’ll make recommendations based on what you’ve ordered and that’s part of the answer.  What you really need, though, is a service which correlates your taste over many books sampled, liked, and disliked with a group of people who react to many books in the same way.  You need to be clustered with people of similar tastes.  So, when someone in your cluster decides that hackoff.com is the best new novel of the year, you can be pretty sure you’ll like it. And vice versa.

But, in order for clusters to form around books or music (I first typed “records”) or movies or unheard of politicians, in order for the long tail to reach its full magnificent bushiness, a lot of people have to spend some time ranking what they like or dislike without benefiting from an existing critical mass of rankings.

If you figure out a way to get from here to there, if you can get the clusters formed, you will have a goldmine.

Comments

[Jason]

I absolutely agree with the article - nowadays online market is overloaded with projects and services of all kinds. Everyone tries to make something original and basically now everybody offers everything. So PR technologies can't be the main factor of success.

Seth Godin is right and only the buzz created by the users of a particular site can lead to big success of a project. I have an interesting example of getting “from here to there”.

Recently a friend of mine showed me http://www.trustedopinion.com/ The concept of this site is quite interesting. They claim that they have created the first social recommendations engine, the mechanism which is so waited for and talked about on the web. It's algorithm gives users personalized ratings and allows rate just anything they want.

But having such a complicated mechanism they started from very simple category - movies. A lot of people see movies and a lot of people want to know what to see or buy. That's why they invite their friends, then those friends invite their friends and so on. So the network becomes wider and soon enough they’ll have a critical mass of users and will be ready to launch the whole service.

[Jason]

RE: Dynamic clusters

I've been using Netflix for a while, and whenever I send back a DVD I tend to rank it because Netflix uses their own algorithms to create a dynamic list of recommendations.

Every time I rank a movie, their recommendations get better. So I keep ranking movies. That's one way to encourage the user to deposit data.

Another tricker / expensive / easier way to go about it might be to take it the other direction entirely.

What if one company aggregated data from Netflix, Amazon, Last.fm, Pandora, etc., etc., and then both re-supplied the larger data sets to each collector and used the database to create their own recommendation sites.

In that case, I guess "getting here to there" would involve someone persuasive enough to talk the big data collectors into selling their data.

But I'm really just thinking out loud. Or on pixels, as it were.

[vcmc]

I've been using last.fm of late, and I'm finding it's performing pretty well for me as a dynamic peer cluster, via the "neighbors" the system generates for you after a week or two of tracking your listening patterns.

The distinction here is that it only uses an inferred ranking system; the assumption is made that the more you listen to a track, the more you enjoy it. Which - in general - is accurate, but there are always exceptions. I always feel like I'm "poisoning" my account if I listen to a new record a few times to see if it sinks in but I don't end up enjoying it.

I could see a mashup/integration between last.fm and metacritic; sorting metacritic reviewers into peer clusters and adding ranking info to the last.fm neighbor recommendation algorithms.

The data is definitely out there, it's just a matter of pulling it all together.