Good points, bad points

• March 16, 2011
• 11 notes

A few months ago I went to an amazing pinball machine shop in the sleepy little town of Lyons, Colorado.  After exchanging a Lincoln for a fistful of quarters, I proceeded to some of the more modern machines, tempted by bright lights and guns n’ roses.  After a couple of pretty pathetic games, I decided to check out one of the more vintage cabinets (that this place specialized in).

What struck me immediately was that I was having more fun with the game.  It wasn’t as flashy, the mechanics of the machine were looser than the newer cabinets.  But I was having more fun because I knew when and why I was scoring points, which allowed me to understand how the game was working.  With the newest cabinets, you just score a ton of arbitrary points, but for the casual player like me, I didn’t really understand what those points meant, how I was getting them, or what I could do to score more.  It all just kind of happened, until I slipped up and lost.  With the older games, the scoring was so simple (and less frequent), and so reactive to what your direct actions in the game.  This made it more fun, because I knew what the points meant and a more tangible idea of how to get more.

This all reminds me of the current trend of just assigning points to everything you do, even though these points are largely not connected to anything of value, or anything you really care about.  Like the new pinball machines, these points are just noise.  The way to fix this problem, is to have an interesting system of how and why points are scored, and then presenting that feedback in a clear way to the player.  

The old and new versions of foursquare are a great example of this.  In the first version, points *seemed* kind of arbitrary, even though they were attached to specific actions.  In the new version, the scoring is so clever and tied to certain behaviors, it becomes really fun to know that, “hey, I get 3 points because my last check-in was over 300 miles away.”

Points only mean something if the thing they are representing means something.  In order to make those connections between meaningful action and meaningful points, people need to know how they are earning points for certain actions and why.  This is something we need to work on with the first version of Superproof, but it’s something we believe really strongly in.

(photo by McWild)