I wanted to pursue a couple things I mentioned in my last post.
I speculated that customer enthusiasm might be a sufficient factor in making decisions in my P.S. to that post. But I was thinking about it this morning and realized that there are some great counterexamples to that. Apple has a nearly cult-like following in terms of customer satisfaction and yet has never broken through to the mass market. They’ve done okay, of course, but never as more than a fringe industry player. BMW is another good example of a company that elicits great customer satisfaction while serving a niche market. I’m not sure what it means, but it does poke holes in my theory that a great story and customer satisfaction is enough.
For many things, quantitatively and analytically maximizing customer value and throughput is the way to go. Very few of us have brand preferences for things like toothpaste. The different brands are fungible. So the companies can’t rely on building a brand and eliciting customer satisfaction. It’s a numbers game of minimizing product cost and maximizing customer selection. And that _can_ be handled analytically by the tools that Bonabeau describes.
Another great example is Amazon. Every now and then, when you go to the Amazon web page, you’ll get an alternative user interface, where they’ve moved some things around. You go back 15 minutes later and it’s back to normal. What’s up with that? Apparently Amazon occasionally has some new UI ideas that it wants to try. It changes its front page for a while. 10,000 people try it. Then they switch back ten minutes later after they’ve collected enough data. And that’s a large enough sample that you can observe statistically significant effects. I read an article at one point that described how Amazon tested the position of the “one-click ordering” button in various places, and determined that the place where it eventually ended up increased the likelihood of ordering by 1 or 2%. Seems like a minor change. But for their volume of sales, it translates into an enormous amount of money.
That’s sort of what I mean by “Trust, but Verify”. Their UI designers had some thoughts on how to improve the conversion rate. They mocked them up, tested them, got real data, and was able to make an informed decision. Bring the iteration time of finding results down, and you increase performance, and reduce the penalty of making poor decisions. I’ll talk about this more when I finish reading Experimentation Matters.