Whether you're launching a new site or evolving an old one, your goal is to predict what users will want. 2 ways to learn what your users want:
watching what users do The most reliable way to learn what your users want is to watch how they currently behave on your site: What features do they use? What products do they look at? What articles do they read? How long do they stay? This is the great advantage of web sites: You can see with great precision how your site is used. (See monitoring & evolving your site, p. 240.) Few industries enjoy this luxury (which is why they rely more heavily on asking users what they want). You can also look outside your own site for insight. Using market research tools like those from Media Metrix or Nielsen NetRatings you can study traffic patterns for other, similar sites. asking users what they think If you're launching a new site or adding a feature unrelated to your current site your traffic logs won't tell you if it's a good idea. So in these cases, you'll want to ask users what they want. Using focus groups, user interviews, or surveys, you can ask users (or people who fit their description) what they think of your proposed idea. Do they need it? Will they use it? Now, if you've already decided to build a particular site (a grocery-delivery service, say), it's essential to talk to users about what they need from it. (See understanding user needs, p. 60.) But if you're still deciding what to do, consumers are a little less helpful.
Focus groups and surveys can help you predict consumer response. But bear in mind: Users don't always do what they say they'll do. They may express interest in sites they'll never use or feign disinterest in those they use often. A real-world example: When you ask city-dwellers why they like urban life, most will mention cultural outlets, like opera or ballet. But let's face it: Most of them have never stepped foot inside an opera house.
Users don't always do what they say they'll do. They may profess a deep interest in features they'll never use. Same goes for web users, who may profess a deep interest in features they'll never use. Maybe they like to think they would use the feature. Maybe they think it's a neat idea for someone to use. Or maybe they're just being polite. Whatever the reason, users are reliably unreliable in predicting their own behavior.
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