hysiologic\u00f9l responses Heart rate pulse Breathing Skin secretions Muscle

Hysiologicùl responses heart rate pulse breathing

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¢¢¬hysiologicùl responses– Heart rate, pulse– Breathing– Skin secretions– Muscle activity– Brain activity (EEG)
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­·teve gffprug:'on’tsrr|ùkesrr|eºÄhink,¥¯ocket­·urgerysrr|ùdeGùsy• Cheap alternative to traditional modes of testing• Test• Test early, test late, test in the middle• Don’t focus too much on demographics (“Recruit loosely and grade on a curve”)– don’t design just for your target audience³mcS±N´µµXc
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!hoosing which technique to useAdvantages of A/B testing:it measures theactual behaviorof your customers under real-world conditions. You canconfidently conclude that if version B sells more than version A, then version B is the designyou should show all users in the future.It canmeasure very small performance differenceswith high statistical significance becauseyou can throw boatloads of traffic at each design.It canresolve trade-offsbetween conflicting guidelines or qualitative usability findings bydetermining which one carries the most weight under the circumstances.It'scheap: once you've created the two design alternatives (or the one innovation to testagainst your current design), you simply put both of them on the server and employ a tiny bit ofsoftware to randomly serve each new user one version or the other.
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!hoosing which technique to useDisadvantages of A/B testing:A/B testing canonly be used for projects that have one clear, all-important goal, that's to say a single KPI (keyperformance indicator). Furthermore, this goal must bemeasurable by computer, by counting simple user actions.Examples of measurable actions include:A/B testing is that itonly works for fully implemented designs. It's cheap to test a design^T]SGI XNc`Y˺b_X da˳Z_\U E]SH a^Wda˳Z]S]SXN]SLˮbut we all know that implementation can take a long time. Before you can expose it to real customers on your livewebsite, you must fully debug an experimental design. A/B testing is thus suitable for only a very small number ofideas.The biggest problem with A/B testing isthat you don't knowaRcyou get the measured results.You're not observingthe users or listening in on their thoughts. All you know is that, statistically, more people performed a certain actionwith design A than with design B. Sure, this supports the launch of design A, but it doesn't help you move ahead withother design decisions.Worst of all, A/B testingprovides data only on the element you're testing.It's not an open-ended method like usertesting, where users often reveal stumbling blocks you never would have expected. It's common, for example, todiscover problems related totrust, where users simply don't want to do business with you because your siteundermines your credibility.
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