In user experience we trust

Nie tak dawno temu, bo w roku 2010 Google oficjalnie pochwaliło się opracowaniem w dwóch frameworków, do mierzenia „doświadczeń użytkownika” w serwiach odwiedzanych przez dużą ilość gości.  W artykule Measuring the User Experience on a Large Scale: User-Centered Metrics for Web Application autorzy piszą o dwóch istotnych obszarach, których mierzenie było dla nich istotne: twardych danych (m.in. ilość odwiedzin, szybkość, zarobki) oraz miękkich (szczęście, zaangażowanie, kończenie z sukcesem zadań itp). Informują też, że stworzone przez nich frameworki, w roku 2010 wykorzystywane były w 20 produktach Google.

Odnośne frameworku PULSE:

The most commonly used large-scale metrics are focused on business or technical aspects of a product, and they (or similar variations) are widely used by many organizations to track overall product health. We call these PULSE metrics: Page views, Uptime, Latency, Seven-day active users (i.e. the number of unique users who used the product at least once in the last week), and Earnings.

These metrics are all extremely important, and are related to user experience – for example, a product that has a lot of outages (low uptime) or is very slow (high latency) is unlikely to attract users. An e-commerce site whose purchasing flow has too many steps is likely to earn less money. A product with an excellent user experience is more likely to see increases in page views and unique users.

Framework HEART:

Based on the shortcomings we saw in PULSE, both for measuring user experience quality, and providing actionable data, we created a complementary metrics framework, HEART: Happiness, Engagement, Adoption, Retention, and Task success. These are categories, from which teams can then define the specific metrics that they will use to track progress towards goals. The Happiness and Task Success categories are generalized from existing user experience metrics: Happiness incorporates satisfaction, and Task Success incorporates both effectiveness and efficiency. Engagement, Adoption, and Retention are new categories, made possible by large-scale behavioral data.

Pełen artykuł źródłowy dla zainteresowanych:  Measuring the User Experience on a Large Scale: User-Centered Metrics for Web Applications”, Kerry Rodden, Hilary Hutchinson, Xin Fu, Proceedings of CHI 2010.

„Products can introduce more complexity over time, but as far as launching and introducing a new product in to the market, its a marketing problem,” Systrom tells Fast Company. „You have to explain everything you do, and people have to understand it, within seconds.”

For Instagram, that meant cutting out the clutter. Systrom refers to Burbn now as a „science experiment,” a way to test „just about everything to figure out what stuck.” That meant experimenting with check-ins, posting photos and videos, adding comments and Like buttons, incorporating game mechanics, and tinkering with a feature called Plans, which related to future check-ins.

„When youre introducing a mobile app, you look around and say, we could be doing 15 different things, but how do we communicate to someone why they would want to download and even sign up for this thing?” Systrom says. „In the mobile context, you need to explain what you do in 30 seconds or less because people move on to the next shiny object. There are so many apps and people are vying for your attention on the go. Its the one context in which youve got lots and lots of other stuff going on. Youre not sitting in front of a computer; youre at a bus stop or in a meeting.”

Źródło: Instagram Founder Kevin Systroms 30-Second Rule for App Success, Fast Company