Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

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Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213
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Transcript of Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Page 1: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Usage Analysis

March 15 (Ides of March), 2001By Kevin Fox, for SIMS 213

Page 2: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Overview

What is usage analysis?Why perform usage analysis?Understanding your usersTools for usage analysis

Page 3: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

What is Usage Analysis?

Theory One-way window between the designer and

real-world users performing their own tasks.

Practice Gathering and analysis of logfiles and other

data from the actual day-to-day use of a site.

Page 4: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Why Perform Usage Analysis?

Task AnalysisDemographic ProfilingDesign Evaluation

Understanding the user

Page 5: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

UA Task Analysis

Usage statistics and profiles show real users performing their own real tasks.

Logfile analysis can be used to identify these tasks and their relative frequencies.

Page 6: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

UA Task Analysis

Advantages Real users Real environments Real tasks Ideal for iterative design Relatively cheap

Page 7: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

UA Task Analysis

Disadvantages You have to have a real site Difficult to obtain demographic data No ‘thinking aloud’ protocol Guessing at a users real intent (usually, more

on that later) Useful analysis can be difficult

Page 8: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Demographic Profiling

How do needs change based on who the user is?

More on this later

Page 9: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Design Evaluation

How well does your existing site work?Where do users run into problems?

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Between Groups Testing

Divert a portion of real users to a new version of a site (or several possible new versions) and compare the results

Importance of keeping user groups distinct (between groups, as opposed to within groups)

True iterative process, using the real world in the feedback loop.

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UA and Marketing

Marketing is not a bad wordPutting your site into the hands of the

users who need/want it

Page 12: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Measures of success

Money?Usage?Brand Identity?

What is Amazon’s measure of success?

Page 13: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Tracking Marketing Statistics

Where do your users come from?What forms of marketing are most

successful?

Page 14: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

What is Marketing Success?

Banner advertisement clickthrough rates?Comparing use patterns across origins

Targeted vs untargeted advertising (punch the monkey, tricking the user)

In short: All users are not equal

Page 15: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

So let’s get to it!

Kinds of InformationSources of InformationTools for Visualizing Information

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Kinds of Information

Usage pathsLatencyRates of abandonmentViral marketing

Page 17: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Usage Paths

Where do your users go, and how do they get there?

The most obvious navigation might not be the one they use.

Example: Berkeley Paths (http://fury.com/berkeleypaths)

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Latency

How long does a user spend on a page before going to the next page?

Why might this statistic be misleading?

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Rates of Abandonment

Multi-stage tasks run a higher risk of being abandoned before completion

Shopping Cart examplePage-by-page abandonment stats can

help isolate usage problems.True for more complex interactive ‘loops’

as well (eVite example)

Page 20: Usage Analysis March 15 (Ides of March), 2001 By Kevin Fox, for SIMS 213.

Viral Marketing

Viral Marketing is usually in the form of iterative traffic. eVite example

Brief tangent: Analyzing viral marketing

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Sources of Information

Web site log filesSpecialized usability appsExit surveys

NetRaker

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Visualizing Usage Data

Make data approachableBest pattern recognition computer is still

the human brainRecognition tools exist, but the most

useful tools are still those that organize data so our own brains can find patterns

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Tools for Visualizing Data

AnalogRealtime Stat providersWebQuiltVIS VIP

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Analog

Provides: Aggregate data for referrers Most popular page data Ttraffic over time Frequent visitors (IP addresses)

Lacks: Ability to filter one criterion by another. WebTV example

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Realtime Stat Providers

Instant accessRequires preparation on site (usually a

graphic on each page)Doesn’t always work (outages, Browser

issues)Superstats

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WebQuilt

Proxy-based site and usage data acquisition tool

Visualization tool

http://guir.berkeley.edu/projects/webquilt

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Upcoming Assignment

“Between Groups” logfile study