least six types of sensors. We are on the cusp of a huge
wave of sensor technology. Sensors will be embedded
in everything, and they will pour out a continuous flood
9. SERVICE DESIGN / SERVICE SCIENCE
Service design and service science refer to the process
of developing and managing services. As hardware
becomes increasingly commoditized, services offer
opportunity for differentiation. A customer’s experience
with a brand may extend across a family of services,
each with a collection of touch points. These touch
points are increasingly networked, and thus customer
behavior may be logged, analyzed, and used to drive
10. SOCIAL MEDIA
Social media refers to media (communications
channels, most often enabled by the Internet) in which
users create most (or all) of the content. Users engage
in conversations with each other—sometimes about
and with businesses that serve them. Participating
in social media and its attendant conversations is a
growing part of managing relations with customers.
Social media are forms of crowd sourcing—or crowd
sourcing from another perspective.
The next generation of computing will assemble vast
stores of data—from a growing array of physical and
virtual sensors. These technical and social changes
will create opportunities for a wide range of companies.
Consumer electronics makers like Apple will monitor
their hardware and supporting services. Network-tools
makers like Cisco will instrument their customers’
networks. Google (and other Web-services providers)
will continue to instrument search and everything you
do with their tools. Health care device makers like
Johnson & Johnson will increasingly offer services to
complement products that continuously monitor your
vital signs. Sports and apparel makers like Nike will also
build biometric sensors into the soles of their shoes and
the fabrics of their clothes, supporting another form of
Apple, Cisco, Google, Johnson & Johnson, Nike,
and others like them will find themselves in essentially
the same business, certainly dealing with the same
customer management, design management, and
information technology management questions. They
will have entered the era of customer-data-driven
tate analysis of the reports. Tools that facilitate
categorization and visualization of data pay for
themselves in short order. Otherwise, time will be
spent telling the bug reporter, “I can’t reproduce
Server-side logging. The simplest and most cost-effective technique is to execute server-side system
logging. Then scripts can be run to collect and analyze the logged data.
The main advantage of this approach is that little
planning is required to generate data because there
are no changes to the device code. In the simplest
case, an IT operator or engineer adds some logging
code (using the existing logging framework) to a
server-side component. These changes are usually low risk to any release. This modification gets
deployed to the main user population at the next
server-side software release.
However, back-end logging alone doesn’t provide
a rich picture of the user experience because many
behavioral issues can be resolved only via data
from the device side.
In addition, tools construction is required to
“extract knowledge from data.” Mike Kuniavasky
gives an overview of both the benefits and issues
with server-side logging [ 13].
Device logging. Logging from the client side is
more complex than logging from the server side,
because device logging has to handle the transmission of state back to the mother ship. In addition,
the organization has to be willing to pay the bandwidth cost required to send back the data.
The simplest code approach is to just add a logging function to each “user event” (such as a key-press). This is analogous to a website “click-stream.”
The UI framework may have a very small number
of places where this logging code could occur. So
the implementation can be both simple and broad.
The downside, of course, is that an enormous
amount of data is generated and transmitted and
most of the data is not germane to the user experience questions at hand.
Fundamentally, this functionality is only useful
for debugging purposes when focused on a small
number of users.
A more complex approach is to log, for the purposes of a targeted experiment, only the data germane to the researcher’s question. This requires
custom code to map between various system states
and the user state. This code can be more complex
because it is integrated into the application logic
[ 13] Kuniavasky,
M., Observing the
User Experience: A
Practitioner’s Guide to
User Research. San
September + October 2009