In-Depth
Getting Personal on the Web
- By John K. Waters
- January 1, 2001
Personalization
promises to teach corporations all they want to learn about customers. But the
fervor for such tools may diminish unless standards and ethical concerns are
faced.
Personalization is hot.
Some observers say it is the model that will make the Internet the top marketing
tool for all types of business. While the personalization concept has been used
for years by direct-mail vendors and telemarketers, the World Wide Web promises
to bring the concept to new levels, providing organizations with data that was
virtually impossible to gather previously.
Companies from all industries,
and of all shapes and sizes, are scrambling to develop Web-based systems that
can personalize interactions with individual customers. The efforts are spreading
through traditional industries, as well as the new so-called "dot.com" businesses.
And software vendors are moving quickly to supply technologies that can "mine"
data for unique characteristics. Suppliers range from start-up Internet firms
to software giant Computer Associates International Inc., Islandia, N.Y., whose
neural network-based
Neugent technology is said
by Chairman and Chief Executive Charles Wang to offer "dynamic personalization.
This can give each customer a different view" of a Web page that is based on
their past activities on a site.
Still, the road to personalization
will not be completely smooth, observers note. The rapid spread of Web personalization
has resulted in a lack of a clear definition of the model, similar to other
concepts, like CASE and EAI, that spread like wildfire through IT shops. If
the trend toward disparate technologies continues, they say, personalization
will cause confusion among information technology operations rather than solve
problems. Some businesses are now looking to standards and industry cooperation
to resolve the issues.
A marketing sea change
Industry observers have
alternately described Web personalization as "the Internet's next big thing,"
"the Holy Grail of e-commerce" and "an ill-defined placeholder for a grab bag
of technologies." To some, personalization is customizing the content of a Web
site; to others, it represents a marketing sea change with far-reaching implications
for anyone selling anything, anywhere.
"Many marketers look at
it as a way to sell 2.1 percent more hula hoops this quarter," said Christopher
Locke, editor-in-chief of Personalization.com and co-author of The Cluetrain
Manifesto: The End of Business As Usual. Locke's Web site, sponsored by personalization
vendor Net Perceptions, provides listings of vendors, analysts, industry associations,
books and news, as well as pointers to other Web-based resources on personalization
and related technologies.
"But what's going on is
a fundamental shift in the nature of markets and marketing," continued Locke.
"Instead of just figuring out what products you'd be interested in, [personalization
software] can figure out what people you'd be interested in and build a market
conversation that throws power back to customers."
Added Locke, "This is much
more profound than just moving the merchandise. If someone asks me point-blank
what kind of books I like, I usually can't give them a particularly useful answer
off the top of my head. Even if I sit down to think about it, I can't come up
with much more than a few old favorites and the titles I'm currently reading.
But if I were to buy a lot of books online, that site could, potentially, provide
a much more complete picture of my reading preferences."
Despite the lack of a clear
definition and some emerging ethical concerns, a basic advantage has become
very clear: Internet personalization can tailor marketing messages to individuals
in a far more interactive manner than snail mail, E-mail or telephone models.
Marketing mavens have started to call the Internet piece of the personalization
puzzle the ultimate one-to-one marketing model.
"The Internet can give consumers
a personalized, customized experience," said Larry Ponemon, a partner and global
leader of the compliance risk management program at New York City-based consulting
firm PricewaterhouseCoopers. "That is important — it's what makes the Internet
more than a television set."
The Web clearly allows the
personalization model to broadly expand beyond telemarketing and even hyperlinks
embedded in E-mail messages. While tra- ditional, offline markets are stuck
with top-down, market-research approaches, personalization tools can explore
market behavior from the bottom up (in other words, from the data). Web-based
personalization systems can use raw information to discover meaningful correlations
in the data and employ increasingly sophisticated software to analyze and exploit
the shopping behavior of individual customers. For example, an untold number
of consumers are now greeted by name at retail Web sites like Amazon.com and
CDNow. But both sites also do a lot more than just remember the names of customers;
they can also offer product recommendations based on the purchase histories
of other customers with tastes similar to a shopper's own.
Observers note that to date,
organizations rely on two technologies to build personalization systems: collaborative
filtering and profiling. Collaborative filtering calls for using the experiences
of an individual consumer to shape electronic responses to that customer. Profiling
aggregates the data from multiple Web sites to create a site configured to the
needs of an individual consumer. Application server and portal suppliers are
quickly starting to unveil tools that promise to make it easier for corporations
to add personalization capabilities to Web
sites.
Choosing your personalization
model
Despite some disagreement
on nomenclature, most analysts agree that there are four basic types of personalization
models: name recognition, check-box, rules-based and behavioral preference-based.
"Keep in mind that the edges blur. These are useful categories for thinking
from 40,000 feet. But when you get down to the nitty-gritty, a lot of [personalization
products] use all four [models]," said Locke at Personalization.com.
Name recognition is probably
the most basic form of personalization, as well as the easiest to incorporate
into most systems. Included in this model is the letter from Ed McMahon or the
"Hi Bob" on someone's MyYahoo! Web page. It is a kind of mass personalization
that is in many ways decidedly impersonal. A few years ago, greeting people
by name marked a turning point in mass-marketing techniques; it continues to
be used by businesses because it still has value. "Most people like to be acknowledged
by name," noted Locke.
Check-box personalization
involves information customers provide on questionnaires, surveys and other
online forms. (Think of the registration page for commercial software.) Users
provide this information about themselves by checking answer boxes. A Web site
using check-box personalization presents content based on a customer's answers.
Segmentation and rules-based
personalization uses a demographic, geographic or psychographic profile, or
other information to divide or segment large populations into smaller groups.
Data such as income level, geographic location and buying history is aggregated
to identify groups of people. Web sites using these types of personalization
systems deliver content based on "if this, then that" rules processing.
Preference-based personalization
seeks to understand the behavioral preferences of a specific, individual user
and then delivers Web site content specifically targeted to that user. This
type of personalization, also known as collaborative filtering, is database-driven
and operates on more complex algorithms. It can also factor more details into
each interaction. Preference-based personalization works by tracking user activity,
comparing that activity with the behavior of other users, and then predicting
what the user would like to see next. Some preference-based personalization
systems can even "learn" and become more precise over time.
Preference-based tools are
better at providing real-time personalization functionality. Real-time personalization
refers to a site's ability to modify a response to a user based on a changing
perception of the user as the interaction occurs. Rules-based and check-box
model approaches are not as good at this. They can, however, assimilate new
data and alter responses while the user is interacting with the site, provided
all potential responses and alternatives have been accounted for.
Collaborative filtering:
Personalization from the bottom up
Traditional market analysis
techniques require access to data on large groups of people, called customer
segments, to define mathematically meaningful relationships. Generally speaking,
you need a lot of people to make the math work.
Collaborative filtering
is used to look at a single customer, one that is unknown to a company. The
emergence of sophisticated collaborative filtering tools is a key reason for
the strong emergence of corporate interest in personalization techniques. Such
tools make it possible to generate statistically significant predictions and
recommendations about an individual, despite the availability of very little
information about that person.
If you have ever browsed
Amazon.com and clicked on a book, you have probably seen collaborative filtering
tools at work. That message at the bottom of the page —"Customers who bought
this book also bought:" followed by a list of titles — is a recommendation generated
by software that collates buying patterns across a large number of customers.
The patterns that emerge from this kind of data are much more than the sum of
their parts. What surfaces is something Locke refers to as "the largely unconscious
process by which social communities assess and measure value." This emergent
behavior of complex systems, he noted, is the real guts of the latest and most
sophisticated personalization techniques.
"It's organization and coordination
that takes place without explicit planning or premeditation," explained Locke.
"Patterns emerge among otherwise unconnected readers, or among any group of
people with a shared interest. In many cases, these are communities that aren't
even aware of themselves. Collaborative filtering tools are new and very powerful
tools that fit the Internet largely be- cause they are capable of defining these
micromarkets."
Here is how the concept
works: The unknown user provides answers to a small number of questions (the
"collaborative" part), which the personalization tool compares with the known
preferences of customers in its database (the "filtering" part). The tool then
generates a temporary "community" of customers with these shared preferences.
It can now extrapolate recommendations based on other preferences the community
shares.
The Album Advisor page on
the CDNow Web site is another example of collaborative filtering. On the page,
a buyer of a gift is asked to provide the titles of three recording artists
the gift recipient likes. The personalization tool — in this case, the Net Perceptions
for E-Commerce product — uses these three data points as the basis for its recommendations.
"When you input the three
artists, the Net Perceptions tool creates a kind of neighborhood of people who
like those three artists," said Steve VanTassel, Net Perceptions' vice president
of commerce solutions. "Then it looks for things those neighbors have in common
beyond those three artists. Where it finds the greatest degree of commonality,
it says, 'Hey, this is what I think this person is also going to like.'"
The collaborative filtering
process has its roots in research conducted at the University of Minnesota in
the early 1990s. Net Perceptions, an Eden Prairie, Minn.-based personalization
tools provider, was founded in 1996 to expand that research and later commercialized
the concept. "We create the customer segments —this 'neighborhood' — from the
bottom up or from the individual out," said VanTassel. "Once another action
is taken, that neighborhood is disbanded and a new one is created. That's why
we call it 'dynamic.'"
Unlike rules-based personalization
tools, which can determine in advance a set of conditions that guide the site's
response to its customers, collaborative filtering technologies impose no business
context. Nonetheless, the two models are often used in collaboration on the
same Web site. A movie retailer, for example, might want a rule stating that
anyone known to be under 17 years old will not be shown movies rated R or above.
Now that the playing field is established, the site still might want to make
recommendations, which is where the collaborative filtering would kick in.
B2B personalization
Beyond business-to-consumer
e-commerce applications, the personalization model is finding its way into business-to-business
(B2B) applications. "Knowing the interests and profiles of your partners and
suppliers helps you recommend meaningful products and services," said Todd Boes,
director of product marketing at Allaire Corp., Cambridge, Mass. In March, Allaire
acquired the Open Sesame profiling and personalization technologies from Browne
Internet Solutions.
"Personalization, in a very
large sense, is about taking general-purpose software and turning it into something
that is specific to a customer or the customer's customer," said Joshua Greenbaum,
principal at Enterprise Applications Consulting, Berkeley, Calif. "On the business
side, personalization has a lot to do with being able to capture the rules and
business processes that define the way you do business.
"[For example,] I have a
different way I want to give incentives to my customers and partners — maybe
I want to give them a discount when they buy in bulk, or I have a different
approach to managing my supply chain," he added. "I want to build those rules
into my software so that I'm automating as many processes as possible."
According to Boes at Allaire
Corp., personalization technologies and strategies do not appear exclusively
in retail and business environments, nor are those necessarily the best applications
of the process.
"It's definitely being used
to customize content delivery at information portals and pure content sites,
such as CNN or ESPN," he said. "Because CNN knows that I happen to be interested
in financial news and I follow the technology industry, that's the content I'm
going to see when I go there. In fact, a lot of personalization is going to
be used on the service and support side, improving daily interactions with customers
— purchases, support, refunds, that sort of thing. I think it's better utilized
in non-retail environments, where the personal interactions are more meaningful."
Boes said Allaire is beginning
to shy away from the personalization moniker because the term is limiting. Instead,
Allaire uses the term "customer intelligence" to describe the process. "A lot
of the information gathered for personalization purposes is useful across organizations,"
said Boes. "Analyzing that information, whether you're in finance, marketing
or support, is critical."
'Pushing the ethical
envelope'
The concept of personalization
has posed ethical concerns to a variety of organizations, however, that fear
some companies might misuse personal information gathered with or without the
permission of its customers. "I am part of the group that believes in the Web,
that it marks a revolutionary business change," said Price- waterhouseCoopers'
Ponemon, who also founded the firm's privacy practice. "But we are starting
to see areas that are pushing the ethical envelope."
PricewaterhouseCoopers is
a founding member of the fledgling Personalization Consortium, formed in April
by 26 companies of all sizes "to promote the responsible and beneficial use
of technology for personalizing consumer and business relationships." Among
the founding members of the Wakefield, Mass.-based consortium are American Airlines,
BroadVision, E.piphany, KPMG Consulting and Servicesoft. Said Ponemon before
the consortium was unveiled during the Spring Internet World conference in Los
Angeles: "If we don't do this now, we will face more and more government regulation.
We have to have some accountability to government, but we want industry to set
up a system of self-regulation" that can include realistic rules.
Precisely where personalization
and privacy collide is anyone's guess. Privacy advocates fear any trend that
puts personal information in the hands of those who might abuse it. Proponents
of personalization swear they take every precaution, such as anonymous identifiers
and using aggregated data to protect the privacy of their customers. Still,
many users simply do not like to surrender personal data.
"People have been reluctant
to use cookies, and there are people who just don't want to give up any information
about themselves," said Allaire's Boes. "But people are warming up to the idea
because it gives them a better experience. They're beginning to see it less
as an invasion of privacy and more as a benefit."
The Personalization Consortium
recently asked 20,000 Web users about personalization and online privacy. The
survey found 51% of respondents willing to exchange personal information for
better service. In contrast, only 15% of respondents said they would be unwilling
to share any information with Web marketers, even if it meant improved service.
When respondents were asked
what personal information they would provide to a Web site in order to customize
their online experience, 76% said they would divulge their hobbies and interests,
81% would provide an address, 95% would provide an E-mail address, and 96% said
they would supply their name.
Eventually, the advantages
of personalization — improved service and faster access to preferred information
— can outweigh the disadvantages of sharing personal information with unknown
merchants, observers say. And the ethical concerns can be addressed, noted Ponemon
at PricewaterhouseCoopers. Until then, e-commerce organizations will continue
to have to provide consumers with privacy controls that allow them to choose
their level of personalization, and to even opt out altogether, he said. Allaire's
Boes breaks personalization strategies down into two approaches: explicit and
implicit. Explicit personalization gets a user to volunteer information (rules-based).
The forms users have to fill out to create a MyYahoo! page are part of an explicit
personalization strategy. The implicit approach leaves it up to the software
to analyze user behavior (collaborative filtering).
But for all the heat this
concept is generating, surprisingly few corporations are utilizing sophisticated
personalization technologies or strategies, said Boes. "There are a lot of folks
who are doing very basic things. We see lots of simple, straightforward explicit
personalization. But we're not seeing many using the implicit approach," he
said.
"In the online world, you
can find a better price with a mouse click," added Boes. "How do you keep people
at your site and get them to purchase from you? It's going to come down to customer
service, to that vendor knowing you better than anyone else, and [being able
to] service your needs and provide support when you need it to keep you from
going anywhere else."
John K. Waters is a freelance
writer based in Palo Alto, Calif. Michael W. Bucken also contributed to this
article.
The language
of personalization
Personalization
is an old idea driven by new technologies and new jargon. Here is
a short list of definitions to help you wade through some of the
emerging nomenclature.
Customer relationship
management (CRM) — a technique that brings information about customers
into a central repository. Serves to provide a better "read" on
individual customers and market trends. CRM tools integrate all
company operations that involve customers, including marketing,
sales and service.
Customization
— a kind of personalization technique that allows the customer to
control the content of a Web page in order to "customize" it to
reflect their particular interests. Usually, there is a form to
fill out. MyYahoo! and MyExcite are examples of customization.
One-to-one marketing
— what personalization is all about. In this context, it refers
to techniques and technologies that gather information about individual
customers, as well as to the automation of marketing efforts designed
to communicate with individual customers.
Permission marketing
— a term probably coined by Seth Godin and Don Peppers, whose book,
Permission Marketing: Turning Strangers Into Friends, and Friends
into Customers explores the concept of enlisting the customer as
a partner in your marketing efforts. The authors argue that traditional
forms of "interruption advertising" — which bombard consumers from
magazines, direct mail and broadcast media — are less effective
than those designed to get a customer’s permission with some kind
of "bait" (such as a free sample, a big discount, a contest, an
800-number or an opinion survey).
Relationship
marketing — a broad category of marketing activities that involves
the management of ongoing relationships with customers, partners
and/or vendors.
Touch points
— "places" where the enterprise connects with the customer, including
the call center, direct mail and Web sites. CRM tools allow organizations
to connect company touch points with a common database that allows
for the sharing of information through a central repository.
— John K. Waters
|
|
Privacy
poll
|
|
Strogly
Disagree |
Disagree |
Neither
Agree nor Disagree |
Agree |
Strongly
Agree |
A privacy statement
is necessary for me to share personal information. |
5%
|
11% |
24% |
31% |
27% |
I find it helpful and
convenient when a Web site remembers basic information about me (e.g., my
name and address). |
4%
|
5%
|
17%
|
42%
|
31% |
I find it helpful and
convenient when a Web site remembers more personal information about me
(e.g., my preferred colors, music or delivery options). |
7%
|
13%
|
30%
|
31%
|
19% |
Banner ads and “pop
ups” are an invasion of my privacy. |
8%
|
21%
|
35%
|
16%
|
19% |
I am willing to give
information about myself in order to receive an online experience truly
personalized for me. |
4%
|
11%
|
33%
|
41%
|
10% |
It bothers me when
a Web site requests personal information I have already provided (e.g.,
my mailing address). |
5%
|
9%
|
23%
|
38%
|
24% |
|
|
|
|
|
|
Source:
Personalization Consortium, April 2000 |
A
closer look at the personalization space
|
As
fast as things are moving in the personalization space, it would be difficult
to offer a definitive list of product vendors. The following listing contains
the names of some of the major players as of press time.
|
Company |
Location |
URL
Address |
Product/Technology |
Allaire
Corp. |
Cambridge,
Mass. |
www.allaire.com
|
ColdFusion,
Open Sesame Profiling Server |
Annuncio
Software Inc. |
Mountain
View, Calif. |
www.annnuncio.com
|
Annuncio
Bright |
Art Technology
Group Inc. |
Cambridge,
Mass. |
www.atg.com
|
Dynamo |
Autonomy
Inc. |
San
Francisco, Calif. |
www.autonomy.co.uk
|
Content
Server |
beFree
|
Marlborough,
Mass. |
www.befree.com
|
Adaptive
relationship modeling technology (gained through acquisition of TriVida
Inc., Culver City, Calif.) |
Blaze Software
|
San Jose,
Calif. |
www.blazesoft.com
|
Blaze Advisor,
Blaze Expert |
Broadbase
Software Inc. |
Menlo Park,
Calif. |
www.broadbase.com
|
Broadbase
EPM |
BroadVision
Inc. |
Redwood
City, Calif. |
www.broadvision.com/
OneToOne/ SessionMgr/home_page.jsp |
One-to-One
|
Computer
Associates International Inc. |
Islandia,
N.Y. |
www.ca.com
|
Neugents
|
Cyber Dialogue
|
New York,
N.Y. |
www.cyberdialogue.com
|
Telescope
|
Edify Corp.
|
Santa Clara,
Calif. |
www.edify.com
|
Electronic
Workforce |
eHNC |
San Diego,
Calif. |
www.ehnc.com
|
SelectCast,
SelectResponse |
Elity
Systems Inc. |
Somerset,
N.J. |
www.elity.com
|
Elity Insight
Engine |
Engage |
Andover,
Mass. |
www.engage.com
|
Engage
ProfileServer |
E.piphany
Inc. |
San Mateo,
Calif. |
www.epiphany.com/index.html
|
E.piphany
E.4 System, E.piphany Real-Time Recommendation Engine |
GuestTrack
Inc. |
Los Angeles,
Calif. |
www.guesttrack.com/exec/
gt/index.html |
GuestTrack
|
Gustos
Software LLC |
Laguna
Hills, Calif. . |
www.gustos.com
|
Gustos
Guide |
ILOG Inc. |
Mountain
View, Calif. |
www.ilog.com/industries/
ebusiness |
Components
for e-Business |
iLux Corp.
|
Newark,
Calif. |
www.ilux.com
|
Suite 2000
|
Inference
Corp. |
San Francisco,
Calif. |
www.inference.com
|
k-Commerce
Sales |
Macromedia
Inc. |
San Francisco,
Calif. |
www.macromedia.com
|
Aria,
Likeminds |
Manna
Inc. |
Wellesley,
Mass. |
www.mannainc.com
|
FrontMind
|
MatchLogic
Inc. |
Westminster,
Colo. |
www.matchlogic.com
|
MatchLogic
|
Metabyte
Inc. |
Fremont,
Calif. |
www.metabyte.com
|
MbTV |
MicroMass
Communications Inc. |
Cary, N.C |
www.micromass.com
|
IntelliWeb |
net.Genesis
Corp. |
Cambridge,
Mass. |
www.netgen.com
|
net.Analysis
|
Net Perceptions
Inc. |
Eden Prairie,
Minn. |
www.netperceptions.com/home
|
Recommendation
Engine Suite |
NovuWeb
Inc. |
Manhattan
Beach, Calif. |
www.novuweb.com
|
Genius
Server |
Open Market
Inc. |
Burlington,
Mass. |
www.openmarket.com
|
IPS, Xcelerate,
Transact |
Personify
Inc. |
San Francisco,
Calif. |
www.personify.com
|
Personify
Essentials, Personify Snapshot |
Responsys.com
|
Palo Alto,
Calif. |
www.responsys.com
|
Responsys
Interact |
Tian Software
Co. |
Denver,
Colo. |
www.tiansoft.com
|
e-volving/ASP
|
Vignette
Corp. |
Austin,
Texas |
www.vignette.com
|
StoryServer,
netCustomer |
Younology |
New York,
N.Y. |
www.younology.com |
OrbjectWare |
|
|
|
|
Source:
John K. Waters |