April 2001
The Challenges And Rewards
Of Personalizing Customer Interactions
BY JENNIFER L. SULLIVAN, UNICA CORPORATION
If today's marketplace is so rich with ways to
communicate with customers, why are so many companies struggling to
optimize online interactions? The answer is personalization -- the
strategy of successfully marrying in-depth customer understanding with
marketing and sales execution to provide customers relevant offers and
information. Personalization is the key to optimizing a company's online
dialog and enhancing its ability to cross-sell and upsell customers.
Knowing and understanding what customers are looking for makes a company's
dialog with them -- regardless of channel -- that much more effective.
Additionally, because the online channel is 'self-service' in
real-time with no direct sales contact, it's critical that every
interaction is optimized for mutual benefit.
The challenge is gaining an in-depth understanding of browsing
customers' habits and real-time needs without intruding on their privacy
or not providing value for the exchange of personal information. Recently
published statistics indicate that companies can achieve at least a 20
percent increase in purchases through personalized online dialog. This is
supported by a study by the Center for Democracy and Technology that found
that 78 percent of Internet users would be willing to provide personal
information in exchange for customized services. The dialog, or exchange
of personal information for customized offers, must prove valuable to both
the customer and the company. Additionally, companies that have
successfully gained the trust of the consumer and privilege of learning
more about their buying preferences have also been the ones that have been
able to increase their customers' annual and lifetime value.
Personalization has enabled them to target offers more specifically to the
individual buyer's needs for higher response rates to cross- and upsell.
A company cannot rely solely on customers to provide all the necessary
information. Online dialogue must be based on predictive analysis. Today,
real-time personalization applications that use rich customer data provide
the right level of personalization with the most effective offer, content
or service to individuals. The technology uses both online and off-line
data, combining predictive profiles, current interaction context and
business objectives for powerful personalization. Because customers are
dynamic, the technology must be dynamic as well. In looking for an
appropriate real-time personalization technology, look for those that have
an open architecture to enable integration with any real-time system,
including Web and contact center systems. Consider how easy or hard it
will be to change and enhance your business rules that drive
personalization. You want to empower marketers to manage the business
rules as much as possible. Look for applications built on RAM-based cache
technology so as not to introduce latency into real-time channels. Again,
you can only be relevant if you understand the customers in all their
dimensions. By combining historical information such as recency,
frequency, monetary value, predictive analysis (such as cross-sell
recommendations), attrition likelihood and lifetime value with real-time
context of the customer interaction including minutes on the Web site,
which products they are viewing and pre-defined business rules, you can
achieve effective personalization techniques.
Let's take a look at a few examples. Let's suppose there is a
"retail/e-tail" company called Gizmos.com that has both a
traditional store and an online store, and supports various customer touch
points for traditional channels such as a contact center, direct mail and
fax, as well as newer channels such as e-mail, Web sites and wireless
devices. Gizmos.com is a sophisticated marketing company that understands
the value of building long-term relationships with its customers by using
analytical CRM and marketing automation for its marketing communications.
Additionally, Gizmos.com provides real-time context-sensitive
personalization at its Web and contact centers for anonymous and known
users based on online and off-line data.
Scenario #1. An individual arrives at Gizmos.com from an
affiliate Web page, Gadgets.com. Based on informational profiles the
marketing team at Gizmos.com has built for an individual coming from
Gadgets.com, Gizmos automatically personalizes the site. Based on lifetime
value information, an instant offer of "10 percent off your next
purchase" pops up while the customer is browsing. Additionally, after
the customer has put a few items into his or her shopping cart, specific
cross-sell recommendations are made. The profile is based on information
from individuals who have come to Gizmos.com from Gadgets.com, as well as
what has been accumulated in the shopping cart. The Gizmos.com site can be
tailored with banner ads, graphics, information and articles more relevant
in nature to these individuals than the standard Gizmos.com site.
Scenario #2. An anonymous visitor arrives at Gizmos.com.
The marketing team at Gizmos.com needs to be armed with ways in which to
personalize the site based on the new individual's interests, and again
must be willing to personalize in exchange for information. As a hook, the
marketing team makes a "free shipping" instant offer in exchange
for registration on the site, which includes just a few key questions
about the visitor's interests. Then, as the shopper continues to browse,
the real-time personalization application may recommend specific graphics,
banner ads and information. As the customer puts items into his or her
shopping cart, cross-sell offers are presented based on the product
profile.
Scenario #3. A known customer visits Gizmos.com. The Web
site will already be personalized with a welcome screen identifying the
customer's name and, as this is a high-value customer, offers "free
shipping on your next purchase over $100." As the customer places
items in the cart, a live chat becomes activated and is displayed for this
high-value customer to ensure there are no barriers to purchase. The high
value associated with this customer has been generated from historical
data, predictive analysis and data from online and off-line sources.
Again, cross-sell items can be displayed based on a customer profile that
was generated by sophisticated models.
Overall, the technology enables marketers to be nimble and flexible in
tailoring personalized exchanges. It exploits available online and
off-line data for known and anonymous users and adapts to user and
aggregate site behaviors. Unlike touch-point-specific, hard-coded rules or
simplistic modeling around a single channel's data, the personalization
strategy and technology facilitates flexible dialog, increasing the
likelihood of a successful sales transaction. Successful personalization
techniques ensure that what you are offering your customer is relevant.
The more relevant the offer, the more likely the customer is to accept,
creating higher ROI for your company and satisfaction for your customer.
In today's changing marketplace, every customer interaction is
critical. Each customer contact is an opportunity to keep or lose a
customer, as well as build brand loyalty or undermine it. Effective
personalization, based on rich cross-channel customer understanding, is
key to successful interactions. Consumers are willing to provide
information in exchange for a value-added relationship. By using online
interactions and the Web's ability to collect information directly and
indirectly from your customers, you should leverage that information to
enhance the value of the exchange. By offering timely personalized
communications, companies will find that they optimize all their online
interactions.
Jennifer L. Sullivan is the manager of Database Marketing at Unica
Corporation (www.unicacorp.com) in
Lincoln, Massachusetts.
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