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Knowledge-based Systems Invigorate CRM
 By Rob Keene
Banking Practice Director
Customer
relationship management systems (CRMS) are designed to allow execution
of targeted strategies at the point of contact. The goal is to maximize
your company's bottom line by controlling the factors that generate
profit and by delighting the customer.
Customers
are delighted when their expectations are exceeded. To exceed expectations,
you must know more than just the customers' expectations. You must have
complete knowledge of how your products and services can achieve this
goal within the confines of profitability and sound business practice.
At the Robert E. Nolan Company, we have found that Knowledge-Based Systems
are invaluable in achieving these goals.
The
cornerstone of an effective Knowledge-Based System is data mining. Data
mining uses statistical analysis to develop better business decisions
than could be made using conventional methods. Data mining improves
your decision making by giving you insight into what is happening in
your business today and by helping you predict what will happen tomorrow.
Many data mining tools on the market today can help you build powerful
Knowledge-Based Systems by:
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Rapidly
exploring data |
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Quickly
identifying patterns and trends |
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Generating
actionable business information |
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Building
better business rules |
The common
results of data mining are the construction of Knowledge-Based Systems
in the following areas:
| Customer
Profiling. Understanding your customers by analyzing their behaviors
and preferences, resulting in the development of profitable, customized
solutions. |
| Target
Marketing. Developing better intelligence on who is responding to
your marketing campaigns so you can focus your offers more precisely,
resulting in lower cost and higher response. |
| Risk Management.
Identifying the customers most likely to be business risks by building
models that anticipate risk events such as early detection of delinquency
or fraud. |
| Valuation
and Loyalty Analysis. Recognizing valuable and loyal customers for
purposes of recognizing and rewarding them to insure retention. |
Develop Knowledge-Based
Systems through the following steps:
| Develop
data sources and prepare the needed attributes. Legacy and other operational
systems provide significant customer information, including account and
household-level information as well as geographic and transactional data.
From this core data you can derive additional data fields that are more
meaningful for building your Knowledge-Based System. |
| Enrich your data sources.
Significant sources of additional information about your customers or
prospects can be purchased from third parties and appended to your data
sources. |
| Import
the data into your data mining tools. Depending on the number of records
and variables needed, your entire database or samples of selected data
should be fed to your data mining tools for analysis. |
| Develop
your models. Using the data mining tools, models can be developed
and verified through iterative testing and re-testing. The tools slice
through the data to get to the key variables that influence business success. |
| Report
your findings and communicate results. Pushing your findings to the
point of contact will focus the effort on attributes that are meaningful
in achieving success. Developing Knowledge-Based Systems and providing
the results to the point of execution results in greater effectiveness
than providing data upon request. |
Knowledge-Based
Systems result in more effective CRM and profitability by simplifying
the decision-making process. Your company will be more nimble and productive
at the point of contact if you focus on the variables in your business
that are statistically significant in providing the desired results.
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