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ManagerGet a 360 degree view of your customers with

our premier onsite data integration solution

Technical White Paper

Sales & Marketing

Solutions

Customer Integration

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Table of Contents

The Need for Customer Data Integration 3

Data Integration Challenges 4

The Data Integration Process 5

Deployment Options 8

Introducing Customer Integration Manager: the Premier Business 9Customer Data Integration Solution from D&B

Business Benefits 9

How It Works 10

The Customer Integration Manager Matching Process 12

Technical Benefits 14

Sample Applications 15

Integrated Customer Relationship Management 15

Consolidated Sales Data for Customer Analysis 16

Interactive Customer Lookup During Order Entry 17

Implementation 18

Monthly Update 18

Support 19

Summary 19

All data is fictitious.

2 Customer Integration ManagerTechnical White Paper

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The Need for Customer Data Integration

CRM. ERP. Supply Chain. Demand Management.

Business Intelligence. Data Warehouse. Look inside any

of today's strategic business technologies and you'll find

the same requirement: to share data freely and accurate-

ly across different business functions. Data sharing is

what lets customer relationship management systems

ensure consistent customer treatment across different

channels. It is what lets enterprise resource planning

systems coordinate manufacturing plans with sales

forecasts and inventory levels with delivery schedules. It

is what lets quality managers track customer complaints

back to specific production units.

In the abstract, data sharing looks easy enough just

connect a few boxes on a white board or assume the

whole company moves to a single all-purpose software

package. But reality is much more complicated.

Different departments, divisions, and subsidiaries will

continue to run separate systems, and even if every

member of the corporate family does adopt the same

integrated product,every supplier and customer will not.

While technology has simplified the physical movement

of data among systems, physical movement is not

enough. Data must be logically integrated as well.

This means your systems must recognize that the cus-

tomer who bought this product through the order entry

system is the same customer who logged that complaint

in the customer service system and the same customer

about to receive those mail promotions from the market-

ing system. The trouble is, each system holds its own

record for that customer in a different format, with dif-

ferent spellings, and possibly even under different

names. You can close your eyes, click your heels three

times, and hope the separate systems go away. Or you

can find a way to identify the relationships among those

records despite the differences.

Finding those relationships is part of a

process called customer data integra-

tion. There is more to customer data

integration than just matching cus-

tomer records, although matching is

at the heart of the process. Customer

data integration also involves estab-

lishing relationships among records

that cannot be matched directly, such

as corporate parents and subsidiaries

with different names or addresses. It

identifies the most accurate version of

information such as a company tele-

phone number or mailing address

that is different in different systems. Most important, it

assigns a permanent identification number to each cus-

tomer. This permits easy sharing of customer data with-

out complicated, on-the-fly matching processes.

Accurate customer data integration is particularly

important for achieving the promises of today's cus-

tomer relationship management projects: lower market-

ing costs, higher retention rates and greater revenue per

3

Customer Integration Managerlinks customer data across systems

Web Site

Accounting Service

Sales

MarketingDatabase

Production

DataWarehouse

Inventory

Customer Integration Manager Technical White Paper

ManagerIntegration

Customer

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customer, among other tangible benefits. All these goals

are premised on developing a complete picture of each

customer's relationships with your business. This

requires both combining data from different systems

and linking records within the same system that refer to

the same customer. Sometimes multiple records exist by

mistake and can be combined. But there is often a valid

reason for the same customer to have more than one

record, particularly when dealing with businesses rather

than individual consumers. A business customer may

have separate accounts for different departments, loca-

tions or even specific projects. While these accounts

must remain distinct for operational reasons, accurate

customer management and analysis must recognize

that they are related. In fact, the most active customers

are the most likely to have multiple accounts making

consolidation a critical function in managing your

largest clients as well as the smaller ones.

Although improved customer relationships are more

than sufficient reason to undertake a data integration

project, there are other benefits as well. One is the

increasing reliance on consolidated data for processes

other than direct customer contact, such as distribution,

financial planning and purchasing. In fact, consolidated

data on suppliers can sometimes be as valuable as con-

solidated data on customers. Data integration is also the

foundation of data warehouse and business intelligence

systems, which are increasingly used for both strategic

and tactical business decisions. Nothing destroys the

credibility of a data warehouse report more quickly than

an obvious understatement of sales to the company's

largest accounts and, as already noted, inaccurate inte-

gration is most likely to affect precisely those customers.

At the most basic level, customer data integration saves

money by avoiding redundant data entry and cleaning

projects, providing more accurate information, and sup-

porting a complete and accurate view of the customer

that is multifaceted.

Data Integration Challenges

The importance of customer data integration is clear, but

so are the difficulties. The fundamental problem is that

data is captured in many different systems, each with its

own formats, standards and requirements. Data may be

perfectly adequate for its original purpose yet still not

suitable for integration:for example,names and address-es in free form text fields can generate serviceable mail-

ing labels but are difficult to analyze for matching.

Similarly, operational processing is often unaffected by

data entry inconsistencies, such as variations in formats

and abbreviations, that make parsing and matching still

more difficult. Operational users often cram extraneous

information such as customer status codes into name

and address data that makes perfect sense to a human

reader or customized computer program, but confuses

external integration processes. Or an operational system

may lack basic information needed for any matching: for

example, a help desk system might capture only the cus-

tomer's first name and a telephone number to call with

an answer, but no mailing address or account ID.

But data integration is difficult even when the finest

operational systems are in place. Customers themselves

often provide different information to different systems,

4

Although improved customer relation-ships are more than sufficient reason toundertake a data integration project,

there are other benefits as well.

The fundamental problem is that data iscaptured in many different systems, eachwith its own formats, standards andrequirements.

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either by mistake or to meet different purposes: a billing

system may correctly hold a different address than a

shipping system. Nor do customers update every com-

pany system when important changes take place: if they

haven't called for customer service since their last move,

the customer service system will have an outdated

address. The system changes needed to support integra-

tion can themselves be a challenge, particularly since

many corporate IT departments have little experience

with customer data integration technologies.

Working with business rather than consumer data adds

yet another level of complexity. Business records include

not just a simple name, address and city/state/ZIP but

personal and company names, titles,departments,build-

ings, mail stops, and other elements. They also contain

industry terms, such as "DBA" for "doing business as",

that must be recognized and interpreted appropriately.

Few companies follow enterprise-wide formats to cap-

ture and hold these elements and even firms with

internal standards must contend with data from exter-

nal sources. Business files may also hold different names

for the same company, such as legal vs. trade names.

Common names may themselves be represented differ-

ently "Kentucky Fried Chicken", "KFC", "Kentucky FC"

and any number of variations. Related firms may have

totally unrelated names, such as Lotus Development

Corporation, a subsidiary of IBM. Multiple locations for

the same business must be somehow brought together.

Today's business trends make customer data integration

more challenging than ever. As more systems are con-

nected, integration techniques must become more effi-

cient to handle the increased volume. Interactive appli-

cations impose strict performance requirements to

ensure data entry and customer service processes are

not delayed. Privacy and security regulations impose

strict limits on how data is shared, making it more

important than ever to ensure accurate consolidation,

precise access control, and audit trails on changes

Privacy concerns also make it more difficult to gather

data directly and thus more important to share as

widely as possible whatever data your company has

already acquired.

The Data Integration Process

Customer data integration may be difficult, but it is

far from impossible. In fact, experience over the past

several decades has provided a firm understanding of

the steps in an effective data integration process:

Input. This is the initial process of gathering and pre-

senting the data to be integrated. Traditionally, large

numbers of records were extracted from source systems,

loaded into files, and run through the integration process

5

Data Integration Process

Parse

Standardize

Group

Match

Enhance

BatchOutput

OnlineInput

OnlineOutput

ValidationData (if used)

SupplementalData

ReferenceRules & Data

BatchInput


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as a group. Results were then posted back to the source

system or used elsewhere. This is referred to as "batch"

processing. Many data warehouses and marketing data-

bases are built this way.

Other systems use "online" processing, where an exter-

nal system presents a single record to the integration

system and waits for the result before continuing. This

often involves interactive processes where a human user

is working on the record. It also includes fully automat-

ed processes, such as processing a credit card transac-

tion, where immediate response is needed even though

there is no direct user involvement. Online processing is

technically more difficult than batch processing, because

the external system must be modified to present the

data and use the results. Online integration must also

run quickly enough to avoid a significant decline in

source system performance.

Matching. This is the heart of the data integration

process, where records are compared to find which are

related. It usually includes three stages:

1. Parsing isolates data elements so they can later be

compared with corresponding elements on other

records. For example, a typical parser would split a name

into title (Mr., Mrs. Ms., etc.), first name, middle initial,

last name, generation (Jr., III) and suffix (Ph.D., L.L.D).

Addresses and other data would be similarly broken into

components. Parsing also identifies missing or question-

able data.

Parsing is necessary because many systems

store name and address data as text lines

rather than separate elements. Often the pars-

er must determine both the nature of the line

and the sequence of the elements within it.

Sophisticated parsers use reference tables that

list how specific words are likely to be used

("Corporation" is probably part of a company name;

"Andrew" is probably a first name) and the likely

sequences of elements within lines of different types.

Reference tables must be tuned for specific applications

such as business or consumer processing and to adjust

for different national data formats.

2. Standardization is the stage in the process thatconverts data elements to standard formats to improve

match accuracy. On consumer records, it might replace

nicknames such as Bob, Bobby and Rob with a formal

name of Robert. For businesses, it might replace differ-

ent versions of a company name with a similar standard.

Like parsing, standardization relies heavily on tables to

make such corrections. Address standardization may sim-

ply apply standard formats or it may extend to valida-

tion and correction using actual postal tables. These

could determine which street names exist in which cities

and what postal code applies to each address. But postal

Parsing

6

Parsed Record

Name: Dan BrandstreetStreet Nbr: 3Street Name: Silven WayCity: ParrippanyState: NJPostal Code: 07054

Input Record

Dan Brandstreet3 Silven WayParrippany NJ07054

Standardization

Input Record

Name: Dan BrandstreetStreet Nbr: 3Street Name: Silven WayCity: ParrippanyState: NJPostal Code: 07054

Standardized Record

Name: Dun & BradstreetStreet Nbr: 3Street Name: Sylvan WayCity: ParsippanyState: NJPostal Code: 07054


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validation and coding are generally considered separate

processes from other standardizations and are often

applied outside of the data integration system.

3. Grouping determines which records are compared to

each other. This avoids the inefficiency of comparing

everything to everything else. Most systems build a

group key by extracting portions of data elements such

as state, city and last name. Often several keys are creat-

ed to bring together records that a single method might

miss. For batch matching, records are typically assem-

bled into one large file, sorted or indexed on the key, and

then compared in sequence. For online matching, the

keys are stored permanently on the customer database.

When a record is presented for matching, the online

system generates keys for that record and selects

customer database records with the same keys for

detailed comparison.

Linking. The process of deciding which records should

be considered a match. All matching systems ultimately

rely on string comparisons that is, they assess the sim-

ilarity between the text strings assigned to the different

data elements in the records being compared. Some sys-

tems extract a few characters from each data element to

create a "match code" and treat all records with the same

match code as a match. Some calculate numeric similar-

ity scores for each pair of elements, add the scores, and

treat as a match any pair of records whose total exceeds

a specified threshold. Some assign alphabetic codes to

different types of element matches and specify which

combinations of codes are considered a record match.

Each approach has its proponents, but the code-

combination technique is the most common among

sophisticated matching systems. The advantage of this

method is precise control over how each combination of

element-level matches is treated. The major criticism is

that specifying treatments for tens of thousands of dif-

ferent combinations is a great deal of work. But vendors

of such systems provide pre-built tables to spare users

most of this labor.

An ultimately more significant difference among match-

ing systems is whether they compare input records

against each other or against a separate validation file

Such validation files are compiled from external sources

and contain all entities that might appear on the input

files themselves. Each entity on the validation database

is assigned a fixed ID number. Input records are com-

pared with the validation file using conventional string-

comparison techniques;when a match is found,the ID iscopied from the validation database record to the input

record. Input records that end the process with the same

ID are assumed to match.

Validation-based matching is significantly more effec-

tive than direct comparison because the validation data-

base can contain links between records that are not

physically similar. For consumer data, this might be

someone who has changed addresses or has summer

and winter homes. This not only lets companies unify

customer records that would otherwise remain frag-

mented, but also provides notice that a customer has

moved even if he has not informed the company direct-

ly. Advantages for business matching are greater still

because of the many reasons legal vs. trade names

parents vs. subsidiaries, headquarters vs. branch sites

etc. that related records appear different.

The value of a validation database depends on its cover-

age and the accuracy of its linkages. The major data

compilers can afford to invest in comprehensive valida-

7

An ultimately more significant differenceamong matching systems is whether theycompare input records against each otheror against a separate validation file.


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tion files, knowing they will reuse the data many times

over. Since only an ID number is transferred from the

validation database to the input records, other informa-

tion compiled by the database developer can remain hid-

den or be provided for an extra fee. Validation-based sys-

tems are available for consumer data in the U.S., United

Kingdom and a few other countries. Business matching

files are available for most major developed countries.

Most systems also provide an option for manual

review of suspect matches that is, record pairs that

are similar, but not close enough to be accepted as

matches automatically.

The final output of any linking process is a set of records

with IDs that identify members of the same match group.

In consumer matching,the match group often represents

a single individual or household; in business matching, it

may represent records at the same site or belonging to

the same company. Matching systems often give each

record several IDs, representing different groupings.

Enhancement. Once matches are identified, the

process may attempt to create a more complete cus-

tomer record by combining information from multiple

sources. This could involve comparing conflicting data

from different systems and picking the values that seem

most likely to be correct. For example, birth date may be

populated in one system and blank or obviously wrong

(e.g., 99/99/99) in another. Or the system may combine

information from multiple records, such as the sum of all

account balances. It might also look at an external data

source that has information not collected internally.

Enhancement can be separate from data integration,

particularly when the enhancement data resides at an

external source. But it is often more efficient to do

enhancement within the integration processing stream.

Like other integration processes, enhancement can be

performed in batch or online. With today's communica-

tion technologies, even external data can be accessed by

in-house online systems at acceptable speeds.

Output. The final step in integration is making the out-

put available for use. In some cases, particularly online

systems, this means returning the data back to the

source system. In other cases, such as building a data

warehouse, the information will go somewhere other

than the original source. In still other configurations, the

result is added to a cross reference table that links source

system IDs such as account numbers with a standard

customer ID. This particular approach allows source sys-

tems to share customer data without modifying their

internal processes or data structures. Whatever the

details, the only task of the integration system is to pro-

duce an output either a batch file or online transaction

that links the original input with a standard customer

ID. Other systems can then process this data in any way

that is appropriate.

Deployment Options

Many firms have installed piecemeal integration solu-

tions to meet specific operational requirements, such as

sharing data between two particular systems. But enter-

prise-wide customer data integration usually involves a

dedicated system to gather, process and distribute data

across many different sources. Such systems can reside

at external service bureaus, as part of an in-house opera-

tion, or even in a hybrid configuration.

External service bureaus provide specialized expertise

and have economies of scale that can make them more

cost-effective than in-house processing. Service bureaus

are particularly appropriate for periodic batch updates,

where immediate turnaround is not required. They are

also often used to produce consolidated files, such as

marketing databases, that will reside at the service

bureau rather than the company's internal systems.


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External processing also simplifies validation-based

matching, since the service bureau has immediate access

to updates to the validation file.

In-house operation has become increasingly common,

particularly in data warehouse projects where the entire

system is maintained internally. In-house operation is

almost required for online applications, where the data

integration processing must take place quickly and be

tightly connected with other corporate systems.

Hybrid solutions let companies do most integration

processing internally, but still access external systems

when needed. The most common hybrid configuration

reads external files for validation or enhancement data.

This lets companies use up-to-the-second versions of

those files without the cost and security issues of copy-

ing them onto in-house systems. High-speed communi-

cations make it possible to use hybrid approaches even

for online integration.

Introducing Customer Integration Manager:

the Premier Business Customer DataIntegration Solution from D&B

Customer Integration Manager provides a single,com-

prehensive solution to your company's business customer

data integration needs. Customer Integration Manager:

Assigns consistent customer IDs to records from all of

your systems, allowing easy integration of customer

information throughout your company

Combines records from your own systems and from

D&B in an in-house validation directory that is easily

accessible for both batch and online processing

Regularly updates the validation database with fresh

D&B data

Remotely searches D&B's own computers for matching

records that have not already been downloaded

Includes D&B's own customer matching engine, a

sophisticated product using world-class technology and

specifically tuned for business matching applications

Performs both batch and online matching

Returns a single best match or provides interactive

users with a set of possible matches to evaluate

Can automatically request further research by D&B

staff when no match is found

Codes records with the D&B D-U-N-S Number, D&B's

universal company ID, opening the door to easy

enhancement with data from D&B's own files and from

many third parties.

Business Benefits

Customer Integration Manager provides your company

with the benefits of sophisticated customer data integration

without the costs of building it yourself. By installing

Customer Integration Manager, your company will:

Gain a consolidated view of customer relationships

that are spread over multiple accounts, sites and trade

names, thereby supporting effective customer relation

ship management programs

Facilitate online access by sales and service staff to

customer information, no matter where the information

is stored

Expand your understanding of each customer by

adding enhancement data from D&B and other

providers

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Ensure the integrity of customer data in each

corporate system, by identifying and eliminating dis-

crepancies caused by entry errors, outdated information

and incomplete records

Improve the efficiency of internal operations

by helping to coordinate front- and back-office systems

Make better business decisions by providing more

accurate data for marketing studies, sales analyses and

other types of research

Save time and money by acquiring a complete solution

that is easily adapted to your needs, rather than attempt-

ing to develop a comparable system internally

Benefit from the experience of D&B consulting servic-

es, world leaders in managing business customer data

HowIt Works

Customer Integration Manager accepts name and

addresses input from your company systems and returns

a standard ID plus company data from D&B files.

The system is built around the Common Customer Directory.

This starts with a set of D&B records representing the

universe of firms your company is likely to do business

with. Each record refers to a specific business site that

is, a branch or office of a single business at a single loca-

tion. Companies with multiple locations will have at

least one site record for each location. If a company does

business under multiple trade names at the same site,

there will be a separate site record for each name. This

improves matching accuracy since input records carry-

ing any of these names can still be recognized as part of

the same site.

Each D&B site record carries a unique D-U-N-S Number,

a universal site identifier assigned by D&B and used

throughout the world as a standard business ID. Records

for the same site but with different trade name will have

the same D-U-N-S Number. In addition to the site's own

D-U-N-S Number, the site record will carry the D-U-N-S

Numbers of the site's headquarters or corporate parent,

national parent and global parent sites if these exist.

D&B can provide additional data about each site from its

own files, including name, address, telephone number,

revenue, number of employees, and key executives. This

is stored on the site record or in separate tables that are

linked to the site records through the D-U-N-S Numbers.

All records carry a second site number, called the Logical

Site ID or LSID. Unlike D-U-N-S Numbers, LSIDs are

assigned independently at each Customer Integration

Manager installation. Use of LSIDs is explained next.

10

Underlying Technology

Operating System: HP-UX 11, Sun Solaris 2.9,Microsoft Windows 2000; configuration dependson data volume and throughput

Minimum hardware requirements:- Application Server: 2 CPUs @ 750 MHz,

Batch data inputs and outputs can be sent as delimit-ed or fixed record length files.The system can moni-tor a specified directory and automatically initiatebatch processes when new files appear.


with open-source solutions, Jboss and Jetty.

scalable architecture. It was built on a Struts framework

Customer Integration Manager is built on industry-standard technologies, making it an easy fit for mostcorporate systems environments. Supports platforms

include:

- Database Server: 4 CPUs @ 440 MHz,4 GM RAM, 1 TB Disk.

Database: DB2 (Version 2), Microsoft SQLServer 2000, and Oracle 9i RDBMS.

2 GM RAM, 100 GB Disk

The system is written in J2EE to provide a highly

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Once the D&B records are loaded, users can match them

against records from the company's own systems. (See

the next section for a detailed explanation of the match-

ing process.) If the input record matches a D&B record,

the input record is coded with the D&B record's

D-U-N-S Number and LSID. This will also happen if the

input record matches a previously-loaded company

record that is itself linked to a D&B record. If the input

record matches a company-provided record without a

D-U-N-S Number, it is given that record's LSID. If there is

no match at all, the system assigns the record a new

LSID. The result is that every record has an LSID while

records linked directly or indirectly to a D&B record have

a D-U-N-S Number as well.

Customer Integration Manager

can find additional D-U-N-S Num-

bers by connecting remotely to

the D&B master file. This

process, called Remote Resolution,

lets Customer Integration

Manager search for records that

were not selected for the local

database or have changed on the

master file but have not yet been

updated locally. If a remote match

is found, the D&B record is copied

to the Common Customer Directory

and its D-U-N-S Number is placed

on the input record;an LSID is

created or copied from an existing

record as appropriate. If no

match is found on the D&B

master file, the record can be

forwarded to D&B's Globa

Resolution Services staff. Thi

group will look for a match that

the computer missed and can

contact a non-matching site to

determine if it is truly a valid business. Since manua

research takes time, the non-matching record is initially

returned without a D-U-N-S Number. If a D&B match is

found later, the D-U-N-S Number will be added and the

LSID adjusted if this links the record to a different site.

Customer Integration ManagerOperation

Common Customer DirectoryCreation

11

Company Systems

Manager

Name & Address

Name & AddressD-U-N-S Numberand D&B data

Customer Integration Managercan findadditionalD-U-N-S Numbers by connectinremotely to the D&B master file.

1

2

Directory

Company InputDun Wordbase 3 Silver Way Parrippany NJDans Pizza 13 Short Ave Parsippany NJ

D&B Input = Initial Common Customer Directory D-U-N-S # LSIDDun & Bradstreet 3 Sylvan Way Parsippany NJ 123456789 1111Dun Worldbase 3 Sylvan Way Parsippany NJ 123456789 1111

Combined Input = New Common Customer Directory D-U-N-S # LSID

Dun & Bradstreet 3 Sylvan Way Parsippany NJ 123456789 1111

Dun Worldbase 3 Sylvan Way Parsippany NJ 123456789 1111

Dun Wordbase 3 Silver Way Parrippany NJ 123456789 1111

Dans Pizza 13 Short Ave Parsippany NJ 2222

(1) Company input matches D&B record; has D-U-N-S Number and LSID

(2) Company input does not match D&B record; has LSID only



CommonCustomer

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Records can be presented for matching in batch or

online. Online processes can choose the best match

automatically or present interactive users with a list of

candidates, ranked to present the most likely matches

first. Batch processes can also create lists of questionable

matches for users to resolve. Users can force a record to

become part of a specified site, regardless of how closely

it matches records already assigned to that site.

Once processing is complete, the record can be added to

the Common Customer Directory, sent to a flat file,

returned to an online system,or any combination of these.

Adding the records to the Common Customer Directory lets a

company assemble a complete list of its customers.The

system's matching functions can then be used to check

whether new inputs, such as responses to marketing

promotions or requests for technical support, match a

known customer record.

Output formats are customized for

each process and can include the

D-U-N-S Number, LSID, and other items

from the Common Customer Directory.

This database includes several separate

tables, linked by D-U-N-S Number, and

can incorporate data from D&B's master

database. Common Customer Directory

records can also store a user-specified "hard

key," typically a record number or account ID

from the original source system.Company

systems can use this key to find a record that

has already been loaded to the Common

Customer Directory. They can then use

the D-U-N-S Number or LSID on that

record to retrieve additional information

or to find records from all company

systems with the same D-U-N-S Number

or LSID.

The Common Customer Directory also receives monthly

updates from D&B itself. These updates include D&B

records that have been changed and new D&B records

that meet the user's selection criteria. The system can

reassign LSIDs and D-U-N-S Numbers if a match is found

to be inaccurate.

The Customer Integration Manager

Customer Integration Manager is powered by the DUNS

Name Matching API,an implementation of D&B's patented

name matching process.The system provides parsing,

normalizationand linking functions,all optimized for busi-

ness data. Linking uses the "code combination" tech-

nique, generally considered the most effective method

available. This assigns a code for the type of match

between each element pair,and then applies a table that

defines how each set of code combinations is to be treated.

12

Step 1: Compare Records and Generate Match Grade

Input Record Validation Record Similarity Type CodeName Dun Wordbase Dunn Worldbase Moderate B

Street Nbr 3 3 Strong AStreet Name Silver Way Sylvan Way Moderate BCity Parripany Parsippany Strong AState NJ NJ Strong APO Box Blank ZTelephone Nbr 973-605-6000 Blank Z

Match Grade = BABAAZZ

Step 2: Find Corresponding Confidence Code in Confidence Matrix

Confidence Matrix (portion)Match Grade Confidence Code Match Percentage

BABAAZF 8 90%BABAAZZ 8 90%BABABAA 8 89%

Step 3: List All Record Pairs Exceeding a Specified Confidence Code

(In this example: record 111111 matches record 222222; records 333333 and 555555 bothmatch record 444444)

Input Record ID Linked Record ID Confidence Code111111 222222 10

333333 444444 8

555555 444444 8


Matching Process

Match Engine Linking

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As described elsewhere in this White Paper, Customer

Integration Manager matches input records against a

validation table, rather than each other. This lets it

identify relationships among records that do not match

each other directly. Details of the process are:

Input. The match engine accepts inputs for business

name, address, city, state, postal code, telephone number

and country code. Country code is used to select coun-

try-specific matching rules and postal code is used to

resolve discrepancies between inputs and D&B valida-

tion records. The other elements are used in the match-

ing process itself.

Parsing. The system uses tables of key words and iden-

tification rules to split the address into street number,

street name and Post Office Box. Parsing tables and rules

are built into the system and not directly accessible by

end-users.

Normalization. The system normalizes the name and

address elements by removing extraneous words (such

as "The") and applying standard forms and contractions.

Normalization tables include standard names for specif-

ic companies as well as general business terms. Address

elements are normalized to improve matching.

Normalized data is a condensed form of the original

input designed for internal comparisons; it does not

replace the original data for display or output.

Grouping. The system creates group keys by extracting

information from the normalized name and address ele-

ments. The name and address keys can be used sepa-

rately or in combination to select records to compare in

the linking process. The system will compare all records

with the same key, regardless of how many there are.

Linking. The system compares the name, street num-

ber,street name, city, state,Post Office Box and telephone

number elements in each pair of records. The compar-

isons use different methods depending on the data type,

but each produces one of four similarity codes

A (strong), B (moderate), F (no similarity) and Z (one or

both is blank). These codes are strung together with the

most significant fields listed first to form a Match Grade

A system table called a Confidence Matrix relates each

Match Grade to a Confidence Code and Match

Percentage. The Confidence Code is a number from 0 to

10, typically interpreted as: 0=no match; 1-4=weak

match; 5-7=limited match needing user validation;

8-10=high quality match. The Confidence Matrix is

provided with the system; because it is based on

extensive empirical research, D&B recommends it

remain unchanged, but it could be modified if necessary

Different runs of the match engine could point to

different Confidence Matrices, although again this is

not recommended.

Output. The output of the matching system depends

on the application at hand. In Customer Integration

Manager it can be one best match or a set of possible

matches from the Common Customer Directory. Output can

include contents of the input record,the D-U-N-S Number

and/or LSID,match results like the Confidence Code or

Match Grade, treatment information such as whether

the record was sent for remote resolution or inserted in

the Common Customer Directory, and enhanced data

from a matching D&B record.The system can generate

different output for matched and unmatched records.

Users control many aspects of the matching process

some within the match engine itself and others in sur-

rounding applications.. In Customer Integration

13

Linking uses the "code combination"technique, generally considered themost effective method available.


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Manager these choices are expressed through

Workflows. Users can determine which types of

records to consider for a match: for example, they may

wish to exclude records that belong to companies known

to be out of business. They can also set the Confidence

Code levels required to accept a match or send it for man-

ual review, how many candidates to return for review,

and which types of records are sent to D&B for remote

resolution. Users willing to override D&B recommenda-

tions can change entries in the Confidence Matrix, allow-

ing them to determine which data elements are consid-

ering in the matching process and how different combi-

nations of element matches are treated. In many cases,

different settings can be applied in different situations

by creating alternate Workflows.

Technical Benefits

The approach taken by Customer Integration Manager

has many advantages:

One table links site records from all sources. The

Common Customer Directory provides all systems with

a single source for links among customer records.This

simplifies cross-system information requests, since

programs must look in only one location.The same directory

is shared by batch and online processes,so the company

need not develop multiple,redundant matching systems.

Minimal impact on source systems. The Common

Customer Directory can be created and managed without

changes to the source systems. Because the Common

Customer Directory holds both source system keys (the

"hard key") and internal linking keys (the D-U-N-S

Number and LSID), source systems can access specific

Common Customer Directory records and find related

records in other systems still without storing any new

data in the source systems themselves.

Company-wide ID scheme. The D-U-N-S Number and

LSID provide consistent IDs to identify the same

customer in all systems. This means that customer data

can be assembled with a simple query rather than a

complicated on-the-fly matching process. Companies

willing to store the D-U-N-S Numbers or LSID on source

system records could join customer data across multiple

systems without using the Common Customer Directory

as an intermediate cross-reference table.

Incorporates D&B data.D&B records in the Common

Customer Directory allow verification-based matching,

which is the most effective way to link business records.

In addition, the corporate family data on D&B records

provides connections that cannot be derived from cus-

tomer records alone. Because company input and D&B

records are coded with the same D-U-N-S Numbers and

LSIDs, it is easy to combine data from both sources.

Accumulates company-specific information. Company-

supplied records can be manually associated with a site

even though they appear unrelated. When similar

records are presented in the future, they will be linked to

the same site automatically. This allows the Site

Reference Database to build a store of information that

improves match accuracy over time. It also lets the sys-

tem associate D&B data with customer records that do

not directly match a D&B record.

Superior matching technology. D&B uses sophisticated

matching technology that is already optimized for busi-

ness data. Users can deploy and operate the system with

a minimum of effort, but still control critical parameters

such as the confidence level required to accept a match

or to flag it for manual review. Online matching

functions are accessed through a Java API that

lets users specify precisely how each transaction

is handled.


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Remote connections to D&B data and research services

This gives access to the most current D&B data without

constant updates to local files. It also lets the system find

matches against D&B records that are not stored locally,

allowing companies to limit the size of the in-house

database. Automated transfer of questionable records to

D&B for remote resolution permits use of this service

with minimal effort from company systems staff. Customer

Integration Manager supports both batch and online

Data Integration Batch, included with Customer

Integration Manager, gives each client a password-protected

home directory on the D&B server.When clients send files

to the directory via FTP. D&B systems process them

automatically, return the results to the directory

and generate email notifications to D&B staff and clients

Data Integration Toolkit, a set of optional modules

allows online, world wide integration of client systems

with D&B systems for corporate family linkage,

enterprise management, financial management and

marketing management.

Easily extended. Custom database tables can easily be

linked to the Site Reference Database using the

D-U-N-S Number or LSID as a key. These tables can hold

any data needed for company-specific applications.

Sample Applications

The following examples illustrate some of the ways that

Customer Integration Manager can be employed.

Integrated Customer Relationship Management

The lead processing module of a company's sales force

automation system calls Customer Integration

Manager to check if an inquiry is from an existing customer

and uses the result to determine how to respond.This

company has stored the LSID on customer records through-

15

The D&B Database

The D&B database is the world's most compre-

hensive repository of business information. It

covers more than 80 million business sites in214 countries, including 17 million in the United

States. Locations that are part of a larger

organization are linked in a corporate family

tree that identifies relationships between

headquarters and branches of the same corpo-

ration, and between parent corporations and

their subsidiaries.

Each site is assigned a D-U-N-S Number, aunique nine-digit identifier. In addition to a

site's own D-U-N-S Number, its record will carry

the D-U-N-S Numbers of the headquarters or

parent site, the ultimate domestic parent, and

the ultimate global parent. The D-U-N-S

Number is used by more than 50 global, indus-

try and trade associations including the United

States government, European Union and United

Nations.

The D&B database is refreshed more than one

million times each day with data from tele-

phone calls, company Web sites, and business

partners. More than 1,000 data elements are

collected; those available in the Common

Customer Directory include company name

and address, telephone number, and indicators

for whether the site is currently active, out of

business, marketable, and has a valid industrial

classification code available. Customer

Integration Manager can also store other D&B

data including revenue, number of employees,

year started, and executive names and addresses.


connections:

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out its CRM systems, so once Customer Integration

Manager has identified the customer's LSID,the CRM sys-

tems can manage interactions among themselves with-

out further Customer Integration Manager involvement.

1. The lead processing system receives an inquiry from

an unknown person. The system reads the business

name and address and sends these via Java to the

Customer Integration Manager API.

2. Customer Integration Manager parses and standardizesthe input. It finds a match in the Common Customer

Directory and returns the LSID via the Java API.

3. The lead processing system queries the company's

central marketing database, using the LSID as a key. The

query returns a customer status code.

4. The lead processing system uses the customer status

code as part of its business rule to determine how to

respond. In this case, the rule determines this is a high

value customer who should receive a telephone call. The

lead processing system sends a transaction to the call

center, including the LSID as part of the customer identi-

fier. The call center calls the customer.

Consolidated Sales Data for Customer Analysis

A company uses Customer Data Integration to associate

transactions from multiple systems with the proper customers.

The company uses D-U-N-S Numbers to consolidate

information from different branches at the headquarters

level. To ensure that as many records as possible have a

D-U-N-S Number, it uses D&B remote resolution services

for inputs that do not match the Common Customer

Directory.

1. The customer database load process creates a flat file

with records from multiple source systems. It places this in

a directory assigned to receive such files. The Customer

Integration Manager scanning and file transport modules

(SST and FTM) notice the file,transfer it to a work area,

and call Customer Integration Manager's matching module.

2. Customer Integration Manager parses andstandardizes each record and looks for a match in the

Common Customer Directory. Records that match an existing

entry are coded with the site and ultimate parent D-U-N-S

Number and accumulated in a flat file.

3a. Records that do not match a Common Customer

Directory entry are accumulated in a (different) flat file.

When processing is complete,this file is sent to a designated

Integrated Customer Relationship Management

16

Lead Processing

Inquiry from Customer

Phone call to Customer

Call Center

1

234

MarketingDatabase



Manager

CommonCustomer

Directory

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directory.SST and FTM send it to D&B for remote resolution.

If the D&B system finds a match on its master database,

it outputs the original record and the D&B site record. If

there is no match, it sends the record for manual research

and outputs the original record with an appropriate flag.

When the process is complete, the files are placed in a

directory where SST and FTM sends them back to

Customer Integration Manager.

3b. Customer Integration Manager adds the returned records

to the Common Customer Directory,codes them with LSIDs,

and sends the coded records to a flat file.

4.Customer Integration Manager sends the output fileswith coded records to the customer database load area for

additional processing.Most records contain a site and

headquarters D-U-N-S Number that will be used for

consolidation. Records that did not match with D&B are

consolidated using the LSID.

Interactive Customer Lookup During Order Entry

A company's order entry system uses Customer

Integration Manager to determine whether an order is from

an existing customer and if credit is available.This firm

has not changed its operational systems to store the LSID

so it must use the Common Customer directory as a

cross-reference table.

1. The call center receives a telephone call from a cus-

tomer wishing to place an order. The caller knows his

firm has ordered before, but does not have an account

number available. The order entry agent enters the com

pany name and address into the order entry system and

selects a 'customer search' option. The order entry sys

tem sends the name and address to the Customer

Integration Manager API via Java. Customer Integration

Manager parses and standardizes the input and looks for

matches in the CommonCustomer Directory. It finds

several that exceed the specified confidence threshold.

2. Customer Integration Manager sends the nameaddress, telephone number and LSID of each matched record

to the order entry system.The order entry system displays

the records to the agent,who reviews them with the caller

There is no match, so the agent asks for an alternate

address and searches for matches on those.When the rightrecord is located,the order entry system issues a command

for Customer Integration Manager to add the original address

to the Common Customer Directory and link it to the alter

nate address.This will allow the system to identify the com

pany automatically if a future caller uses either address.

3. The order entry system issues a direct SQL query to the

Common Customer Directory,selecting all records with

the specified LSID that represent credit system accounts

There are several such records, relating to different

accounts that the customer has established for different

departments at the same site.

17

Consolidated Sales Data

D&B Remote

1

Multi-sourceData Extract

CustomerDatabase Load

3a3b2

4

CodedRecords

D&BDatabase



Manager

Directory

CommonCustomer

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4. The order entry system extracts the account numbers

from the returned records and submits them to the cred-

it system. The credit system evaluates these accounts

and returns an approval to the order processing system.

The agent completes the order.

Implementation

Every Customer Integration Manager installation is

tailored to the customer's requirements with help from

a dedicated team of D&B consultants. Most imple-

mentations include the following stages:

Install the Customer Integration software.Preliminarysteps include establishing a home directory, setting data-

base access rights, and installing Java Virtual Machine

(Java 2 SDK Standard Edition version 1.4.1). The user

then runs an automated installation Wizard that will

The Graphical User Interface (GUI) lets the user easilyset up and manage operations and administrative

functions. D&B consultants will provide advice on proper

settings. The GUI controls technical details like directory

locations, and business decisions such as which records are sent

to D&B for remote resolution. Users create

visual workflows to define matching, file processing,

input and output formats, remote resolution, logging and

Set up the Common Customer Directory.D&B consul-tants will help to build the data tables,design special views

and indexes, and determine which records to load. The

initial records will be selected from the D&B master

database. This process also includes matching your

specific records against D&B data, and conducting manual

and remote resolution as needed.Customer Integration

Manager uses a relational database with the

following categories: matching, data append, and

operational. The Common Customer Directory is a set of

relational database tables with predefined data

Develop interfaces with specific applications. Details

will depend on the situation, but tasks will generally

include researching existing data sources and systems,

developing extract programs for batch feeds, modifying

online systems to communicate with the Customer

Integration Manager APIs, and making other changes

needed to use Customer Integration Manager outputs.

Implementation time can vary from a few hours for sim-

ple batch matching to several days for a process includ-

ing remote connections to D&B. Projects requiring

changes to the client's in-house systems may take

longer.

Monthly Update

D&B provides Customer Integration Manager clients

with a monthly update for D&B records in the Common

Customer Directory. This can be sent electronically or by

tape, CD, orother physical media. The update file will include

changed records for the primary Common Customer

Directory table which contains matching data,and complete

replacements for the otherD&B database tables.

Interactive Customer Lookup

18

1OrderProcessing

System

4

Conversation with Customer

Credit System

2

3



Manager

Common

CustomerDirectory

prompt the user for the required information.

notifications.

structures for matching.

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Customer Integration Manager includes a monthly

update utility with scripts to control the process.This script

drops indexes and tables and later recreates them,records

each step in a log file,and notifies an operator via email when

the process is complete or an error occurs.The process can

restart from the point of failure if necessary.The system

stores detailed information on changes to individual

records, with separate files for records that have been

added, updated and deleted.

SupportD&B professional services staff supports Customer

Integration Manager clients during and after

implementation. Technical assistance is provided by email,

telephone, and in person. Clients receive a prompt response

during normal business hours.Training is tailored to each

implementation . D&B usually creates a custom training

system with the client's own data. Most training is

conducted at the client's office.Clients also receive detailed

written documentation.

Summary

Customer Integration Manager provides a comprehensive,

flexible solution for business customer data integration.

It combines sophisticated matching technology, your

organization's internal customer knowledge, and valida-

tion against D&B data, to produce the most thorough

relationship identification available. It supports both

batch and online processes, allowing a single system to

serve all customer data integration requirements. It can

provide a central cross-reference file to link account

numbers in different source systems,or generate a single

customer ID for all systems to use internally. It combines

the efficiency of in-house operation with the accuracy of

up-to-the-minute external validation data. The system is

built on industry-standard databases, hardware and

Java APIs, making it simple to integrate with

existing corporate infrastructures. Perhaps most

important, it links your data with the worldwide

resources of D&B, whose D-U-N-S Number opens the

door to an unmatched range and depth of business

customer information.

19Customer Integration Manager Technical White Paper

Monthly Update Process

D&B adds, changes,deactivates

Monthly Update Utility

Old CommonCustomer Directory

New CommonCustomer Directory

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