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WHITE PAPER: CRM




WHITE PAPER /
High Data Quality in the CRM
(Customer Relationship Management) System:
the proverbial icing on the cake

The goal of introducing a CRM (Customer Relationship Manage-
ment) system is to optimize and stabilize the relationships with exist-
ing and future customers in the long-term. The key to a satisfactory
relationship for both sides is not only an intelligent CRM system but
also the high quality of the data it contains.
There are indications of sub-optimum customer data quality if the
return rate of mailshots is relatively high as a result of incorrect or
incomplete addresses, or customers complain about multiple deliver-
ies of the same advertising mail. For good measure, it is embarrass-
ing if discriminatory comments can be read in the address line of a
customer, because importance was not attached to the „hygiene“ of
the name and address components. Even if the in-house staff have
no confidence in the database and manually check each entry be-
fore the customer is contacted, this should also be considered as an
indication of poor data quality. On the basis of points stated here,
it becomes evident that data quality in the CRM system is just as
important as the system itself. If this is not the case, the hoped-for
effect of long-term customer bonding combined with an increasing
efficiency of the work carried out with customer data will not arise.
Various use scenarios of a CRM system are considered in the fol-
lowing. The areas of focus are the relationship of the data quality
and the consequences of poor data quality. Furthermore, a practical
solution approach for providing a newly created or existing CRM
system with high-quality data and maintaining this status quo is pre-
sented.


—
All company and product names and logos used in this document are trade names and/or registered trademarks of the

respective companies.




                                                                                                                               Page 1
WHITE PAPER: CRM



Contents

               In touch with your customers                         PAGE 3


               Important components for the                         PAGE 4
               success of a CRM system

              The perfect couple:                                   PAGE 6
              CRM and Data quality

               Data quality in the CRM: how to                      PAGE 8


               Initial data cleansing                              PAGE 10


              « first time right » -                               PAGE 13
              the Data Quality Firewall

               Data Maintenance: Automated measures for maintai-   PAGE 15
               ning the data quality standard

              It’s time to get on board:                           PAGE 16
              The Data Quality Audit




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                         Page 2
WHITE PAPER: CRM



  In touch with your customers
  The awareness that the introduction of a CRM (Customer Relationship
  Management) system is a key factor for the long-term success of the company
  has rapidly developed in the managerial levels of many companies in the past
  few years.

  Irrespective of the supplier and the components of       HERE ARE A FEW EXAMPLES:
  the CRM system which are used, the focus is always
  on customer orientation and the underlying service       –   A satisfied customer is prepared to recom-
  concept.                                                     mend the supplier and his products through
  If the introduction of a CRM system is considered from       simple word-of-mouth propaganda.
  an economic perspective, it quickly becomes clear
  that relationship management is associated with con-     –   In a long-standing, satisfactory relationship
  cepts such as the desire for long-term business rela-        between the customer and the supplier, the
  tionships and the economic security connected with           customer may make suggestions for improving
  this. Furthermore, a CRM system should contribute to         products, in order to call attention to changing
  the stabilization of the business contact.                   demands in the market.


WELL-MAINTAINED BUSINESS RELATION-                         –   A satisfied customer is more tolerant towards
SHIPS AS WELL AS RELATIONSHIPS WITH                            price increases than potential customers who
CUSTOMERS, I.E. A STABLE NETWORK OF                            are still comparing similar products and serv-
RELATIONSHIPS, HAVE A VARIETY OF VERY                          ices of different suppliers.
POSITIVE EFFECTS ON THE INDIVIDUAL
COMPANY.                                                   –   If there is an existing business relationship with
                                                               a customer, the customer will contact the sup-
                                                               plier if he is dissatisfied with a product or a
  Well-maintained business relationships as well as            service, in order to indicate the deficiencies. As
  relationships with customers, i.e. a stable network of       a result, the supplier has the opportunity to opti-
  relationships, have a variety of very positive effects       mize the product and performance. In the neg-
  on the individual company. .                                 ative case, the customer would simply change
                                                               supplier without informing the supplier about
                                                               the perceived deficiencies of the product.




  © UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                  Page 3
WHITE PAPER: CRM



Important components for
the success of a CRM system
The above examples make clear that the customer is always the centre of the
interest in a CRM system, since direct and indirect gains can be achieved in
the long-term through a satisfactory relationship.

In this respect, there are various areas in a CRM     OPERATIVE CUSTOMER RELATIONSHIP MANAGEMENT
system which are designed to help satisfy a wide      In contrast to analytical CRM, operative CRM
variety of customer needs in the expected form        covers the areas of sales, marketing and service.
and in an appropriate manner. Any information         In other words: All the employees who are in
obtained can therefore be evaluated, in order to      direct or indirect contact with the customer use
use it in marketing campaigns or other Business       operative CRM.
Intelligence-based analyses.
A difference is made between an operative CRM         In marketing, this actually means that e.g. there
and an analytical CRM.                                are possibilities in campaign management to fil-
                                                      ter out the right target groups for the respective
ANALYTICAL CUSTOMER RELATIONSHIP MANAGEMENT           campaigns. (The evaluations of analytical CRMs
Analytical CRM is used to consider all the possible   normally provide indications of the correct filters.)
customer data for evaluations within the sphere       In this respect, the right customers, the appropriate
of Business Intelligence. The term Customer Data      information and service offer, the selection of the
Warehouse is also used to some extent. This shows     optimum communication channel, etc. are the main
that analytical CRM concerns a «snapshot» of          concerns. The goal is that the presented information
the CRM data for the analysis and not the data        reaches the right customer target group. The solic-
of the actual live system. The data is stored in a    ited customers should be motivated to examine the
specially designed system, as is the data of a        respective contents of the campaigns and to identify
Data Warehouse. It can be evaluated via a large       the added value which the information (or the prod-
number of different dimensions. The keyword here      uct) creates for themselves or their company.
is Online Analytical Processing (OLAP), which is
also used in the Data Warehouse.




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                             Page 4
WHITE PAPER: CRM



  Sales uses the operative CRM for various tasks.         The third area which makes intensive use of the
  Personal contact with the customer figures large, in    CRM system is the service area.
  order to develop and maintain a strong customer         The individual customer requirements are consid-
  relationship. Functions such as the integration of      ered to a particularly large degree in this environ-
  e-mail clients, calendars or similar features are       ment, the customer is accompanied through the
  indispensable here. However, information from the       different stages of the relationship. Complaint man-
  CRM is also used e.g. to update sales opportuni-        agement and customer support are also important
  ties. It can also be evaluated why the customer         issues here.
  rejected the offer (lost order analysis) or why the
  business relationship ended. A CRM system is also       Finally, a CRM system can be used interdepartmen-
  used as a “logbook”, in which all the activities with   tally and across areas as a control instrument for
  a customer are recorded. As a result, colleagues        business processes or can offer valuable assistance
  can very quickly gain an overview of all the cor-       for compliance with business rules.
  respondence with the customer.
                                                          In the context of the importance of a profession-
                                                          al Customer Relationship Management and the
THE EMPLOYEE IN DIRECT CUSTOMER
                                                          introduction of an appropriate CRM system, it is
CONTACT IS THE CALLING CARD OF THE
                                                          essential to keep one central aspect in mind: the
COMPANY, BECAUSE HE OR SHE IS SYN-
                                                          employee in direct customer contact is the calling
ONYMOUS WITH THE QUALITY OF THE
                                                          card of the company, because he or she is synony-
PRODUCT AND SERVICE FOR THE OUTSIDE
                                                          mous with the quality of the product and service
WORLD.
                                                          for the outside world. It is precisely here that enor-
                                                          mous, usually inactive potentials can be activated
                                                          for the benefit of satisfied customers on the basis of
  The CRM system is also used to dynamically gener-       an efficient CRM system.
  ate reliable forecast analyses. These are extremely
  important for defining further business strategies.




  © UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                Page 5
WHITE PAPER: CRM



The perfect couple:
CRM and Data quality
Regardless of whether an analytical or operative CRM is implemented, the
above described areas of application indicate the importance of correct data,
i.e. data quality.

In an analytical CRM, a high data quality is indispen-
 n                                                         In an operative CRM, it is important that the contact
sable, in order to be able to carry out appropriate        data of the customer is correct, so that appropriate
analyses in the first place, not to falsify them and -     marketing campaigns and the service offer reach their
building on this - to make the right strategic decisions   target, i.e. the customer.
in the long-term.

IN CONCRETE TERMS, DATA QUALITY MEANS:




  –   Correct address data, also in the inter-              –   A duplicate-free customer data stock, i.e.
      national environment, so that written cor-                there is really only a single instance of the
      respondence reaches the recipient. In this                customer in the database, in order:
      regard
                                                                »   not to send the information several times
      »   Address data must be updated if places                    in mailshots and save on postage costs
          or streets are renamed
                                                                »   not to unnecessarily annoy repeatedly
      »   Relocations must be recorded and the                      solicited customers in marketing cam-
          addresses updated                                         paigns and therefore provoke customer
                                                                    losses and lost sales
      »   No customer relationships are main-
          tained with deceased persons and                      »   to be able to make reliable statements
                                                                    about sales opportunities and forecast
      »   Company changes (mergers, reloca-                         analyses
          tions, etc.) must be recorded
                                                                »   to design service more efficiently by hav-
                                                                    ing all the relevant information available
                                                                    for direct customer contact




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                  Page 6
WHITE PAPER: CRM



  Against this background, it becomes evident that      If all these aspects are not considered in a CRM
  data quality, i.e. correct and duplicate-free data,   system, the defective quality of the data can
  is an important prerequisite for the so-called        quickly the tip the scales. Analyses in Business
  «Single View of Customer» or «Single Point of         Intelligence produce incorrect conclusions, cus-
  Truth», because only optimum data really allows       tomers are dissatisfied with the service and mar-
  all the data relating to a customer to be com-        keting campaigns and also terminate business
  pressed into one data record, thereby enabling a      relationships in the worst case.
  comprehensive view of a customer.
                                                        Poor data quality can also have a direct effect
IT BECOMES EVIDENT THAT DATA QUALITY,                   on the motivation of the company’s employees.
I.E. CORRECT AND DUPLICATE-FREE DATA,                   They may not satisfy the needs of the customers to
IS AN IMPORTANT PREREQUISITE FOR THE                    the expected extent, since the information in the
SO-CALLED «SINGLE VIEW OF CUSTOMER»                     CRM system is not consistent.
OR «SINGLE POINT OF TRUTH», BECAUSE
ONLY OPTIMUM DATA REALLY ALLOWS                         Duplicate data records of customers which con-
ALL THE DATA RELATING TO A CUSTOMER                     tain information required for customer satisfaction
TO BE COMPRESSED INTO ONE DATA                          are an example here. It is the employee who has
RECORD, THEREBY ENABLING A COMPRE-                      to listen to the troubles of frustrated customers.
HENSIVE VIEW OF A CUSTOMER.                             And becomes dissatisfied at the same time.

                                                        The direct connection between reliable data from
  This view must also have been authorized for the      the CRM system and employee motivation is
  employees of the various departments within a         therefore proven.
  company.




  © UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                           Page 7
WHITE PAPER: CRM



Data quality in the CRM: how to
REGARDLESS OF WHETHER                                                the requisite high data quality can be achieved in
                                                                     three sub-processes:
–    a completely new CRM system is to be put in place,
                                                                     1. Initial data cleansing
–    the data quality of an existing CRM system is to                2. «first time right» and mechanisms which inter-
     be optimized,                                                      cept poor data quality when the data is cre-
                                                                        ated or edited (Data Quality Firewall)
–    or two or more independent systems are to be                    3. Use of data maintaining as a measure to preserve
     combined into a single CRM system,                                 a high data quality standard



THE DATA QUALITY PROCESS OF UNISERV SHOWS
HOW THE ABOVE THREE STEPS ARE CONNECTED.



                                                                                            Implementation of Data
                                                            Profiling                       Profiling and investigation
                                                                                            of the data

    Initial clean-up        1.



                                                                                            Analysis of the data quality and cleans-
                                                          Cleansing                         ing of customer, transaction,
                                                                                            order, financial, statistical data ...



       Integration of external data.
       Provision of data for external systems.


                                                      CLOSED DATA
                                                      QUALITY CYCLE
                                                                                                              Securing the data
                  3.             Maintaining                                  Real-Time Check                 quality directly at input



         Application of change
         reports from third-party
         companies. (anti-ageing)
                                                          Monitoring                                             2.


                                 Continuous monitoring of the data quality and compliance with the
                                 business rules for transaction, order, financial, statistical data ...




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                                       Page 8
WHITE PAPER: CRM



  The data quality process of Uniserv shows how         In this respect, it not only concerns correctly writ-
  the above three steps are connected.                  ten addresses or duplicate data records but also
                                                        learning about the structure of the data to be
IT NOT ONLY CONCERNS CORRECTLY                          migrated and checking the existing business rules.
WRITTEN ADDRESSES OR DUPLICATE DATA                     This step is typically implemented in a data
RECORDS BUT ALSO LEARNING ABOUT                         quality audit.
THE STRUCTURE OF THE DATA TO BE MI-
GRATED AND CHECKING THE EXISTING                        Downstream monitoring is advisable for con-
BUSINESS RULES. THIS STEP IS TYPICALLY                  stant determination and verification of the status
IMPLEMENTED IN A DATA QUALITY AUDIT.                    quo of the data quality. Compliance with the
                                                        business rules can be automatically checked
                                                        here and critical threshold values specified,
  It is advisable to obtain an overview of the qual-    in order to be able to carry out optimization
  ity of the data in a first step, so that an initial   measures in real-time. Such threshold values
  cleansing oriented towards results is possible.       could also be key performance indicators (KPI),
                                                        which provide information about the status quo
                                                        of defined company goals.




  © UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                             Page 9
WHITE PAPER: CRM



1. Initial data cleansing
First of all, the initial cleansing of the data is of prime importance. In this respect,
the entire database is checked and cleansed in a batch run. The number of
different data sources or the countries which the data originates from are irrel-
evant here.

THE TYPICAL PROCEDURE FOR THIS INITIAL CLEANSING IS     –    The name components are analyzed.
AS FOLLOWS:                                                  Very complex name lines which either consist
                                                             of several individuals or include the company
–    The data is converted to a standardized format.         name with the department and contact are
     Example: Standardized format for telephone              analyzed. The analysis establishes whether the
     numbers.                                                data concerns consumer data or company
                                                             data. All the elements of the name line are also
 ++49 72319360                                               written to specially assigned fields, so that e.g.
                                                             analyses of academic titles or legal forms of the
 0049-7231-9360               0049-7231-9360
                                                             company can be carried out.
                                                             Example: UNISERV GmbH
 +49 (0) 72 31/9 36 – 0


                                                                                        Company name:
–    The field contents of different data sources are                                    UNISERV
     assigned to standard fields.                           UNISERV GmbH
     Example: The name of the contact person is in                                      Legal form:

     fields with different names in each data source.                                    GmbH



Data source A :

Name:              Pfeiffer, Roland


Data source B :
First name:        Roland

Last name:         Pfeiffer


Data source C :
Contact :          Roland Pfeiffer




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                Page 10
WHITE PAPER: CRM



–    A validation of the addresses is carried out.      –    The addresses are converted to specific formats.
     A postal validation is carried out irrespective         In certain countries, e.g. France, the address must
     of whether national or international addresses          be formatted according to the specifications of the
     are concerned. In this respect, the postcode,           national postal authorities, in order to be able to
     place, street and house number are checked              take advantage of postage rate optimization meas-
     for correctness. If possible, missing address           ures for the cheapest possible delivery options.
     components are corrected and / or added.                Example of an address from France:
     Officially renamed streets and places are
     automatically updated. PO box validation            Input                          Formatted output

     and bulk customer postcode validation are            Stephane Petit                 STEPHANE PETIT
     also available for certain countries.
                                                          Immeuble de corbusier          IMMEUBLE DE CORBUSIER
     Example:                                             Esc B

    Rastaterstrasse 13          Rastatter Str. 13         12 Route de Locmine            ESCALIER B

                                                          56150 BAUD                     12 ROUTE DE LOCMINE
    75197 Forzheim              75179 Pforzheim


                                                                                         56150 BAUD
–    Addresses of movers are updated.
     Around 8 million people change their place
     of residence in Germany each year. Only a
     very few of them actively advise of their new      –    The addresses are enhanced with additional
     address. The data records of the individuals            information.
     concerned can be updated initially or subse-            The addresses can be enhanced with rel-
     quently periodically (see point 3) by means of a        evant information as required. This could
     relocation check over the entire database.              be geocoordinates, but sector codes or in-
                                                             house, user-defined information can also be
                                                             attached to the data records.
                                                             For example:


                                                            Rastatter Str. 13               Y coordinate +04889883

                                                            75179 Pforzheim                 X coordinate +00866723




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                Page 11
WHITE PAPER: CRM



–   Duplicates are identified.                          –    The “Golden Record” is formed.
    Potential duplicates are identified according            The formation of a “Golden Record” is funda-
    to individually customized search algorithms.            mental, particularly when data comes from a
    Suitable business rules can be applied in the            variety of sources which have further relevant
    search, so that subsequent elimination can               contents attached in addition to the postal
    take place automatically to some extent. The             information. As a result, there is the possibility
    duplicates are also evaluated, so that state-            of transferring all the information from the next
    ments about the “certainty”, i.e. probability            duplicate to the head duplicate, i.e. to one
    of a duplicate can be made. It goes without              data record. Even if duplicate data records do
    saying that standardized matching schemes                not have to be eliminated, marking (flagging) is
    which can be applied to consumer or busi-                possible, so that the information contained in a
    ness data are available here. It is also pos-            duplicate can be displayed to the subsequent
    sible to incorporate further individual fields in        user of the CRM system.
    additional free fields in the duplicate search.          Example: The second data record has an addi-
    For example:                                             tional field with coordinates which are to be
                                                             attached to the first data record. If the second
Data record 1                     Data record 2              data record is deleted from the database, the
                                                             first data record, which is now the “Golden
Roland Pfeiffer                    R. Pfeifer
                                                             Record”, also includes this information.
Rastatter Str. 13                  Rastaterstrasse 31
                                                         Data record 1                   Data record 2
75179 Pforzheim                    75179   Forzheim
                                                         (head duplicate)                (next duplicate)

                                                            Roland Pfeiffer               R. Pfeifer

    Comparison of the two data records pro-                 Rastatter Str. 13             Rastaterstrasse 31

    vides a high measure of similarity, since the           75179 Pforzheim               75179    Forzheim
    name, street, house number and place differ.            Y coordinate +04889883        Y coordinate +04889883
    However, the difference in this example and
                                                            X coordinate +00866723        X coordinate +00866723
    with the selected matching algorithm is not
    great, so that the data records are identified
    as a single block.




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                                  Page 12
WHITE PAPER: CRM



2. « first time right » -
the Data Quality Firewall
It is important to specify certain standards after the transfer of the initially cleansed
data stock. Only in this way can the obtained high data quality be preserved.
A variety of options from the online area present themselves here:

Firstly, the user of the CRM system can ensure that     Since work is carried out under high pressure of
certain input rules are complied with, e.g. street      time at peak periods, especially in call centres,
names should only be entered in the fields pro-         address validation must take place very quickly.
vided. A syntax check is also possible for fields for
telephone numbers or e-mail addresses. In addi-           NO MATTER WHICH TECHNOLOGY IS
tion, there is the possibility of checking the stated     USED, THE POSSIBILITY OF A SIMPLE,
address for correctness.                                  QUICK AND ERROR-TOLERANT SEARCH
                                                          FOR ANY EXISTING CUSTOMER DATA IS
This could be important, e.g. if the address is only      FUNDAMENTAL.
given to a call centre by telephone and errors
quickly arise in the notation or because of different   A rapid entry client which completes the address
interpretations of what was heard or typing errors.     components after input of the initial letters or num-
If the information received over the telephone is       bers can be used as an alternative.
incorrect or unambiguous, the employee can also
immediately ask for missing additional information      No matter which technology is used, the possibility
such as the town district, in order to be able to       of a simple, quick and error-tolerant search for any
transfer a postally correct address to the system.      existing customer data is fundamental. This func-
                                                        tion is not used if matching takes too long or does
The performance of the underlying technology is         not furnish the desired results. The Data Quality
the decisive factor for acceptance here.                Firewall is by-passed.




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                             Page 13
WHITE PAPER: CRM



  An everyday example demonstrates this: if the           If the company or individual already exists in the
  search for information in the most well-known           database, the employee receives a relevant indica-
  Internet search engines, Google or Yahoo,               tion via the input mask.
  took longer than the typical 0.3 seconds, these
  search engines would not be used on account of          An error-tolerant search is also appropriate here,
  the slowness.                                           so that the respective data record can be found in
                                                          spite of hearing errors or synonyms or incomplete
UNISERV HAS CREATED DQ CONNECTORS                         company names.
FOR THE MOST IMPORTANT CRM SYS-                           It goes without saying that this so-called implicit
TEMS, SUCH AS SAP CRM, MICROSOFT                          search also has to take place very quickly and pre-
DYNAMICS CRM, SIEBEL AS WELL AS UP-                       cisely, so that the work-flow of the employee in the
DATE.SEVEN AND SALESFORCE.COM                             CRM system is not impeded.

                                                          These requirements for the Data Quality Firewall
  The fully automatic prevention of new duplicates is     are implemented by means of the DQ Connectors.
  also important. Here too, there is the possibility of   In conjunction with development partners, Uniserv
  checking whether the customer is already recorded       has created DQ Connectors for the most impor-
  in the system when the data is created.                 tant CRM systems, such as SAP CRM, Microsoft
  If this is the case, a new customer account does        Dynamics CRM, Siebel as well as update.seven
  not have to be created. The existing information        and salesforce.com, which enable the integration
  can even be enhanced by the current process. This       of data quality mechanisms at data acceptance
  search runs in the background without being spe-        and for record-by-record processing. As a result,
  cifically triggered by the employee at each initial     nothing stands in the way of these functions, which
  data creation or change of the address data.            are important for implementing high data quality in
                                                          the CRM system.




  © UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                            Page 14
WHITE PAPER: CRM



  3. Data Maintenance: Automated
  measures for maintaining the data
  quality standard
  In spite of the initial data cleansing and mechanisms to maintain the status quo
  of the data quality, it is good policy to carry out a periodic check of the overall
  database.

  This is also necessary if the databases are to       These periodic checks of the overall database
  be consolidated e.g. after corporate takeovers.      should ideally be executed as a batch process.
  Another scenario is a periodic check for street      This guarantees that all the data complies with
  and place renaming.                                  a common data quality standard at specified
                                                       intervals.
A DATA QUALITY HIGH ENOUGH TO AC-
COMPLISH THE ACTUAL TASKS OF THE                       A data quality high enough to accomplish the actu-
CRM SYSTEM CANNOT BE ASSUMED UN-                       al tasks of the CRM system cannot be assumed until
TIL THE THREE PROCESS STEPS DESCRIBED                  the three process steps described here have been
HERE HAVE BEEN IMPLEMENTED AND                         implemented and adopted as practice, thereby
ADOPTED AS PRACTICE, THEREBY ENA-                      enabling the CRM system to reach its full potential
BLING THE CRM SYSTEM TO REACH ITS                      and provide a return on investment.
FULL POTENTIAL AND PROVIDE A RETURN
ON INVESTMENT.                                         The evaluations in the analytical CRM are now
                                                       on a sound basis. The data in the operative
                                                       CRM permits a customer-oriented approach in
  Relocations must be tracked and maintained,          all areas. Finally, the customer relationships are
  and the data records of deceased customers           strengthened in the long-term. The confidence
  should be flagged at least. The requirement for      of the company’s employees in the quality of
  enhancement of the existing data with addition-      the data increases at the same time. This means
  al information is also not excluded.                 that an additional check of the data is no longer
                                                       required. The direct results are an increase in
                                                       efficiency and reduction in costs.




  © UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                         Page 15
WHITE PAPER: CRM



It’s time to get on board:
The Data Quality Audit
The Uniserv DQ Audit presents itself, in order to be able to make statements
about the status quo of the in-house data in the CRM system.

The audit is the first step with clear goals in mind
for sound decision-making and marks your per-             For further information
sonal introduction to the project «Data Quality in        please visit our web page
your CRM System».                                         www.uniserv.com or contact us directly:

During the audit, the quality of the addresses is
primarily evaluated with the support of the data
quality tools from Uniserv. In a second step, there
is the possibility of getting to the root of the possi-   We are looking forward for advising and sup-
ble causes of the deficient data quality in a proc-       porting you through your project.
ess analysis. So the best thing to do is to Contact
us right away!




© UNISERV GmbH / +49 7231 936-0 / All rights reserved.                                              Page 16
WHITE PAPER: CRM



Uniserv
Uniserv is the largest specialised supplier of data quality solutions in Europe
with an internationally usable software portfolio and services for the quality as-
surance of data in business intelligence, CRM applications, data warehousing,
eBusiness and direct and database marketing.

With several thousand installations worldwide, Uniserv
supports hundreds of customers in their endeavours to
map the Single View of Customer in their customer data-                                          DATA
base. Uniserv employs more than 110 people at its head-                                       MIGRATION
                                                                                               PROJECTS
quarters in Pforzheim and its subsidiary in Paris, France,                 E-COMMERCE
and serves a large number of prestigious customers in all
sectors of industry and commerce, such as ADAC, Al-               ERP

lianz, BMW, Commerzbank, DBV Winterthur, Deutsche
Bank, Deutsche Börse Group, France Telecom, Green-
                                                                                                          COMPLIANCE
peace, GEZ, Heineken, Johnson & Johnson, Nestlé,
                                                                 CRM
Payback, PSA Peugeot Citroën as well as Time Life and
Union Investment.



Further information is available                                                                 SOA


at www.uniserv.com                                              DIRECT
                                                               MARKETING                                    MDM/CDI


                                                                                              ON-PREMISE/
                                                                                              ON-DEMAND




                                                                             BI/BDW



                                                                                        CPM




Experience:                              Market position:                      Employees:
OVER 40 YEARS                            LARGEST                               MORE THAN 110 PEOPLE
                                         EUROPEAN SUPPLIER


UNISERV GmbH                                                                   Contact:
Rastatter Straße 13 • 75179 Pforzheim • Germany • T +49 7231 936-0 •           +49 7231 936-0
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Data Quality and CRM

  • 1. WHITE PAPER: CRM WHITE PAPER / High Data Quality in the CRM (Customer Relationship Management) System: the proverbial icing on the cake The goal of introducing a CRM (Customer Relationship Manage- ment) system is to optimize and stabilize the relationships with exist- ing and future customers in the long-term. The key to a satisfactory relationship for both sides is not only an intelligent CRM system but also the high quality of the data it contains. There are indications of sub-optimum customer data quality if the return rate of mailshots is relatively high as a result of incorrect or incomplete addresses, or customers complain about multiple deliver- ies of the same advertising mail. For good measure, it is embarrass- ing if discriminatory comments can be read in the address line of a customer, because importance was not attached to the „hygiene“ of the name and address components. Even if the in-house staff have no confidence in the database and manually check each entry be- fore the customer is contacted, this should also be considered as an indication of poor data quality. On the basis of points stated here, it becomes evident that data quality in the CRM system is just as important as the system itself. If this is not the case, the hoped-for effect of long-term customer bonding combined with an increasing efficiency of the work carried out with customer data will not arise. Various use scenarios of a CRM system are considered in the fol- lowing. The areas of focus are the relationship of the data quality and the consequences of poor data quality. Furthermore, a practical solution approach for providing a newly created or existing CRM system with high-quality data and maintaining this status quo is pre- sented. — All company and product names and logos used in this document are trade names and/or registered trademarks of the respective companies. Page 1
  • 2. WHITE PAPER: CRM Contents In touch with your customers PAGE 3 Important components for the PAGE 4 success of a CRM system The perfect couple: PAGE 6 CRM and Data quality Data quality in the CRM: how to PAGE 8 Initial data cleansing PAGE 10 « first time right » - PAGE 13 the Data Quality Firewall Data Maintenance: Automated measures for maintai- PAGE 15 ning the data quality standard It’s time to get on board: PAGE 16 The Data Quality Audit © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 2
  • 3. WHITE PAPER: CRM In touch with your customers The awareness that the introduction of a CRM (Customer Relationship Management) system is a key factor for the long-term success of the company has rapidly developed in the managerial levels of many companies in the past few years. Irrespective of the supplier and the components of HERE ARE A FEW EXAMPLES: the CRM system which are used, the focus is always on customer orientation and the underlying service – A satisfied customer is prepared to recom- concept. mend the supplier and his products through If the introduction of a CRM system is considered from simple word-of-mouth propaganda. an economic perspective, it quickly becomes clear that relationship management is associated with con- – In a long-standing, satisfactory relationship cepts such as the desire for long-term business rela- between the customer and the supplier, the tionships and the economic security connected with customer may make suggestions for improving this. Furthermore, a CRM system should contribute to products, in order to call attention to changing the stabilization of the business contact. demands in the market. WELL-MAINTAINED BUSINESS RELATION- – A satisfied customer is more tolerant towards SHIPS AS WELL AS RELATIONSHIPS WITH price increases than potential customers who CUSTOMERS, I.E. A STABLE NETWORK OF are still comparing similar products and serv- RELATIONSHIPS, HAVE A VARIETY OF VERY ices of different suppliers. POSITIVE EFFECTS ON THE INDIVIDUAL COMPANY. – If there is an existing business relationship with a customer, the customer will contact the sup- plier if he is dissatisfied with a product or a Well-maintained business relationships as well as service, in order to indicate the deficiencies. As relationships with customers, i.e. a stable network of a result, the supplier has the opportunity to opti- relationships, have a variety of very positive effects mize the product and performance. In the neg- on the individual company. . ative case, the customer would simply change supplier without informing the supplier about the perceived deficiencies of the product. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 3
  • 4. WHITE PAPER: CRM Important components for the success of a CRM system The above examples make clear that the customer is always the centre of the interest in a CRM system, since direct and indirect gains can be achieved in the long-term through a satisfactory relationship. In this respect, there are various areas in a CRM OPERATIVE CUSTOMER RELATIONSHIP MANAGEMENT system which are designed to help satisfy a wide In contrast to analytical CRM, operative CRM variety of customer needs in the expected form covers the areas of sales, marketing and service. and in an appropriate manner. Any information In other words: All the employees who are in obtained can therefore be evaluated, in order to direct or indirect contact with the customer use use it in marketing campaigns or other Business operative CRM. Intelligence-based analyses. A difference is made between an operative CRM In marketing, this actually means that e.g. there and an analytical CRM. are possibilities in campaign management to fil- ter out the right target groups for the respective ANALYTICAL CUSTOMER RELATIONSHIP MANAGEMENT campaigns. (The evaluations of analytical CRMs Analytical CRM is used to consider all the possible normally provide indications of the correct filters.) customer data for evaluations within the sphere In this respect, the right customers, the appropriate of Business Intelligence. The term Customer Data information and service offer, the selection of the Warehouse is also used to some extent. This shows optimum communication channel, etc. are the main that analytical CRM concerns a «snapshot» of concerns. The goal is that the presented information the CRM data for the analysis and not the data reaches the right customer target group. The solic- of the actual live system. The data is stored in a ited customers should be motivated to examine the specially designed system, as is the data of a respective contents of the campaigns and to identify Data Warehouse. It can be evaluated via a large the added value which the information (or the prod- number of different dimensions. The keyword here uct) creates for themselves or their company. is Online Analytical Processing (OLAP), which is also used in the Data Warehouse. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 4
  • 5. WHITE PAPER: CRM Sales uses the operative CRM for various tasks. The third area which makes intensive use of the Personal contact with the customer figures large, in CRM system is the service area. order to develop and maintain a strong customer The individual customer requirements are consid- relationship. Functions such as the integration of ered to a particularly large degree in this environ- e-mail clients, calendars or similar features are ment, the customer is accompanied through the indispensable here. However, information from the different stages of the relationship. Complaint man- CRM is also used e.g. to update sales opportuni- agement and customer support are also important ties. It can also be evaluated why the customer issues here. rejected the offer (lost order analysis) or why the business relationship ended. A CRM system is also Finally, a CRM system can be used interdepartmen- used as a “logbook”, in which all the activities with tally and across areas as a control instrument for a customer are recorded. As a result, colleagues business processes or can offer valuable assistance can very quickly gain an overview of all the cor- for compliance with business rules. respondence with the customer. In the context of the importance of a profession- al Customer Relationship Management and the THE EMPLOYEE IN DIRECT CUSTOMER introduction of an appropriate CRM system, it is CONTACT IS THE CALLING CARD OF THE essential to keep one central aspect in mind: the COMPANY, BECAUSE HE OR SHE IS SYN- employee in direct customer contact is the calling ONYMOUS WITH THE QUALITY OF THE card of the company, because he or she is synony- PRODUCT AND SERVICE FOR THE OUTSIDE mous with the quality of the product and service WORLD. for the outside world. It is precisely here that enor- mous, usually inactive potentials can be activated for the benefit of satisfied customers on the basis of The CRM system is also used to dynamically gener- an efficient CRM system. ate reliable forecast analyses. These are extremely important for defining further business strategies. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 5
  • 6. WHITE PAPER: CRM The perfect couple: CRM and Data quality Regardless of whether an analytical or operative CRM is implemented, the above described areas of application indicate the importance of correct data, i.e. data quality. In an analytical CRM, a high data quality is indispen- n In an operative CRM, it is important that the contact sable, in order to be able to carry out appropriate data of the customer is correct, so that appropriate analyses in the first place, not to falsify them and - marketing campaigns and the service offer reach their building on this - to make the right strategic decisions target, i.e. the customer. in the long-term. IN CONCRETE TERMS, DATA QUALITY MEANS: – Correct address data, also in the inter- – A duplicate-free customer data stock, i.e. national environment, so that written cor- there is really only a single instance of the respondence reaches the recipient. In this customer in the database, in order: regard » not to send the information several times » Address data must be updated if places in mailshots and save on postage costs or streets are renamed » not to unnecessarily annoy repeatedly » Relocations must be recorded and the solicited customers in marketing cam- addresses updated paigns and therefore provoke customer losses and lost sales » No customer relationships are main- tained with deceased persons and » to be able to make reliable statements about sales opportunities and forecast » Company changes (mergers, reloca- analyses tions, etc.) must be recorded » to design service more efficiently by hav- ing all the relevant information available for direct customer contact © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 6
  • 7. WHITE PAPER: CRM Against this background, it becomes evident that If all these aspects are not considered in a CRM data quality, i.e. correct and duplicate-free data, system, the defective quality of the data can is an important prerequisite for the so-called quickly the tip the scales. Analyses in Business «Single View of Customer» or «Single Point of Intelligence produce incorrect conclusions, cus- Truth», because only optimum data really allows tomers are dissatisfied with the service and mar- all the data relating to a customer to be com- keting campaigns and also terminate business pressed into one data record, thereby enabling a relationships in the worst case. comprehensive view of a customer. Poor data quality can also have a direct effect IT BECOMES EVIDENT THAT DATA QUALITY, on the motivation of the company’s employees. I.E. CORRECT AND DUPLICATE-FREE DATA, They may not satisfy the needs of the customers to IS AN IMPORTANT PREREQUISITE FOR THE the expected extent, since the information in the SO-CALLED «SINGLE VIEW OF CUSTOMER» CRM system is not consistent. OR «SINGLE POINT OF TRUTH», BECAUSE ONLY OPTIMUM DATA REALLY ALLOWS Duplicate data records of customers which con- ALL THE DATA RELATING TO A CUSTOMER tain information required for customer satisfaction TO BE COMPRESSED INTO ONE DATA are an example here. It is the employee who has RECORD, THEREBY ENABLING A COMPRE- to listen to the troubles of frustrated customers. HENSIVE VIEW OF A CUSTOMER. And becomes dissatisfied at the same time. The direct connection between reliable data from This view must also have been authorized for the the CRM system and employee motivation is employees of the various departments within a therefore proven. company. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 7
  • 8. WHITE PAPER: CRM Data quality in the CRM: how to REGARDLESS OF WHETHER the requisite high data quality can be achieved in three sub-processes: – a completely new CRM system is to be put in place, 1. Initial data cleansing – the data quality of an existing CRM system is to 2. «first time right» and mechanisms which inter- be optimized, cept poor data quality when the data is cre- ated or edited (Data Quality Firewall) – or two or more independent systems are to be 3. Use of data maintaining as a measure to preserve combined into a single CRM system, a high data quality standard THE DATA QUALITY PROCESS OF UNISERV SHOWS HOW THE ABOVE THREE STEPS ARE CONNECTED. Implementation of Data Profiling Profiling and investigation of the data Initial clean-up 1. Analysis of the data quality and cleans- Cleansing ing of customer, transaction, order, financial, statistical data ... Integration of external data. Provision of data for external systems. CLOSED DATA QUALITY CYCLE Securing the data 3. Maintaining Real-Time Check quality directly at input Application of change reports from third-party companies. (anti-ageing) Monitoring 2. Continuous monitoring of the data quality and compliance with the business rules for transaction, order, financial, statistical data ... © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 8
  • 9. WHITE PAPER: CRM The data quality process of Uniserv shows how In this respect, it not only concerns correctly writ- the above three steps are connected. ten addresses or duplicate data records but also learning about the structure of the data to be IT NOT ONLY CONCERNS CORRECTLY migrated and checking the existing business rules. WRITTEN ADDRESSES OR DUPLICATE DATA This step is typically implemented in a data RECORDS BUT ALSO LEARNING ABOUT quality audit. THE STRUCTURE OF THE DATA TO BE MI- GRATED AND CHECKING THE EXISTING Downstream monitoring is advisable for con- BUSINESS RULES. THIS STEP IS TYPICALLY stant determination and verification of the status IMPLEMENTED IN A DATA QUALITY AUDIT. quo of the data quality. Compliance with the business rules can be automatically checked here and critical threshold values specified, It is advisable to obtain an overview of the qual- in order to be able to carry out optimization ity of the data in a first step, so that an initial measures in real-time. Such threshold values cleansing oriented towards results is possible. could also be key performance indicators (KPI), which provide information about the status quo of defined company goals. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 9
  • 10. WHITE PAPER: CRM 1. Initial data cleansing First of all, the initial cleansing of the data is of prime importance. In this respect, the entire database is checked and cleansed in a batch run. The number of different data sources or the countries which the data originates from are irrel- evant here. THE TYPICAL PROCEDURE FOR THIS INITIAL CLEANSING IS – The name components are analyzed. AS FOLLOWS: Very complex name lines which either consist of several individuals or include the company – The data is converted to a standardized format. name with the department and contact are Example: Standardized format for telephone analyzed. The analysis establishes whether the numbers. data concerns consumer data or company data. All the elements of the name line are also ++49 72319360 written to specially assigned fields, so that e.g. analyses of academic titles or legal forms of the 0049-7231-9360 0049-7231-9360 company can be carried out. Example: UNISERV GmbH +49 (0) 72 31/9 36 – 0 Company name: – The field contents of different data sources are UNISERV assigned to standard fields. UNISERV GmbH Example: The name of the contact person is in Legal form: fields with different names in each data source. GmbH Data source A : Name: Pfeiffer, Roland Data source B : First name: Roland Last name: Pfeiffer Data source C : Contact : Roland Pfeiffer © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 10
  • 11. WHITE PAPER: CRM – A validation of the addresses is carried out. – The addresses are converted to specific formats. A postal validation is carried out irrespective In certain countries, e.g. France, the address must of whether national or international addresses be formatted according to the specifications of the are concerned. In this respect, the postcode, national postal authorities, in order to be able to place, street and house number are checked take advantage of postage rate optimization meas- for correctness. If possible, missing address ures for the cheapest possible delivery options. components are corrected and / or added. Example of an address from France: Officially renamed streets and places are automatically updated. PO box validation Input Formatted output and bulk customer postcode validation are Stephane Petit STEPHANE PETIT also available for certain countries. Immeuble de corbusier IMMEUBLE DE CORBUSIER Example: Esc B Rastaterstrasse 13 Rastatter Str. 13 12 Route de Locmine ESCALIER B 56150 BAUD 12 ROUTE DE LOCMINE 75197 Forzheim 75179 Pforzheim 56150 BAUD – Addresses of movers are updated. Around 8 million people change their place of residence in Germany each year. Only a very few of them actively advise of their new – The addresses are enhanced with additional address. The data records of the individuals information. concerned can be updated initially or subse- The addresses can be enhanced with rel- quently periodically (see point 3) by means of a evant information as required. This could relocation check over the entire database. be geocoordinates, but sector codes or in- house, user-defined information can also be attached to the data records. For example: Rastatter Str. 13 Y coordinate +04889883 75179 Pforzheim X coordinate +00866723 © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 11
  • 12. WHITE PAPER: CRM – Duplicates are identified. – The “Golden Record” is formed. Potential duplicates are identified according The formation of a “Golden Record” is funda- to individually customized search algorithms. mental, particularly when data comes from a Suitable business rules can be applied in the variety of sources which have further relevant search, so that subsequent elimination can contents attached in addition to the postal take place automatically to some extent. The information. As a result, there is the possibility duplicates are also evaluated, so that state- of transferring all the information from the next ments about the “certainty”, i.e. probability duplicate to the head duplicate, i.e. to one of a duplicate can be made. It goes without data record. Even if duplicate data records do saying that standardized matching schemes not have to be eliminated, marking (flagging) is which can be applied to consumer or busi- possible, so that the information contained in a ness data are available here. It is also pos- duplicate can be displayed to the subsequent sible to incorporate further individual fields in user of the CRM system. additional free fields in the duplicate search. Example: The second data record has an addi- For example: tional field with coordinates which are to be attached to the first data record. If the second Data record 1 Data record 2 data record is deleted from the database, the first data record, which is now the “Golden Roland Pfeiffer R. Pfeifer Record”, also includes this information. Rastatter Str. 13 Rastaterstrasse 31 Data record 1 Data record 2 75179 Pforzheim 75179 Forzheim (head duplicate) (next duplicate) Roland Pfeiffer R. Pfeifer Comparison of the two data records pro- Rastatter Str. 13 Rastaterstrasse 31 vides a high measure of similarity, since the 75179 Pforzheim 75179 Forzheim name, street, house number and place differ. Y coordinate +04889883 Y coordinate +04889883 However, the difference in this example and X coordinate +00866723 X coordinate +00866723 with the selected matching algorithm is not great, so that the data records are identified as a single block. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 12
  • 13. WHITE PAPER: CRM 2. « first time right » - the Data Quality Firewall It is important to specify certain standards after the transfer of the initially cleansed data stock. Only in this way can the obtained high data quality be preserved. A variety of options from the online area present themselves here: Firstly, the user of the CRM system can ensure that Since work is carried out under high pressure of certain input rules are complied with, e.g. street time at peak periods, especially in call centres, names should only be entered in the fields pro- address validation must take place very quickly. vided. A syntax check is also possible for fields for telephone numbers or e-mail addresses. In addi- NO MATTER WHICH TECHNOLOGY IS tion, there is the possibility of checking the stated USED, THE POSSIBILITY OF A SIMPLE, address for correctness. QUICK AND ERROR-TOLERANT SEARCH FOR ANY EXISTING CUSTOMER DATA IS This could be important, e.g. if the address is only FUNDAMENTAL. given to a call centre by telephone and errors quickly arise in the notation or because of different A rapid entry client which completes the address interpretations of what was heard or typing errors. components after input of the initial letters or num- If the information received over the telephone is bers can be used as an alternative. incorrect or unambiguous, the employee can also immediately ask for missing additional information No matter which technology is used, the possibility such as the town district, in order to be able to of a simple, quick and error-tolerant search for any transfer a postally correct address to the system. existing customer data is fundamental. This func- tion is not used if matching takes too long or does The performance of the underlying technology is not furnish the desired results. The Data Quality the decisive factor for acceptance here. Firewall is by-passed. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 13
  • 14. WHITE PAPER: CRM An everyday example demonstrates this: if the If the company or individual already exists in the search for information in the most well-known database, the employee receives a relevant indica- Internet search engines, Google or Yahoo, tion via the input mask. took longer than the typical 0.3 seconds, these search engines would not be used on account of An error-tolerant search is also appropriate here, the slowness. so that the respective data record can be found in spite of hearing errors or synonyms or incomplete UNISERV HAS CREATED DQ CONNECTORS company names. FOR THE MOST IMPORTANT CRM SYS- It goes without saying that this so-called implicit TEMS, SUCH AS SAP CRM, MICROSOFT search also has to take place very quickly and pre- DYNAMICS CRM, SIEBEL AS WELL AS UP- cisely, so that the work-flow of the employee in the DATE.SEVEN AND SALESFORCE.COM CRM system is not impeded. These requirements for the Data Quality Firewall The fully automatic prevention of new duplicates is are implemented by means of the DQ Connectors. also important. Here too, there is the possibility of In conjunction with development partners, Uniserv checking whether the customer is already recorded has created DQ Connectors for the most impor- in the system when the data is created. tant CRM systems, such as SAP CRM, Microsoft If this is the case, a new customer account does Dynamics CRM, Siebel as well as update.seven not have to be created. The existing information and salesforce.com, which enable the integration can even be enhanced by the current process. This of data quality mechanisms at data acceptance search runs in the background without being spe- and for record-by-record processing. As a result, cifically triggered by the employee at each initial nothing stands in the way of these functions, which data creation or change of the address data. are important for implementing high data quality in the CRM system. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 14
  • 15. WHITE PAPER: CRM 3. Data Maintenance: Automated measures for maintaining the data quality standard In spite of the initial data cleansing and mechanisms to maintain the status quo of the data quality, it is good policy to carry out a periodic check of the overall database. This is also necessary if the databases are to These periodic checks of the overall database be consolidated e.g. after corporate takeovers. should ideally be executed as a batch process. Another scenario is a periodic check for street This guarantees that all the data complies with and place renaming. a common data quality standard at specified intervals. A DATA QUALITY HIGH ENOUGH TO AC- COMPLISH THE ACTUAL TASKS OF THE A data quality high enough to accomplish the actu- CRM SYSTEM CANNOT BE ASSUMED UN- al tasks of the CRM system cannot be assumed until TIL THE THREE PROCESS STEPS DESCRIBED the three process steps described here have been HERE HAVE BEEN IMPLEMENTED AND implemented and adopted as practice, thereby ADOPTED AS PRACTICE, THEREBY ENA- enabling the CRM system to reach its full potential BLING THE CRM SYSTEM TO REACH ITS and provide a return on investment. FULL POTENTIAL AND PROVIDE A RETURN ON INVESTMENT. The evaluations in the analytical CRM are now on a sound basis. The data in the operative CRM permits a customer-oriented approach in Relocations must be tracked and maintained, all areas. Finally, the customer relationships are and the data records of deceased customers strengthened in the long-term. The confidence should be flagged at least. The requirement for of the company’s employees in the quality of enhancement of the existing data with addition- the data increases at the same time. This means al information is also not excluded. that an additional check of the data is no longer required. The direct results are an increase in efficiency and reduction in costs. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 15
  • 16. WHITE PAPER: CRM It’s time to get on board: The Data Quality Audit The Uniserv DQ Audit presents itself, in order to be able to make statements about the status quo of the in-house data in the CRM system. The audit is the first step with clear goals in mind for sound decision-making and marks your per- For further information sonal introduction to the project «Data Quality in please visit our web page your CRM System». www.uniserv.com or contact us directly: During the audit, the quality of the addresses is primarily evaluated with the support of the data quality tools from Uniserv. In a second step, there is the possibility of getting to the root of the possi- We are looking forward for advising and sup- ble causes of the deficient data quality in a proc- porting you through your project. ess analysis. So the best thing to do is to Contact us right away! © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 16
  • 17. WHITE PAPER: CRM Uniserv Uniserv is the largest specialised supplier of data quality solutions in Europe with an internationally usable software portfolio and services for the quality as- surance of data in business intelligence, CRM applications, data warehousing, eBusiness and direct and database marketing. With several thousand installations worldwide, Uniserv supports hundreds of customers in their endeavours to map the Single View of Customer in their customer data- DATA base. Uniserv employs more than 110 people at its head- MIGRATION PROJECTS quarters in Pforzheim and its subsidiary in Paris, France, E-COMMERCE and serves a large number of prestigious customers in all sectors of industry and commerce, such as ADAC, Al- ERP lianz, BMW, Commerzbank, DBV Winterthur, Deutsche Bank, Deutsche Börse Group, France Telecom, Green- COMPLIANCE peace, GEZ, Heineken, Johnson & Johnson, Nestlé, CRM Payback, PSA Peugeot Citroën as well as Time Life and Union Investment. Further information is available SOA at www.uniserv.com DIRECT MARKETING MDM/CDI ON-PREMISE/ ON-DEMAND BI/BDW CPM Experience: Market position: Employees: OVER 40 YEARS LARGEST MORE THAN 110 PEOPLE EUROPEAN SUPPLIER UNISERV GmbH Contact: Rastatter Straße 13 • 75179 Pforzheim • Germany • T +49 7231 936-0 • +49 7231 936-0 F +49 7231 936-3002 • E info@uniserv.com • www.uniserv.com © Copyright Uniserv • Pforzheim/Germany • All rights reserved. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 17