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Data Quality and CRM


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High Data Quality in CRM : the proverbial icing on the cake!

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Data Quality and CRM

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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 not have to be created. The existing information and, 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. 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. 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». 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. 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 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 • © Copyright Uniserv • Pforzheim/Germany • All rights reserved. © UNISERV GmbH / +49 7231 936-0 / All rights reserved. Page 17