increasing the data quality in crm

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Arlanis salesforce.com Customer Day 2010

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Data Quality Solutions

© Uniserv GmbH

Increasing the data quality in CRM

Arlanis salesforce.com Customer Day 2010

© Uniserv GmbH 2

Who is UNISERV?

Market leader in customer data quality in the German-speaking countries and France

Head office in Germany, branch office in France

Partner network in various European countries and the USA and Canada

Listed in Gartner's Magic Quadrant for data quality tools

~ 870 customers

~ 130 employees

More than 40 years experience

© Uniserv GmbH 3

UNISERV – (Small) extract from customer references

© Uniserv GmbH 4

UNISERV – Fields of application of data quality solutions

Analytical business applications

CPMCPM

BI / BDW

Data migration

Data migration Compliance

Compliance

Dialogue / Direct

marketing

Dialogue / Direct

marketing

Data integrationMDM /

CDI

MDM /CDIOperative

Business Applications

ERPERP

CRM

eBusinesseBusiness

© Uniserv GmbH 5

UNISERV – Fields of application of data quality solutions

Analytical business applications

CPMCPM

BI / BDW

Data migration

Data migration Compliance

Compliance

Dialogue / Direct

marketing

Dialogue / Direct

marketing

Data integrationMDM /

CDI

MDM /CDIOperative

Business Applications

ERPERP

eBusinesseBusiness

CRM

© Uniserv GmbH 6

Typical quality problems for customer data

Incorrect customer data

Obsolete customer data

Duplicates

© Uniserv GmbH 7

Incorrect customer data

CausesTyping errors, illegible documents, phonetic ambiguities

Errors during data transfer

Inadequate consideration of international addresses

EffectsLoss of image

Undeliverable addresses

Risk of duplicates

© Uniserv GmbH 8

Obsolete customer data

CausesPlace was incorporated

Street was renamed

Buildings were re-numbered

Customer/prospective customer has relocated

EffectsUndeliverable addresses

High costs for manual research and correction

Risk of duplicates

© Uniserv GmbH 9

Duplicates

CausesContacts / accounts are inadvertently recorded twice

Automated transfer from different sources

Address changes

EffectsAdditional costs and dead letters for mailings

Information distributed over different data records

"Single View of Customer" is not implemented.

© Uniserv GmbH 10

"Intelligent" solution for duplicate check

KFZ Werkstatt A. Müller

Ringstr. 12

12345 B-Stadt

Anton Müller

Ringstr. 12

12345 B-Stadt

Autohaus am Ring

Ringstr. 12

12345 B-Stadt

sim

ilar

similar

not different

KFZ Werkstatt A. Müller

Ringstr. 12

12345 B-Stadt

Autohaus am Ring

Ringstr. 12

12345 B-Stadt

Anton Müller

Ringstr. 12

12345 B-Stadt

© Uniserv GmbH 11

International address validation

France Italy Switzerland

Austria

Germany

Canada

USA

Norway

Poland

Denmark

Sweden

Finland

UK

Portugal

Spain

Netherlands

LuxembourgBelgium

Brazil

Russia

Czech Rep.

Hungary

Slovakia

Global solution for ~ 240 countries

© Uniserv GmbH 12

Securing the data quality in a closed cycle

© Uniserv GmbH 13

Data quality audit at www.data-quality-on-demand.com

Select free audit

Upload address file

Carry out address validation and duplicate check

Download result statistics and quotation

© Uniserv GmbH 14

Database cleansing at www.data-quality-on-demand.com

Select processing with costs

Upload address file

Carry out address validation and duplicate check

Download results

© Uniserv GmbH 15

Check for new entries and changes

Integrated check in salesforce.com (together with Arlanis)

Address check + duplicate check

Automatic check of each new entry or change of a contact or account

Fully integrated in salesforce.com

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