How U.S Organizations Measure Contact Data Quality

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How U.S. Organizations Measure Contact Data Quality

Jennifer Levin

Amanda Van Veen

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Overview

Review Experian QAS research findings

Provide tips to improve contact data quality

Highlight tools that help achieve accuracy standards

Questions & Answers

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Main Themes

Cross department management is complex

Current accuracy levels are low

Manual audits are common

Errors affect multiple business units

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Poll Question:

What’s the most important aspect of contact data quality to you?

► Cost savings

► Protection of organization reputation/brand

► Customer satisfaction

► Profiling/Analysis

► Efficiency savings

► None of these/I don’t know

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Research Methodology

June 2011

300 respondents

Finance, insurance and retail industries

Decision makers

IT, marketing, administration, finance, HR and operations

Contact data quality

► Physical mail

► Email

► Telephone

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Managing the Data

Organizations have multiple data collection channels

► 68% of respondents are capturing customer contact data through mobile applications

Data owners differ from data users

IT52%

Customer Service7%

Marketing13%

Sales9%

Mul-tiple de-

part-ments17%

Other2%

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Maintaining Contact Records

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Poll Question:

How confident are you in your contact data accuracy?

► Very confident

► Confident

► Not confident

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Low Level of Accuracy

23% cite inaccuracies

Customer Service creates most data errors

Most common errors: incomplete/outdated information & spelling mistakes

Barriers to accurate data are:

Knowledge of changes

Human error

Budget

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Barriers to Accurate Contact Data

0

20

40

60

80

Budget Senior Management Support

Knowledge of Changes Human Error

Time & Internal Resources None

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Current Strategies

82% currently have a data quality strategy

Over 75% view data management as essential issue

Data cleansing responsibility lies with IT

Organizations clean contact data through manual processes

Staff measurement

Manual review

Staff training

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Current Strategies

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Affects of Poor Contact Data

98% of respondents say staff budget is wasted on inaccurate contact data

Burden dependent on department

Administrative departments waste the most

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Tips for Success: Collecting Accurate Data

Consider a 360-degree view

Balance speed with accuracy

Create processes across business units

Eliminate the chance for human error

Consider real-time and batch mode data quality solutions

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About Experian QAS

Contact data verification, standardization, and enrichment tools

Business Processes(Marketing, Sales, Operations, Customer

Support, etc.)

CRM databaseVerified Records

Experian QAS

Clean,De-Duplicate,Enhance

Address Entry

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QASProducts & services

Service Options

• Real-time verification• Bulk processing - Lists & DBs• De-duplication

Data Verification

• Email• Phone numbers• Addresses• Names• Demographics

Deployment Options

On premiseOn-demand (hosted web services)

Bureau ServicesCRM Integrations: SFDC, MS CRM, Siebel, Oracle, SAP SugarCRM and

more…

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Summary

Data errors affect everyone – work across departments

Leverage technology to avoid common errors

Review confidence levels regularly to ensure improvements are made

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Questions

?Questions after the event?

Email: us.webinars@qas.com

Call: 888-727-3985

Visit: www.qas.com

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Please visit www.qas.com for more information.