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Data Quality Survey Review:How Companies are Approaching Data Accuracy in 2011

Tuesday, February 15, 2011

Teleconference:

Dial-in: 1-888-373-5705

Passcode: 700836

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Welcome!Introductions and Overview of Today’s Session

Experian QAS reviews December 2010

► Review research findings

► Discuss interesting trends within and across markets

► Compare data quality initiatives

► Provide tips for improving contact data quality

Today’s speakers:

► Erin Haselkorn

● Marketing Programs and Data Quality Research Specialist, Experian QAS

► Elizabeth MacKenzie

● Marketing Programs Specialist, Experian QAS

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Key Takeaways

Accurate contact data matters

Current accuracy levels are low

Manual cleansing processes are common

Choose solutions carefully

Demonstrate ROI

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Research Methodology

December 2010

1,320 respondents from 7 countries

Produced by Dynamic Markets

Multiple industries

250+ employees

C-level executives, vice presidents, directors, managers and administration staff

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Data Quality Matters

87% of U.S. businesses have a documented data quality strategy

► Data quality strategies are most common in the U.S.

Companies improve contact records to:

► Increase efficiency

► Enhance customer satisfaction

► Generate revenue

APAC is more focused on informing business decisions

The financial industry wants to improve contact records to comply with regulations

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Data Quality Matters

Revenue Generation Cost Savings

Increased Efficiency Brand Protection

Customer Satisfaction Customer Profiling

Enable Informed Decisions Compliance

Reduce Risk/Fraud The Environment

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Low Level of Accuracy

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Low Level of Accuracy

89% suspect customer/ prospect data inaccurate in some way

24% of total records inaccurate

U.S. most confident; APAC region least confident

Education was least confident; utilities and financial services are most confident

79% experienced at least one negative consequence in the last 3 years from data accuracy issues

► 87% wasted departmental budget

► 30% negatively impacted customer perception

► 26% lost a potential customer

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Reasons for Inaccuracy

0 10 20 30 40 50 60

Percentage

Don't Know

Other

Human Error

Inadequate Data Strategy

Inadequacies in Current

Relevant Technology

Lack of Relevant Technology

Lack of Internal Manual

Resources

Insufficient Budget

Inadequate Senior

Management Support

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Current Strategies

87% manage data accuracy in some way

73% of U.S. businesses use at least 1 manual process, compared to 64% globally

81% of organizations upgraded data management systems in the last 2 years

$-

$1

$2

$3

$4

$5

$6

$7

$8

$9

$10

Mil

lio

ns i

n U

.S.

Do

llars

The UK The Netherlands France The U.S.

Australia New Zealand Singapore

Return from Data Quality Improvements

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Current Strategies

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Current Strategies

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Find the Right Contact Data Quality Tool

► Review data usage

► Examine entry points

► Evaluate data errors

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Demonstrate ROI

► Set objectives and benchmark current performance

► Establish target metrics

► Communicate vision to stakeholders

► Evaluate based on metrics

► Present results to stakeholders

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Summary

1. Businesses are investing in data quality

2. Significant uplift is seen from improving data quality

3. Organizations rely too heavily on manual processes

4. Evaluate data prior to choosing a solution

5. Demonstrate ROI and make sure the solution is working

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