better leverage your data: overcome common data quality challenges

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© 2015 Experian Information Solutions, Inc. All rights reserved. Experian and the marks used herein are service marks or registered trademarks of

Experian Information Solutions, Inc. Other product and company names mentioned herein are the trademarks of their respective owners.

No part of this copyrighted work may be reproduced, modified, or distributed in any form or manner without the prior written permission of Experian.

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Better leverage your data

Overcome common data quality challenges

2 © 2013 Experian Information Solutions, Inc. All rights reserved.

Experian Public. 2 © 2015 Experian Information Solutions, Inc. All rights reserved.

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Speakers and agenda

Erin Haselkorn

Analyst & Public Relations Manager

Today’s agenda: • Setting the stage: the data

accuracy challenge

• Why is data management so

hard?

• What can marketers do?

• Case study

• Q&A



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Data creates opportunities



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58% 55%

51% 47% 46% 44% 42%

35% 34%

22%

4%

0%

10%

20%

30%

40%

50%

60%

70%

Reason for maintaining high quality data

Increased efficiency Enhancement of customer satisfaction

Enable more informed decisions Cost savings

Protection of organization's reputation Capitalize on market opportunities through profiling

Reduction of risk Compliance

Single customer view Help the environment

Other

Wide use of data| Information touches every aspect



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Turning data into insight| Desire to stay informed

53% 51%

49%

45%

37% 37%

28%

4% 2% 1%

0%

10%

20%

30%

40%

50%

60%

Drivers for turning data into insight

Wanting to understand customer needs

Wanting to find new customers

Wanting to increase the value of eachcustomer

Secure future budgets

Wanting to determine past marketingcampaign performance

Customization of future campaigns

Driving more traffic from one channel toanother

Other

None

Don’t know



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Turning data into insight| Needed for marketing success

As marketers continue to automate processes and work within tighter timeframes to keep up with consumers, maintaining and analyzing

accurate data will be critical.

53%

45%

21%

41%

32% 25%

48%

4%

0%

10%

20%

30%

40%

50%

60%

Data essential for marketing success

Data sets essential for marketing success

Contact data Demographic data Geolocation data Behavioral data

Preference data International data Sales data Other



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Data not always useful



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High degree of errors| Plagued by inaccuracy

On average, US organizations believe 32 percent of their data is inaccurate, up from 25 percent just a year ago

47%

19%

42% 39%

23%

33%

47%

4% 3% 1% 0%

10%

20%

30%

40%

50%

Most common data errors

Most common data errors

Incomplete or missing data Spelling mistakes Outdated information

Duplicate data Typos Data entered in the incorrect field

Inaccurate data Other None

Don’t know



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High degree of errors| A lesson in human error

20% 26% 28%

25% 26% 31%

60%

39%

4% 1%

0%

10%

20%

30%

40%

50%

60%

70%

Reason for inaccuracy

Inadequate senior management support Insufficient budgets

Lack of internal manual resources A lack of relevant technology

Inadequacies in relevant technology Inadequate data strategy

Human error Lack of internal communication between departments

Other Don’t know



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Maintaining data quality

is a challenge



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Unsophisticated approaches| Data quality strategy

17%

29%

29%

22%

3%

Sophistication of data quality approach

Unaware

Reactive

Proactive

Optimized

Don’t know



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Lack of ownership| Data belongs to everyone and no one

43% See potential to monetize high quality data

68% Believe it is difficult to

find a stakeholder without a siloed view of data management

4 out of 5 see data as a valuable asset

that is not being exploited

17% Businesses believe they

could increase profitability if data

were higher quality



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Challenges unresolved | Data constantly evolving

10%

21%

26%

31%

31%

35%

36%

36%

38%

39%

41%

42%

48%

Standardization and select cleansing

Inter-enterprise data sharing

International support

Single customer view

Data profiling / discovery

Workflow tracking

Visualization of data quality metrics

Monitoring and governance

Real time processing

Data capture and validation

Increasing variety of data

Increasing volume data

Data quality issue resolution

Biggest challenges to managing data



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Data management lacks skills| Shortage in staff

11%

8%

22%

23%

27%

27%

30%

35%

37%

37%

None of the above - no failing points

Lack of project ownership

Lack of alignment to business objectives

Inadequate scoping of the project

Business does not yet place value on dataas an asset

Organization doesn't see the need to beproactive about data quality

Lack of support from the Board

Lack of knowledge of the importance of dataquality

Lack of investment in appropriate technology

Lack of relevant skills / staff

Main data quality failing points



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Marketing’s task



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What can marketers do?

Marketing doesn’t always collect the data, but it can encourage better data stewardship

• Start with contact data

• Prioritize your data challenges

• Understand your silos

• Identify steps that will make a difference

• Know your third party suppliers



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Start with contact data

Contact data is the foundation. Use it to aid in marketing communications, a single customer view, customer service,

intelligence, and much more.



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Prioritize data challenges

• How do you identify data issues today?

• How do you resolve those issues?

• Where is the most data collected?

• How is data used in marketing?

• Where do you see the biggest pain

points?

Data Quality

Management



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Understand silos

Marketing doesn’t always collect the data, but it can encourage better data stewardship



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Identify steps for improvement

Every organization will be different in how they tackle data improvement, but there are some similarities

Changes in staffing

Fewer manual processes

Investment in technology

Central ownership



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Know your third party suppliers

You are making decisions using information from someone else. How much can you trust it? Does it benefit your

customer?



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Case study



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Many of us don’t trust our data

Creating an effective data management strategy is not easy

It takes more than just Marketing

Start with contact data

Take steps that will make the biggest difference first

Summary



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Q & A