According to a recent Experian report, data quality is a growing space, and while 84% of companies are investing in a data quality solution, many are not sophisticated in their data strategy today.

91 Percent of Companies Feel Poor Data Wastes Revenue (And 47 More Data Stats)For instance, 32% of companies believe their data is inaccurate. Therefore, there’s still a long way to go in the world of ensuring quality data. In addition, there is a real need for data quality, because companies implementing data quality solutions see a significant increase in profits, among other benefits.

These stats and more come from the 2015 Experian Data Quality Benchmark Report. Here’s a recap of the report in the form of 48 insightful data quality stats.

Big Data Quality Takeaways

1. 95% of companies feel driven to turn their
data into insight

2. 32% of U.S. companies believe their information is

3. 26% of their
total data might be inaccurate

4. 83% of commercial companies believe their
revenue is affected by inaccurate and incomplete customer or prospect data

5. 63% of organizations lack a
coherent, centralized approach to their data quality strategy

6. 94% of U.S. companies are leveraging data and data quality in an attempt to
optimize their customer or prospect experience

7. 99% of organizations think data is essential for
marketing success

8. 74% of companies feel they do not have a
sophisticated data quality approach and could improve it

9. 27% are
proactive about data quality

10. 14% are
totally unaware of data quality

11. 91% of companies think
revenue is wasted due to poor contact data

12. 92% of companies say managing their data is challenging

Drivers for Maintaining High Quality Data

13. 47% say
cost savings

14. 46% say
increased efficiency

15. 55% say
protection of their reputation

16. 51% say
capitalizing on market opportunities through profiling

17. 35% say
enabling more informed decisions i

18. 34% say

19. 42% say a
single customer view

20. 22% say a
reduction of risk

Drivers for Turning Data into Insight

21. 53% say an understanding of
customer needs

22. 45% say wanting to determine past
marketing campaign performance

23. 49% say
securing future budgets

24. 37% say wanting to
increase the value of each customer

25. 51% say
customization of future campaigns

26. 28% say wanting to find
new customers

27. 4% say driving
more traffic from one channel to another

How Data is Managed

28. 35% manage their data in a centralized way with a single

29. 51% have some centralization, but many departments adopt their
own strategy

30. 42% have data managed by a
Chief Data Officer, Chief Information Officer, or Chief Technology Officer

How Data Quality Tools are Utilized

31. 33% use data quality tools for
data cleansing

32. 29% use it for data
enrichment and suppression

33. 31% use it for
matching and linkage

34. 33% use it for

35. 43% use it for
Data profiling

36. 42% use it for
monitoring and audit

37. 30% use it for
manual data cleansing

Data Quality Plans for the Future

38. 51% of companies plan to
prioritize and improve data quality solutions they already have in place

39. 64% will focus on a
new solution

Biggest Reason for Data Errors

40.The most common cause of contact data accuracy issues is
human error

41. 51% say the biggest reason for data errors is
incomplete or missing data

42. 48% say it’s
outdated information

43. 44% say it’s
inaccurate data

44. 32% say it’s
duplicate data

How Data Quality Issues are Detected

45. 57% say data quality issues are detected when
reported by employees, customer or prospects

46. 35% say it’s detected during an
analysis of marketing campaign results

47. 44% take
proactive data audits

48. 24% use
specialist detection software


As Inga Romanoff shares, “Data quality is not an accident.” Which stats stand out to you?


Get more data stats for business in this free report.

91 Percent of Companies Feel Poor Data Wastes Revenue (And 47 More Data Stats)

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