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

    By | Small Business

    data quality stats

    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. 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 inaccurate

    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 compliance

    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 director

    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 standardization

    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?

    Achieve total data quality with the free data quality guide below.

    complete data quality guide

    This article was syndicated from Business 2 Community: 91% of Companies Feel Poor Data Wastes Revenue (And 47 More Data Stats)

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