The High Costs of Dirty Data

In Big Data by Shelly Kramer1 Comment

Every day, businesses collect a mountain of data about their existing and potential customers — vital information that is rightly seen as the lifeblood of sales and profits.

While resources have often targeted data quantity, the focus on quality is moving up on the agenda. Executives recognize that inaccurate or “dirty” data can have a negative impact on revenue, as well as the reputation of a business.

Data fuels sales and marketing, unless its wrong

A survey by Experian Data Quality highlighted that, despite the draw of email and social media marketing, traditional methods still hold sway with many marketers: Direct mail is the channel of choice for one in ten marketers. Even landlines ranked just behind mobile marketing.

These tactics require the dissemination of high quality, trustworthy information. Experian found nearly every one of the more than 1,200 organizations surveyed worldwide has a strategy in place to manage the overall quality of their data.

However, these efforts are undermined by a critical problem: Inaccuracy. Experian discovered that an overwhelming majority of organizations — more than 90 percent — report errors in their contact data.


Company websites are a key source of contact information. Whether through blog or webinar sign ups and registrations, downloaded research reports or case studies, or landing pages with other types of gated content, that valuable contact information provides a wealth of data aside from an email address. Time spent on page. Levels of engagement. What content formats are most popular to your prospects. All information with which to feed your lead generation, lead nurturing, and drip campaigns, and eventually grow your consumer base.

Mobile is also having an impact on inaccurate data collection. Nearly half of respondents (47 percent) reported they collect data via mobile sites or apps, yet they also estimated 22 percent it is inaccurate — higher than a year ago. Among marketing and sales professionals, that estimate is even higher at 30 percent. Whichever figure you believe, there is clearly a lot of dirty data in corporate databases.

The source of dirty data

Most bad data starts with human error. Poor communication between departments can also play a part. And to continue on with the “trickle down effect”, not surprisingly those data management departments tend to shift the blame onto poor data strategy and insufficient budgets.

While the vast majority of companies say they have systems in place to check accuracy, less than half use specialized software at the point of capture; fewer use software to clean up after collection. In fact, many organizations still use manual checking to ensure accuracy — surely a bad move when a majority blame human error for the bad data.

The cost of seemingly small errors isn’t insignificant.

Experian estimates the average business loses 12 percent of its revenue to inaccurate data, due to reductions in productivity, wasted resources and, crucially, missed opportunities for cross-channel marketing due to gaps in contact data records.

And that’s just inside an organization. From the outside looking in, marketers are struggling with dirty data as well. According to a recent article from, “…marketers are generating a large portion of poor quality leads, including those with improper formatting and even inaccuracies. Bad prospect information can have negative consequences, including wasted media investment, squandered resources and poor customer experience, which marketers simply can’t afford.”

In fact, dirty data could cost B2B brands more than $2.5 million.

The hidden cost in terms of loss of reputation could be even higher; More than one in four respondents felt customer service suffered as a consequence of poor contact data.

Ironically, as this graphic shows, businesses seem quite able to articulate whyquality records keeping and clean data gathering is so vitally important. Yet, none appear to be adopting strategies or systems to help them achieve better results.



The Experian report concludes that organizations need to move beyond simple awareness of the problem and begin to face it head on. Integrated strategies that improve data collection accuracy, identifying key areas for improvement, deploying technology to reduce human error, and evaluating the success or failure of solutions are all areas of focus that organizations need to address and commit to, in order to overcome the problems caused by dirty data.

Between lost revenue and dissatisfied customers, dirty data could be costing you dearly. Is it time to clean up your database? I would love to hear what you think about the impact of dirty data on your business.

The full Global Research Report is available to download from Experian (registration required).

Graphics source Global Research Report

Photo Credit: adnanbilgrami via Compfight cc

This post was written as part of the Dell Insight Partners program, which provides news and analysis about the evolving world of tech. For more on these topics, visit Dell’s thought leadership site PowerMoreDell sponsored this article, but the opinions are my own and don’t necessarily represent Dell’s positions or strategies.

This article can also be seen on V3 Broadsuite Blog.

Shelly Kramer is a Principal Analyst and Founding Partner at Futurum Research. A serial entrepreneur with a technology centric focus, she has worked alongside some of the world’s largest brands to embrace disruption and spur innovation, understand and address the realities of the connected customer, and help navigate the process of digital transformation. She brings 20 years' experience as a brand strategist to her work at Futurum, and has deep experience helping global companies with marketing challenges, GTM strategies, messaging development, and driving strategy and digital transformation for B2B brands across multiple verticals. Shelly's coverage areas include Collaboration/CX/SaaS, platforms, ESG, and Cybersecurity, as well as topics and trends related to the Future of Work, the transformation of the workplace and how people and technology are driving that transformation. A transplanted New Yorker, she has learned to love life in the Midwest, and has firsthand experience that some of the most innovative minds and most successful companies in the world also happen to live in “flyover country.”


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