The Bane of Bad Data

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In this special guest feature, Mark Woollen, Chief Product Officer at Radius, discusses how bad data is the bane of any marketer, especially those who find themselves late to marketing and sales opportunities or miss them altogether, and already costs $8.8 million annually for the average company. Research shows that in only a three-month period, 7.6% of contacts in the average CRM become unreachable, and these data inaccuracies will only worsen as data volume expands. Mark is passionate about building market redefining products inspired by exceptional customer collaboration. He brings experience as a CRM executive with marketing, product and sales roles at Salesforce, Oracle, Siebel and venture-backed start-ups for products generating up to $2.5 billion revenue. As a seasoned general manager, he has built and led global teams through full product lifecycle – ideation and strategy through implementation, go-to-market, support and rapid growth.

In just one hour from now, 521 business addresses will change. During that same span, 872 telephone numbers will switch or disconnect, 1,504 URLs will be created or altered, and 158 companies will modify their corporate structure. Prospects have never been more difficult to track or harder to reach–and the data trials are only getting tougher.

Each year, the volume of data swells to mind-numbing new highs. Current estimates suggest annual data production will reach 163 zettabytes by 2025 per IDC. While more data means more opportunities across sectors, especially for the implementation of improved automation processes, it also means more headaches too. In fact, the abundance of data is largely overshadowed by the many significant shortcomings in its quality.

Bad data is the bane of any marketer, especially those who find themselves late to marketing and sales opportunities or missing them altogether. It causes marketing messages to be sent to the wrong people or go undelivered.  Entire go-to-market segments can become misclassified resulting in key target prospects not being included in critical campaigns. Poor data quality already costs $8.8 million annually for the average U.S. B2B company according to Gartner, which also found about 12 percent of revenue losses are directly attributable to data woes. This is primarily because data fuels business strategy and is a necessity for operationalizing and optimizing go-to-market activities. Faulty data clouds assumptions about good and bad customers, negatively impacting the marketing strategies and tactics that are essential to growing your business. This makes accurate, up-to-the-minute, complete data a core competency for successful marketing at scale.

Consider recent Radius research that sought to better understand the severity of the current data quality crisis. Radius studied CRM data from over 200 marketing automation platforms to find that 33 percent of customer information is rendered useless due to inaccurate, outdated, duplicate or missing data. Going further, Radius found over the course of a three-month period that 7.6 percent of contacts in the average CRM become unreachable, 4.2 percent of phone numbers change or become disconnected and 2.5 percent of emails become invalid. With so much incorrect or incomplete data within sales and marketing systems, B2B organizations cannot accurately analyze their full total addressable market and are unable to extend their reach to drive increased demand through the power of omnichannel marketing. Bad data diminishes marketing return on investment and negatively impacts marketing and sales productivity.

The amount of resources that organizations already devote to data maintenance is certainly cause for concern given the widespread quality issues. For the average enterprise, Radius found annual spend on data validation and cleansing is over $100K while on-premises data quality tools rack up a $208K bill. Consulting services for matching and unification can run over $500K and yearly costs for list buying (often used as a short term “fix” to overcome the limitations of bad data) can surge over $1M depending on company size. With all this money being thrown at fixing data, the expectation for decent quality is not unreasonable. The results, sadly, come up short. Lack of data analysis knowledge and skills is one of the biggest barriers preventing companies from improving data quality and, per Experian’s findings, a whopping 94 percent of companies have experienced marketing and sales challenges internally trying to overcome data limitations.

With so many problems swirling around data quality, the situation might seem discouraging to B2B marketers. Thankfully though, some organizations are setting precedents that offer hope and lay out blueprints to knock down the barriers built by bad, inadequate data. As an example, Zenefits, one of the fastest growing company in history, was victim to their own success. Website form fills, CRM user misuse and data uploads deteriorated their system of record. With over three years of hyper growth, the “garbage in” data lead to “garbage out” forecasting, productivity and ultimately revenue scalability. The problem was truly realized by marketing leadership after inbound buzz subsided and the sales floors could no longer sustain the herculean effort. Zenefits tried to run high performance outbound campaigns but simply could not with the current state of their data. Cleanup projects were expensive band-aids on their fatally wounded system of record—a comprehensive and continuous solution was necessary to stop the bleeding.

Organizations must continuously update CRM and MAT data to power decisions. Properly analyzing the viability of markets and campaigns leads to shorter sales cycles and a higher percentage of closed deals. Still, most companies struggle to keep CRM and MAT data organized to address data gaps and inaccuracies, which impacts the bottom line. By determining the overall health of internal ecosystems, including identification of duplicate records, out-of-business records, incomplete records and more, companies will be better prepared to drive revenue working with the most accurate data available.

At the end of the day though, good versus bad data is not the chief worry for marketers. They care most about running high-performance marketing campaigns that lead to great outcomes. To accomplish this, organizations must connect their system of record to a network of record and become stewards of their data. This becomes especially critical given the rise of AI-based technologies like predictive analytics that rely on clean, rich foundational data to function correctly. Companies should incorporate key performance tactics like omnichannel marketing and partner marketing to drive disruptive advantage within their respective market segment, all of which starts with quality data. That said, removing the obstacles between data and revenue does not happen overnight. Organizations must fully commit to the intensive process that is required for properly rectifying their data and seek out a solution that provides unlimited access to B2B data and intelligence to find, target and convert their best prospects.


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