Five Ways Dirty Data Is Killing Marketing Performance

    As marketing becomes increasingly data driven, it’s time for marketers to make data quality a top priority. Following a recent analysis from Integrate, which examined the data quality of more than 775,000 leads generated for B2B marketers in the technology industry in 2014, it’s clear that poor prospect data quality is a rampant problem for marketers. Specifically, 40 percent of leads generated by third-party media partners for marketing clients, on average, didn’t meet marketers’ criteria or contained invalid, incomplete or duplicate data.

    These findings amplify the challenge that marketers face in acquiring clean, accurate data via third-party demand gen programs. They also highlight the enormous roadblock dirty data can create if it’s not governed before being imported into marketing automation nurture tracks or passed to sales for follow up. At a time when marketers are held more accountable for ROI and customer acquisition, bad prospect information can have several negative consequences, which marketers simply can’t afford.

    To overcome this silent killer of marketing campaigns, organizations need to first make data quality a priority. They must also implement software to properly validate and govern their data. Without taking these vital steps, Scott Vaughan, CMO of Integrate, says that marketers risk the following five consequences.

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    The Consequences of Bad Data

    Click through for five consequences marketers face when using data of poor quality, as identified by Scott Vaughan, CMO of Integrate.

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    Skewed Conversion Insights and Reduced Optimization Effectiveness

    Duplicate data, invalid values/ranges and missing fields are the most prevalent data quality issues for B2B leads. When data isn’t up to par, organizations aren’t able to make informed decisions based on their lead data, which in turn prevents good leads from converting through the pipeline.

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    Slowed Velocity of Entire Pipeline

    Without data governance software, organizations must manually catch and correct thousands of prospect data errors. This manual data cleansing slows the rate at which leads can move through the pipeline, allowing good prospect data to go bad.

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    Wasted Time and Resources

    With so much automation technology available today, it might come as a surprise that intelligent and capable marketing professionals are spending their days manually scrubbing Excel spreadsheets. But, because of inaccurate, invalid and duplicate data, this unfortunately is something that still happens. This is how marketing professionals end up spending their time and expertise, rather than on nurturing qualified, interested prospects.  

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    Diminished Customer Experience

    Due to the difficulty of vetting leads and ensuring accurate data, a prospect might not receive follow up for weeks or be contacted with the incorrect information. This is hardly a good customer experience.

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    Decreased Marketing Automation and CRM ROI

    By wasting usage volume on ineffective data, organizations’ ROI for marketing tech systems takes a hit too.  In fact, 36 percent of marketers say “insufficient data quality” is the biggest obstacle to marketing automation success. With average B2B lead prices at over $50, the failed email and address validation issues from the recent analysis would translate into more than $2.5 million in wasted media spend.

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