Bad Data Blues: The Impact Data-Quality Issues Have On CRM Functionality, Bottom Lines, And More

No matter how advanced and intuitive CRMs become, they aren’t immune to bad data or the ensuing garbage in, garbage out consequences.

New research from Validity highlights exactly how much of a negative impact bad data can have, with 37% of the CRM users surveyed saying revenue loss has been a direct consequence of poor data quality.

“An overwhelming 76 percent of respondents said less than half of their organization’s CRM data is accurate and complete,” says The State of CRM Data Management in 2025 report. “Now for the real kicker: In the same survey, only 32 percent said their company has a data quality problem. … Amid the confusion, one thing is clear: There’s a major disconnect between data perception and reality.”

The report calls the apparent widespread settling for data that is merely good enough to be “a ticking time bomb,” and as someone who’s seen an unfortunate number of companies fail at the basics of even getting their CRM up and running properly, I couldn’t agree more. Of the reasons behind some of this data dysfunction, Validity points to lack of responsibility with CRM governance, data silos, and inability to measure data quality.

“One in every three respondents said they feel unsure how to assess the quality of their CRM data,” the report says. “Without clear metrics or standards in place, it’s nearly impossible to identify issues, track progress, or prove the value of data quality initiatives.”

Incomplete data, missing data, and incorrect data were the leading quality issues that users struggled with, above even duplicate records.

(Source: Validity)

“When CRM records are incomplete, outdated, or just plain wrong, sales and marketing teams are left flying blind,” the report says. “They can’t target the right customers, personalize messaging, or build trust. The result? Missed opportunities, wasted budget, and a major hit to the bottom line.”

The report says manual data-cleaning continues to be the main approach for improving CRM quality, and that while not everyone is prepared yet for AI to “assess the readiness” of their data, there’s a connection between quality data and AI adoption.

“In the age of AI, bad data means bad decisions — and the risks are growing too big to ignore,” the report says. “If organizations want to unlock AI’s full potential, improving CRM data quality must move to the top of the priority list.”