Everyone claims to be “data-driven.”
Heck, it’s hard to find a resumé or LinkedIn bio these days that doesn’t contain this phrase. But it’s the quality of the data driving these decisions that determines if you’re driving in the right direction—or off a cliff.
When organizations don’t show their CRM data the love and attention it deserves (by keeping it clean and up to date), they’re left with low-quality data that drives even lower-quality business outcomes.
Validity got to the heart of the matter in our recent study: The State of CRM Data Health in 2022. We surveyed over 1,200 CRM admins from 606 organizations around the world to learn the truth about CRM data quality and how it affects users.
(Spoiler alert: We didn’t see some of these answers coming.)
One major finding from our study was that organizations are setting the bar too low for data quality.
Seventy-five percent of our survey respondents rated the overall accuracy, quality, and usefulness of the data in their CRM as “good” or “very good.”
Good news, right? Not quite. When we drilled deeper, over half of these same respondents rated their CRM accuracy and completeness at less than 80 percent. Many also blamed their data for a wide range of negative business outcomes that we’ll discuss later.
Clearly, organizations need to hold their data—and those who manage it—to a higher standard.
Our survey respondents are already paying a steep price for neglecting their data quality. Based on their responses, we identified five ways that CRM data quality is sabotaging businesses like yours in 2022.
Low-quality data can have a major impact on team productivity. Take for example, the stat we mentioned: The quality and accuracy of the average CRM is less than 80 percent.
Now, let’s do some basic math:
Say a sales development representative (SDR) touches 150 records per day (Lead, Contacts, Accounts, Opportunities, etc.) If only 80 percent of these records are accurate, they work with 30 inaccurate records each day. That leads to around two and a half working hours per day wasted hunting for missing data or trying to chase down prospects using inaccurate contact information.
That’s only for one SDR. Take this number and multiply it across other users and departments, and the productivity loss becomes staggering.
Depending on how it’s managed, your CRM data can be a goldmine or a money pit.
Sometimes it’s hard to draw a straight line from data quality back to revenue. As such, it’s easy for leadership to push data quality far down on their list of priorities.
However, 44 percent of study respondents estimated their company loses over 10 percent of their annual revenue due to poor quality CRM data.
While there may not be any direct costs for data mismanagement, the companies we surveyed reported they lose customers, blow new business deals, and delay revenue-driving initiatives like marketing and brand awareness campaigns.
In this climate, employees have limited patience for working with dirty data.
Every member of the team relies on different data points, from a sales representative using up-to-date contact information to reach a prospect, to a marketing professional looking for a customer’s address to create a segmented email list.
A database riddled with duplicates, incomplete data, missing data, incorrect data, or expired data can make it nearly impossible for employees to perform well.
For some employees, these stressors might be the push they need to walk out the door.
If your organization won’t invest in data quality improvements in 2022, it’s easier than ever for them to find an employer who will. Sixty-four percent of study participants say they would consider leaving their current role if additional resources are not allocated to a robust CRM data quality plan.
The relationship between sales and marketing can easily grow contentious.
Oftentimes, it’s the same old story. The marketing team says, “We’re delivering all these MQLs, leads, inquiries, etc., and sales never follows up on them.”
Then the sales team says, “Yeah marketing, you deliver these leads, but they stink. I couldn’t sell these people a glass of cold water in the desert!”
These problems only get worse when data quality is an issue.
Our study found marketing professionals were 155 percent more likely than their sales counterparts to say that their sales forecasts are ”inaccurate” or “very inaccurate.” Unsurprisingly, we found that one of the main culprits behind inaccurate forecasts is low-quality data.
It’s easy to see why marketers are frustrated. Marketing teams need accurate forecasts to plan campaigns and activities that support these pre-defined targets.
But sales forecast accuracy is heavily dependent on the data in the CRM, including the information sales representatives input to predict when/if deals will close and what stages certain deals are in.
Sales and marketing teams struggling with data quality issues have a huge opportunity here. Both teams should remove the boxing gloves and put their collective power into solving these data challenges.
By doing so, they’ll see data become a bridge that unites these teams, not a wall that keeps them apart.
When organizations fail to make data quality a priority, employees can develop an undesirable relationship with their data.
A whopping 76 percent of respondents said employees “sometimes” or “often” manipulate data to tell the story they want decision makers to hear.
Even worse, 75 percent said staff “sometimes” or “often” fabricates data to tell the story they want decision makers to hear. (Our jaws dropped too.)
How does this happen?
It’s safe to assume that CRM users don’t go around making up data on purpose. But we’re only human. When we make a hypothesis, it’s natural for us to be biased towards data points that support that point.
In organizations with data quality issues, these biases become more pronounced. When folks already lack confidence in their data, it becomes all too tempting to hunt through the CRM to find evidence to support their points.
These stats are a strong warning sign that many organizations need better data governance.They need to get real about how they’re using data, where it comes from, and what data points they’re using to create each report.
By connecting some of these dots, they can create environments in which people don’t feel like they have to manipulate or fabricate data to do their jobs.
Some of the statistics can seem a little doom and gloom.
But we should view these findings through a positive lens. CRM stakeholders are becoming more aware of these problems. And there are actionable steps they can take now to start fixing data quality issues.
To learn more about why and how CRM users should raise the bar for data quality, read Validity’s new report: The State of CRM Data Health in 2022.