7 Ways Dirty Data is Hurting Your Bottom Line

dirty data

Using dirty data to fuel your business initiatives is akin to putting the wrong type of fuel in your car.  You think you’re doing everything right to keep your car running smoothly when, in reality, you’re doing serious damage to your engine.

Consider these statistics (source):

  • 40% of business objectives fail due to inaccurate data.
  • It costs $1 to verify a record as it’s entered, $10 to scrub and cleanse it later, and $100 if nothing is done.
  • Bad data costs U.S. businesses more than $611 billion each year.

These numbers may catch your attention— but statistics alone don’t explain how and why dirty data hurts your bottom line. Without additional context, it’s easy to see why some companies continue to neglect data hygiene. In today’s blog post, we’re digging a bit deeper into the issue of dirty data. Let’s get into it!

1. Ineffective marketing campaigns.

Your marketing team likely uses many channels and tactics to identify, target, and engage with prospects and customers. In order to be effective, you must use the data at your disposal to inform and coordinate these tactics. Therefore, the effectiveness of these tactics is intrinsically linked to the accuracy of your data. Inaccurate data skews your understanding of your target audience, which has a domino effect as it negatively influences your approach to each and every campaign.

Let’s use email marketing as an example. Say you want to promote a new product by sending a free trial offer to a specific segment of your audience. Your goal is to target prospects who are most likely to purchase the product — a conclusion you reach by examining online behavior, purchase history, job function, and other data points. The problem is, many of these data points are outdated or entirely inaccurate—resulting in low open rates and abysmal engagement.

There’s no way around it, dirty data creates an inaccurate idea of your ideal customers and throws off your efforts to target the right people. Ultimately this poor targeting leads to less successful campaigns— and less revenue from marketing.

2. Poor customer experience.

The modern customer has more control over their buying journey than ever before. As a result, the importance of facilitating a positive customer experience has increased drastically. In fact, 65% of buyers say a positive experience with a brand is more influential than great advertising (source).

When a customer is interested in buying from your company, they want every interaction to be seamless. Inaccurate data all but guarantees your customer interactions will suffer from miscommunications and mistakes. Something as simple as calling a prospect by the wrong name can be the difference between closing a deal and losing a potential customer to your competition.

When bad data results in poor customer experience, you’ll lose out on valuable prospects and fail to retain current customers. In fact, 39% of customers will stay away from a vendor for up to two years following a single bad experience (source).

3. Damaged reputation.

This next consequence of dirty data is directly related to our last point about customer experience. In today’s hyper-connected world, customers don’t just abandon your business when they have a poor experience. They also tell their peers about it. An overwhelming 79% of customers will share a bad experience they had with a company (source). Their negative reaction may be posted on social media, popular review sites, and other channels that facilitate customer feedback.

But dirty data can hurt your company’s reputation in more ways than simply encouraging negative customer feedback. For example, when you send emails to invalid or outdated addresses, you increase bounce rates and spam complaints. As a result, internet service providers (ISPs) will penalize your sender score and email reputation thus damaging the deliverability of future messages.

4. Misinformed decision-making.

In the past, executives and key stakeholders relied on instinct and intuition to make important long-term business decisions. Now, data is so readily available that there’s no longer a need for guesswork when it comes to crucial decision-making.

Here’s the problem: If your executive team relies on inaccurate data, it can lead them to make misinformed and potentially damaging long-term decisions. Accurate and comprehensive reporting is critical to data-driven decision-making. When bad data contaminates your marketing metrics and reporting, it can hurt your business on a massive scale.

5. Misaligned sales and marketing teams.

On the ZoomInfo blog, we often stress the importance of sales and marketing alignment. We do so because the alignment of these departments has a major effect on your business’s bottom line. Consider these statistics (source):

  • Organizations with tightly aligned sales and marketing functions enjoy 36% higher customer retention rates.
  • Aligning both departments can help generate 209% more revenue from marketing.
  • Companies with strong sales and marketing alignment achieve a 20% annual growth rate.

Unfortunately, dirty data is a major roadblock to healthy marketing and sales alignment. Lead generation is one of the first initiatives to suffer from low-quality data. This means your marketing team will end up sending low-quality leads to sales. Your sales teams will ignore them. And, the relationship between the two departments will quickly become fractured.

6. Decreased ROI from sales and marketing technologies.

When you invest in marketing automation and CRM platforms, you do so to improve the efficiency and effectiveness of your sales and marketing initiatives. But, dirty data prevents your technology stack from operating at its full potential. In fact, 36% of B2B marketers say that insufficient data quality is the biggest roadblock to marketing automation success (source).

7. A slower sales cycle.

A fast and efficient sales process is critical to modern business success. Customers have so many options at their fingertips, and therefore they demand a quick and seamless buying experience. Dirty data creates roadblocks through every stage of the sales cycle.

Poor lead management means that high-quality leads are contacted too late, or sometimes, not at all. And, without ongoing data hygiene, your teams are in an interminable state of playing catch-up. This process slows down the speed at which leads move through the sales process. And, as a result, good leads will go bad and you’ll lose out on potentially lucrative opportunities.

Key Takeaways on the Consequences of Dirty Data

This list is by no means comprehensive. Just about every modern business initiative can suffer at the hands of inaccurate data. But, we hope these examples paint a better picture of the tangible impact dirty data has on your business. To learn more about dirty data and how to combat it, we implore you to read the following articles:

For more information about ZoomInfo, contact our sales team today. Our comprehensive data maintenance solutions can keep your contact database clean and your business primed for success.