What is the True Cost of Bad Data for Your Business?

Your go-to-market actions are only as good as the data they run on. You can hire the best sales and marketing talent and outfit them with state-of-the-art CRM and automation tools, but without high-quality data, their efforts will fall short of your targets. 

Let’s dive deeper into what qualifies as bad data, what it actually costs businesses, and why you should switch from poor-quality to high-quality data.

What is poor data quality?

Poor quality data is inaccurate data. It can take several forms:

  • Missing contact fields (phone numbers, emails, physical addresses, etc.) 
  • Outdated information (old job titles, changes caused by mergers and acquisitions, etc.) 
  • Data entered in the wrong field 
  • Duplicate entries
  • Misspellings, typos, and spelling variations
  • Non-normalized data

Without continuous, real-time maintenance, data can stagnate and decay, making accurate database maintenance a tall order. Databases must be cleaned, maintained, and appended regularly, in order to ensure that sales and marketing teams are operating with the best possible data.

What does bad data actually cost businesses?

According to a Gartner survey, companies estimate that bad data costs them nearly $13 million per year. More notably, the research firm found that 60% of businesses don’t know how much bad data actually costs them because they don’t measure the impact. This indicates that a majority of businesses lack a fundamental understanding of how the quality of the data they have running through their systems affects their business outcomes. 

What are the risks of poor data quality?

Simply put, you run the risk of losing money. Bad data and data decay weaken critical business activities, such as prospecting or running email campaigns. 

Clean data enables your business to take focused action based on relevant data points. The more complete and accurate the data, the more likely it is that your marketing and sales efforts will align with the needs of your target customer. 

What is the impact of bad data on sales and marketing? 

The impact of dirty data on your sales and marketing teams can range from inaccurate targeting that prevents lead generation, to a sluggish sales pipeline that struggles to convert opportunities into customers. 

Bad data also prevents successful automation. Many aspects of the sales and marketing process can be automated to optimize demand generation outreach. However, because automated email campaigns or sales call auto-dialing rely on data accuracy, they can misfire if based on bad data. 

Here are four things that could go wrong: 

Four problems bad data causes for marketing teams 

1. Possibility of getting blacklisted 

Email marketing is the most ubiquitous form of marketing today. Ease of use, sophistication, and simplicity make it one of the best tools in a marketer’s arsenal. 

However, email marketing with bad data on your email lists runs the risk of falling into spam traps. Spam traps are email addresses that have been set up by internet service providers to identify which senders are using lists with dirty data. 

Too many trips into spam traps can get you blacklisted by your email service provider. In the worst case, they could suspend your email account. Your business then has to dedicate time and resources to solve this problem by either reversing the suspension or getting a new service provider. 

2. Increased email churn

Email churn is caused by customer attrition. Churn rate refers to the percentage of email subscribers who leave your list over a period of time.

Churn refers to legitimate customers who were once on your list but have now either dropped your services and no longer wish to receive your organization’s emails or are no longer using the email address you used to contact them. 

There are two types of list email churn:

  • Transparent churn: These are unsubscribes, hard bounces, and spam complaints. 
  • Opaque churn: These are emails that land in a spam folder, go to an inactive email address, or remain unopened.

It’s important to factor churn into your database maintenance, otherwise, you run the risk of irritating people who don’t want to be on your marketing list. They may then take action and file spam complaints. In the long run, mismanaging churn can cause you to lose contact with new and existing customers and negatively impact your relationship-building efforts. 

3. Prospects and customers get the wrong content 

If your marketing database isn’t accurate, you might be sending prospects content that doesn’t align with where they are in the buyer’s journey.

For example, if the CEO of a company downloads your whitepaper, they may not appreciate getting an email notification to download the same document again. The marketing director at a prospective customer might grimace at emails addressed to “marketing specialist.” The same goes for names—Karla won’t be pleased to receive an email addressed to Carla.

Not only do these missteps directly affect your customers’ experiences, but they tarnish your brand reputation, too. 

4. Buyer personas don’t hold up

The key to generating product interest and brand awareness is sending relevant messages to the right audience at the right time. 

Your buyer personas play a significant role in directing appropriate content to the right buyers. However, if your database contains inaccuracies, you might be basing your buyer personas on false information, which can have much bigger consequences for the entire marketing team, such as failed campaigns and missed opportunities. 

Three problems bad data causes for sales teams 

1. Inaccurate data waste sales reps’ time

Every time a sales rep dials a wrong number or emails an outdated account, they’re wasting valuable time that could be spent selling. A LeadJen study showed that SDRs wasted an average of 27% of potential selling time following bad data, resulting in a loss of more than $20,000 in productive sales time per year for each SDR. 

Many reps may feel they don’t have enough information before making a call, working with patchy, inaccurate data further compounds their ability to do their job well. 

With confidence in ongoing data hygiene and maintenance, reps can barrel through call lists, spending more time connecting with quality prospects and leads.  

2. Poor data quality can produce bad experiences for customers, prospects and your team 

Bad data can lead to misspelled names, undelivered messages, account or contact mix-ups, duplicate communications, and more. Though these seem like minor mistakes, they can prevent you from reaching your intended audience. 

In the worst case, your audience might experience a combination of these issues, leaving them with a negative impression of your brand. This can create difficult conversations for your sales reps. In the long run, poor data quality can cause churn and result in lost deals. 

3. Bad data can frustrate the sales process and hurt morale

When salespeople call the wrong number and reach the wrong person, they waste valuable time and energy that could’ve been spent on productive opportunities. Constant missed connections can be frustrating. And since most sales salaries are commission-based, anything that makes it more difficult to sell can hurt your team’s morale. 

How to deal with poor data quality

Using bad data might be the reason your sales and marketing teams consistently underperform or are struggling to hit their numbers. To understand what’s going on, start with an audit that helps define your business’ data strategy: 

1.  Assess and improve data collection methods

Take a look at every source and method by which data enters your business systems, including: 

  • Streamline web forms. Webforms help you capture first-party data — your most valuable business data. This includes data gathered via content downloads, blog subscriptions, webinar registrations, or anyone who shares their information on your website. 
  • Assess the quality of second-party or third-party data sources. This data is often purchased and should be thoroughly vetted before being entered into your systems. 
  • Consider how to minimize manual data entries. Automation tools can reduce human errors on data entries and free up sales and marketing teams to do more productive work.

No business database can ever be 100% accurate, but by ensuring that all the data that enters your database is cleaned, appended, and updated on a regular basis, your teams can trust the information in your systems. 

2. Work with a market intelligence provider 

Aggregating, analyzing, and assimilating all the information your sales and marketing teams need to win can be a mammoth task, especially for smaller businesses. 

Partnering with a market intelligence provider is a great way to outsource the massive amount of work it takes to build and maintain a good database. They help to analyze your database and identify and address any issues to enable your teams to confidently take data-driven actions. 

3. Rely on a high-quality data provider 

Work closely with a reputable data provider that addresses all of your data needs. Work with them to fix any holes or inconsistencies in your sales and marketing contact database.

Make sure to vet every provider on the accuracy, coverage, and consistency of their data. Download our guide to evaluating global data providers to learn more about what you should look for in a data provider. 

Drive better business outcomes with high-quality data

Basing your business functions on high-quality data might be the difference between driving optimal sales and marketing that connects with your audience — or missing out on revenue and alienating potential customers. 

The cost of having bad data running through your system far outweighs the cost of introducing good data to your business. When it comes to critical business data, don’t simply look at the price tag, consider the return on investment in high-quality data and the time and money you could lose by making the wrong choice.