Tackling Bad Data: How Poor Data Quality Impacts Your B2B Bottom Line

You hire talented sales and marketing professionals and set them up with state-of-the-art CRM and automation tools.  Wait, are they working with bad data? 

Businesses depend on data to fuel business growth. However, if that data isn’t clean, your marketing and sales efforts take a hit. 

30-50% of CRM and ERP data is inaccurate.”

Henry Schuck, Founder and CEO of ZoomInfo.

What Is Poor Data Quality?

In simplest terms, poor data quality is bits of inaccurate information. For businesses, that bad data can negatively affect revenue growth. Examples of poor data include:

  • Missing contact fields
  • Inaccuracies due to outdated information (e.g., individual role changes and mergers and acquisitions)
  • Data entered in the wrong field 
  • Duplicate entries
  • Misspellings, typos, and spelling variations
  • Non-normalized data

For B2B companies, bad data and data decay weaken CRM and sales and marketing automation tools. In turn, sales and marketing efforts — from prospecting to running email campaigns — are less effective. 

How Does Dirty Data Affect Sales?

The impact of dirty data on sales can range from a sluggish sales pipeline to catastrophic revenue loss. Let’s take a closer look.

Inaccurate data waste sales reps’ time.

Think about it—every time a sales rep dials a wrong number or emails an outdated account, they’re wasting valuable time that could be spent selling. 

Considering that 42% of sales reps 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 ongoing data hygiene maintenance, reps can barrel through call lists, spending more time connecting with quality prospects and leads.  

Prospect and customer experiences take a hit.

Unfortunately, lost deals and customer churn are side effects of low-quality data. 

Bad data results in misspelled names, undelivered messages, account or contact mix-ups, duplicate communications, and much more. 

Though these mistakes seem small, they impact people’s experiences with your brand. 

Sales reps’ morale dips and frustration peaks with bad data.

Understandably, it’s frustrating for sales reps who must rely on inaccurate information to do their job.  

Most sales’ salaries are commission-based, so anything that makes it more difficult to sell will impact the team’s morale.

What Impact Does Bad Data Have On Marketing?

If your marketing campaigns aren’t generating leads or your lead-to-customer conversion rate is low, poor data might be the cause. Things to be aware of include:

Increased email churn

Churn rate refers to the percentage of email subscribers who leave your list over a period of time. 

If your department doesn’t prioritize email data hygiene, that list churn is likely wreaking havoc on your email campaigns.

There are two types of list churn to be aware of.

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

So, what does list churn have to do with B2B marketing data? The short answer—a lot.

If your database includes inaccurate contact information, your email list falls apart, and you lose contact with new and existing customers. 

This stalls relationship-building and can mean the difference between a customer renewing a contract and getting snatched up by the competition.

Prospects and customers get mismatched content.

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

For instance, the CEO who downloads your whitepaper might not appreciate getting an email notification to download the same document. 

Also, if contact information is inaccurate, the prospect who is now a director 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 affect your customers’ experience, but the errors also chip away at your brand reputation. 

Buyer personas don’t hold up.

The key to generating product or brand interest 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. 

Unfortunately, if your database contains inaccuracies, you might be basing your buyer personas on false information.

What To Do About Bad Data

If your sales team is hitting dead ends with prospects or your marketing campaigns aren’t generating quality MQLs, it’s likely an impact of bad data. 

Start with a data audit. Typically, this one-time evaluation involves three main steps:

1. Analyze your data. 

While you can analyze your existing database yourself, it can be a time-consuming and tedious process.

Your and your teams’ time is probably better spent elsewhere. 

Think about partnering with a market intelligence provider — they’ll analyze your database and identify any data issues. 

2. Assess and improve data collection methods. 

Take a look at your data collection methods. That includes web forms (from white paper downloads to webinar registrations), contact list building, and manual entries. 

Are you asking prospects to fill out unnecessary fields? This is an excellent time to revisit and streamline your web forms.  

Also, consider how you can minimize manual data changes. Using automation tools will reduce human error and free up sales and marketing teams to do more productive work.

3. Fix your data. 

Don’t let your data provider go just yet! Work with them to fix any holes or inconsistencies in your sales and marketing contact database.

From Poor Data Quality To Clean Data Flow

Your sales and marketing teams are great at what they do.  And you might give them the best tools possible to work with. 

Ultimately, though, their success (and your bottom line) depends on a constant flow of clean data. 

It’s hard to put a price tag on that.