What Is Data Quality? Common Issues, Strategies & Best Tools

When B2B teams do sales outreach, they tend to focus on quantity over quality.

The assumption is that more leads mean more chances of success, right?

The answer is often no in reality.

Your data quality determines the results you get from your outreach. The good news is that B2B teams can improve low-quality data in many ways.

Read on to learn about data quality, common issues, how to make a quality assessment, and the best tools for managing data. 👇

What is data quality?

Data quality measures how well a dataset is suited to its specific purpose.

Measures of data quality are based on various quality characteristics. The main ones are accuracy, timeliness, uniqueness, validity, consistency, and completeness.

When the characteristics are broken down, they simply mean:

• Accuracy. Can the data be trusted? Data is only useful if it’s accurate.
• Timeliness. Is the data up-to-date and accessible? Out-of-date data is mostly invaluable to B2B organisations.
• Uniqueness. Is there duplicate data in your dataset? Do all the customer profiles have unique customer IDs?
• Validity. Does the data comply with the expected formats and quality standards?
• Consistency. Is the data consistent across all operational systems and sources?
• Completeness. Is your dataset complete? A sales dataset with too many missing values, such as a person’s job title, is ineffective.

Why should B2B teams care about their data quality?

Wasted time, missed opportunities, and lack of personalisation contribute to poor data quality.

Having quality data solves all of these issues and more.

Below are five key benefits of quality data. 👇

It leads to more opportunities

Quality data is the core of any successful B2B sales team.

It leads to more opportunities at a high level, as you can make decisions based on accurate customer data.

Better data means better opportunities, which means more revenue for B2B sales teams.

It minimises resource waste

According to Experian, 94% of organisations believe their customer and prospect data is inaccurate in some way.

Organisations with accurate data save significant money and have a competitive edge over those without it - see this example from Michael Iannuzzi, Director of Marketing & Sales Development at Drift:

It reduces the workload

According to ZoomInfo, an average B2B salesperson wastes 27.3% of their time searching for bad data.

With quality data, less work is required to find the correct information, which reduces SDR workload.

It improves personalisation

When the data is correct, you can better personalise your outreach messages.

Details, like whether the prospect’s company role or industry is up to date, will make all the difference to your business strategy.

It lowers the email bounce rate

Email bounce rate affects B2B teams significantly.

If your email bounce rate is too high, it signals to internet service providers (ISPs) that you’re sending spam emails. This reduces your chances of landing in your prospects’ primary inboxes.

As a result, your sales team wastes time and effort.

High-quality data helps to combat this by keeping your email bounce rate low. Essentially, this improves your email deliverability and overall outreach efforts.

How should B2B teams assess their data quality?

So, what are the practical steps to improving data quality?

Below, we’ve outlined seven steps in the quality improvement process. 👇

Evaluate your current situation

You can’t improve data quality without knowing your current situation.

As a first step, assess where you are now.

This includes answering questions like:

• Where is the data stored?
• How is the data collected?
• Who can access the data?
• What is the current data format?
• Who is responsible for data management?
• How often is the data updated?
• How do we currently measure data quality?

Address current data quality issues

It’s easier said than done, but addressing data issues is key to improving quality.

Some of the most common data quality issues include:

• Inaccurate data - due to misspellings and errors made by humans (or tools).
• Duplicate records - adding B2B data to sales engagement tools or CRMs without checking if it already exists.
• Formatting inconsistencies - for example, there are multiple ways to express a date, such as November 10th, the tenth of November, or 10/11.
• Irrelevant data - not all data is valuable, and storing irrelevant data can create security and compliance risks.
• Missing data - such as prospects’ job titles and companies.
• Non-compliant data - having data that doesn’t comply with the GDPR and other B2B compliance laws presents a huge problem.

You may think, what causes these issues?

There are many reasons, one of which is a lack of correct policies.

For example, you might have imported company data from a validated lead list years ago. Since then, many key decision-makers may have changed their companies or roles within them.

With data quality rules in place, you can implement regular audit checks and create strict data entry protocols.

Validate your data

Data validation ensures the accuracy and quality of B2B data. It involves verifying that your data meets the specified format and requirements.

Data validation helps to prevent:

• Non-compliant data.
• Duplicate data.
• Inconsistent data.
• Inaccurate data.
• Outdated data.

Working with reputable vendors like Cognism is the best way to ensure valid data. Buying lead lists from unscrupulous vendors can quickly lead to issues with data quality.

It’s not worth spending your money on poor-quality data, as this will immediately impact your sales outreach efforts.

If you use data providers, ensure they validate emails and phone numbers, update their database frequently, and maintain compliance.

Data enrichment is also beneficial since it prevents B2B data depreciation and duplication.

Cognism is a data provider that meets all of these requirements. Click here to schedule a demo with our team.

Create a data governance policy

Creating data governance policies ensures that data is managed appropriately.

These policies essentially act as building blocks to establish a structured system for data integrity, security, and compliance.

A data governance framework should include the following:

• The persons responsible for managing data.
• The tools used for data management.
• The metrics for tracking data efficiency.
• The training provided for employees.
• The processes for obtaining and storing data.

This quality framework should include policies and the people responsible for data stewardship.

Data stewardship teams ensure data quality within departments or areas.

Knowing who’s responsible for your governance framework improves accountability. It also enables quicker resolution of compliance and quality concerns.

Organise all data in one place

A LinkedIn and Edelman’s survey found that:

• 87% of sales and marketing leaders believe collaboration between sales and marketing drives growth.
• And 98% of the same sales and marketing leaders believe bad alignment negatively affects business.

In many B2B companies, it’s common for sales to use one type of software, marketing another, and IT yet another.

There are a few major issues with this approach.

Using multiple software quickly leads to siloed data and a lack of departmental collaboration.

A centralised system for all data allows departments to collaborate more effectively and share insights.

Educate and train your employees

Human error causes many data quality issues. However, it isn’t necessarily your employees’ fault if they aren’t adequately educated in such matters.

To prevent your team from falling into these pitfalls, educate them on data management best practices.

You can:

• Create SOPs outlining the data management strategy.
• Conduct training sessions to keep employees up-to-date with the best practices.
• Use real-life examples to demonstrate the effects of poor quality data on profitability and commissions.
• Create policies for buying B2B data.

Update your data quality procedures

Effective data quality management is not a one-time project.

You must continuously review and update your policies and best practices.

The difficulty is that updating data quality procedures without a valid reason can lead to problems.

For this reason, you can determine if changes are needed by:

• Monitoring data quality metrics - such as completeness, accuracy, uniqueness, and timeliness. This helps detect issues early on.
• Implementing feedback loops - from those interacting with the data. This can highlight inefficiencies in data handling or gaps in the data itself.
• Performing regular data audits - to ensure that data remains accurate, consistent, and meets organisational requirements.
• Staying informed with regulatory changes - ensuring your data quality policies remain compliant.

In addition, you should maintain accurate documentation of your processes, data sources, and systems.

Keep this in mind when approaching data quality challenges:

“If you don’t write it down, it doesn’t exist.”

The 5 best tools for managing data quality

Companies can use different B2B databases to improve their data quality.

With these tools, you can minimise bad data’s effects on your business.

Below are the five best B2B data tools. 👇

1. Cognism

With Cognism, you can access high-quality and up-to-date company and customer data that complies with the GDPR and CCPA.

It lets you reach ideal clients through business emails, direct dials, and phone-verified mobile numbers.

It also offers an AI Search tool.

With this new feature, you can write or say what you’re looking for in plain terms, and our AI engine will surface accurate results.

For example, if you type “Find me marketing leaders in London in companies with over 500 employees,” the AI generates a list of relevant leads.

Watch this video to see how AI Search works 👇

Why do B2B teams choose Cognism’s sales intelligence platform?

• High-quality and up-to-date B2B data that is GDPR and CCPA compliant.
• Phone verified mobile numbers.
• Unrestricted access to person and company-level data (subject to fair use policy).
• AI Search for lightning-fast prospect list-building.
• Integrates with leading CRMs, including Salesforce, HubSpot, Pipedrive, and Microsoft Dynamics.
• Cognism Chrome extension for prospecting on LinkedIn and corporate websites.
• Pricing tailored to your individual needs and workflows.
• Ask Cognism for a quote.

2. Kaspr

Kaspr helps B2B teams quickly find accurate contact information.

One of its key features is its Chrome Extension. It helps you get GDPR and CCPA-aligned emails and phone numbers from LinkedIn.

Kaspr integrates with CRMs and sales tools for accurate data transfer.

Sign up for free here.

3. ZoomInfo

ZoomInfo is a B2B lead database that collects, verifies, and publishes millions of contacts and company profiles in real-time.

It provides insights into industries, employee headcount, revenue, company location, and more.

ZoomInfo relies on community verification for phone numbers rather than conducting individual in-house verification.

UserEvidence conducted A/B quality testing between Cognism and ZoomInfo - Cognism came out on top, as UserEvidence SDR Hayden Fake said:

4. Lusha

Lusha provides sales teams with verified B2B data.

It’s mainly known for its Chrome Extension. You can open it on LinkedIn, Salesforce, Sales Navigator, or any company site to quickly access prospect contact data.

Lusha used a credit-based pricing system, which is a minor downside. All Cognism licenses include unrestricted data access and individual and page-level exports (subject to fair use policy).

5. UpLead

UpLead is a business intelligence tool that offers contact and company information.

Business users can search for prospects by industry, location, technology, employees, title, and revenue. It also provides a Chrome Extension that works on LinkedIn and company websites.

Some G2 reviewers say UpLead’s data isn’t as accurate as Cognism’s.

Achieve better data quality with Cognism

Salespeople are notorious for wanting to close deals quickly. This can lead to them cutting corners, such as neglecting data quality.

This isn’t ideal since, as we’ve explained, quality data is essential to sales success!

High-quality data matters, but it doesn’t have to mean a slow and inefficient prospecting process.

Cognism is your partner for improving your business data. Here are just some of the benefits we’ve brought to our 3,000+ customers:

• Ultima increased its dial-to-connect ratio and significantly shortened its sales cycle.
• Protolabs saw an email deliverability rate of 95-98% from using our data.
• Henderson Scott switched its data provision from Lusha to Cognism due to compliance concerns. 

We’d love to do even better for you! As a start, why not try Cognism’s data for yourself?

Click 👇