Why data quality is now a regulatory control

Do you know where to find specific data in your business or who to contact for that data? Modern businesses know that making data-driven decisions is critical to improving their bottom line. A strong data governance strategy saves time and money by improving data quality and making it easy for teams to get the information they need. By following data governance best practices, you can reap the benefits of implementing the best data governance framework for your business. What is data governance? Data governance is the set of processes that make sure data meets business standards and rules as it’s entered into a system. It lets businesses control the management of data assets. Data governance involves three aspects that make sure data is usable, accessible, and fits its intended use: People Process Technology A data governance plan is important for different types of organizations and industries. It’s especially important for those that have regulatory compliance, such as finance and insurance. To meet compliance regulations, organizations must have formal data management processes in place to govern their data throughout its lifecycle. While data governance is a key focus for many organizations, not all strategies return the anticipated results. Best practices for data governance Following strong data governance practices means your business gets the most from a data governance strategy. We know what methods work best when building a data governance policy. When developing your data strategy, one of the best data governance tips is to first focus on people, then refine processes, and finally integrate technology. 1. Get business stakeholders on board To begin creating the best data governance strategies, you need executive buy-in, but getting a green light is just the start. You also want to inspire stakeholders to take action so your governance plan is adopted across your organization. The best way to get executives excited about your plan is to build a business case for your data governance practices. By building a business case, you show leadership the specific benefits they can expect from a data governance strategy. 2. Data stewardship Data governance practices are only successful when roles, responsibilities, and ownership structure are clearly defined. Defining the data governance roles of team members across your organization creates the framework on which a governance plan runs. The goal of data governance is to improve data quality and collaboration between teams. It needs input and data ownership from all parts of your organization. While each organization’s data governance structure will look slightly different, there are a few key players to use in your framework: Data governance council or board: This team oversees the entire governance strategy. They help guide the data governance plan through strategic suggestions, typically prioritize aspects of the strategy, and approve new policies. Tactical team members: Members of the tactical data governance team develop data governance strategies based on the council’s suggestions. They create the data processes and policies that are then approved by the data governance council.Owners: Data owners are the team members responsible for specific data. They are the person of contact when someone needs a certain type of data. For example, if you need last month’s sales information, you contact the sales data owner.Data users: Team members actively inputting and using data as part of their regular work responsibilities. Putting the right people in the right roles is one of the best practices for data management, especially when creating a data governance framework.  3. Data quality management Your business needs data quality management to create the best data governance strategies. It enables you to harness the full potential of your data assets for informed decision-making, competitive positioning, and customer satisfaction. By guaranteeing consistent, secure, and credible data, your organization can unlock numerous benefits contributing to your success in today’s dynamic marketplace. Data governance is pivotal in unlocking better data quality by creating systems promoting actionable, accurate, and complete data. It empowers your business to adapt swiftly to evolving market trends and customer preferences. Your business can enhance the customer experience by delivering personalized communications, promotions, and customer service interactions. High-quality data is needed for informed decision-making, and having it means you can confidently navigate any challenges your business faces and achieve your objectives. 4. Use metrics to measure progress As with any change, it is critical to measure progress and display the success of your data governance program. Once you have executive sponsorship from your business case, you need data to support each step you take. Plan on defining your metrics before you start introducing data policies. This lets you set a starting point based on your current data management practices. Track your progress using the original metrics regularly. Not only does this show how much progress has been made, but it serves as a checkpoint to make sure your data governance best practices are effective in practice and not just in theory. A plan that’s flawless on paper may not transfer to real life as well as you hoped. It is important to keep a close eye on your governance strategy and be flexible regarding adjustments and improvements. 5. Data security and privacy When creating your data strategy, it is crucial to make sure your business’s data is safe and private. Data security practices protect data against unauthorized access, alteration, or destruction. Encryption techniques, access controls, and authentication mechanisms are commonly employed to mitigate risks associated with data breaches. Additionally, organizations often implement firewalls, intrusion detection systems, and data loss prevention solutions to bolster their defense mechanisms against external threats. Data privacy concerns the ethical and legal obligations surrounding the collection, use, and disclosure of personal data. With more data-driven technologies available and the increasing volume of personal information collected by organizations, customer concern about privacy continues to grow. Organizations must adhere to established privacy regulations such as the GDPR (General Data Protection Regulation) in Europe or the CCPA (California Consumer Privacy Act) in the United States. Complying with these regulations means implementing privacy policies, data anonymization techniques, and consent management procedures to protect customer’s privacy. The best data governance strategies establish clear guidelines for data usage and dissemination for accountability purposes and to foster responsible data stewardship. The best way to handle security and privacy in a data governance plan is through transparent communication regarding data practices, along with regular audits and assessments.  6. Encourage frequent communication Whether you’re just starting a data governance program or have been practicing one for years, communicating early and often is essential. Consistent and effective communication helps show the impact of the strategy—from highlighting successes to reorganizing after a setback. An executive team member, such as the Chief Information Officer (CIO) or Chief Data Officer (CDO), should become the communications leader of the data governance program. These leaders are the central contact for the current status of governance practices across the organization. Team leaders and data owners can give regular updates to the executive. The executive team member then brings the most important updates to the rest of the leadership team and the organization as a whole. 7. Data architecture and metadata management Another one of the best practices for data management when creating your data strategy is using the right tools, data architecture, and processes. Data architects are critical in developing appropriate models and architectures to integrate and manage data across disparate systems. Central to a data governance framework are well-defined processes governing data storage, access, security, and management.  Metadata management processes allow your organization to maintain an inventory of data assets and verify their relevance and accuracy. Well-defined data governance processes govern data storage, access, security, and management, ensuring compliance with regulatory requirements and maintaining data integrity throughout its lifecycle. All of these processes are tailored to your organization’s objectives and structure, serving as guiding principles for data governance initiatives.  8. Data governance is a practice, not a project Creating a data governance program often feels like tackling a new project. You might be tempted to assemble a team to take on the project while the rest of the organization waits for it to be done. This is where many businesses see their data governance strategies slow down. A data governance strategy isn’t a one-time project. There is no set end date or conclusion. Instead, it’s an ongoing practice that’s introduced as a regular policy. Much like dress codes or policies for requesting time off, the best data governance strategies become part of everyday life at your organization. Ready to put data governance practices to work? Implementing the best data governance framework for your business helps it work more efficiently, but you’ll need to build a business case for stakeholders before getting started. Find out how to get the green light for your data governance strategy by connecting with our team today!

Regardless of what industry your business falls into, email remains one of the most powerful tools your team can leverage for marketing initiatives. But here’s the thing—no matter how great your email content is, it’s almost useless if it’s not reaching the right audience. If you’re sending emails to invalid, outdated, or fake addresses, you’re essentially throwing time and money down the drain. That’s where email verification comes into the equation.  By ensuring that your email list is clean, up-to-date, and accurate, you significantly boost your chances of success. With the help of email verification, you can improve deliverability, protect your sender reputation, and drive better engagement with your audience. In this blog, we’ll walk through the real-world benefits of verifying email data and provide some email verification examples that show exactly how this simple tool can transform your email marketing strategy.  Why email verification matters: The real-world benefits Boosted deliverability rates Email verification ensures your emails reach active inboxes and not invalid addresses, reducing bounce rates and protecting your sender reputation. Using bulk email validation to clean your list and real-time email validation during sign-ups helps keep deliverability high and resources focused on valid contacts. This means your messages are more likely to reach engaged recipients, improving overall campaign performance. Clean lists also lead to fewer delivery issues, allowing for better targeting and increased chances of reaching key customers.  Enhanced sender reputation Writing compelling emails is important, but ensuring they land in your recipients’ inboxes—rather than their spam folders—is just as crucial. Your sender reputation plays a key role in whether Internet Service Providers (ISPs) deliver your emails to inboxes or mark them as spam. Sending emails to invalid addresses or engaging in poor practices can damage your reputation, potentially leading to blacklisting.   Using email verification tools helps maintain a clean, verified email list, safeguarding and improving your sender reputation. A strong reputation boosts the chances that your emails are delivered, opened, and engaged with—critical for the success of your marketing campaigns.   Cost savings Email marketing can get expensive, especially if you’re paying based on the volume of emails sent. Sending emails to invalid addresses is a waste of resources since not only are you paying to send emails to inboxes that won’t engage with your content, but bounced emails can lead to increased costs for managing and cleaning your list. Plus, some ESPs may even charge you additional fees or suspend your account if your bounce rates are too high.  By verifying email addresses before sending your campaigns, you save money by ensuring your emails only reach valid addresses. This also helps reduce costs related to managing and cleaning your email lists, making email verification a smart investment for businesses looking to improve cost efficiency while maximizing ROI.  Boosted engagement rates A clean, verified email list translates directly into better engagement. When you ensure that your emails are delivered to real, active addresses, your chances of getting a positive response increase. This includes higher open rates, more clicks, and increased conversion rates. The result? More successful campaigns and better overall marketing performance.  Furthermore, when you target engaged users, you’re able to nurture better relationships with your audience, which fosters customer loyalty and repeat business. Engaged subscribers are more likely to share your content, sign up for events, and make purchases.  Enhanced data quality Potentially one of the most overlooked, yet important, benefits of email verification is the improvement of your overall data quality. By eliminating invalid and outdated email addresses from your list, you’re left with only accurate, actionable data and taking a proactive data approach. This higher-quality data allows you to make more informed decisions about your marketing strategy, personalize your campaigns effectively, and improve the overall experience for your customers.  Email verification examples: real world examples Now that we’ve discussed the benefits of email verification, let’s explore some email verification examples that demonstrate how this process can directly impact businesses.  Example 1: Retail A popular retail brand was facing declining email performance, with many of their promotional emails either bouncing or ending up in spam folders. After adopting email verification, they cleaned their list by removing outdated or invalid addresses, ensuring that only active, engaged customers received their emails. This simple adjustment led to a noticeable improvement in deliverability, boosting open rates, engagement, and ultimately, sales. With a more refined list, the retailer was able to connect with the right audience, driving more effective campaigns and better overall results.  Example 2: Nonprofit A nonprofit organization frequently uses email to communicate with donors and supporters about upcoming events and fundraising efforts. Unfortunately, they struggled with low engagement and high bounce rates, which impacted their ability to connect with key supporters.  After incorporating email verification into their workflow, the nonprofit was able to identify and remove invalid addresses. As a result, their emails began reaching a more engaged audience. Not only did this increase event attendance, but it also boosted donations and participation, enabling the organization to achieve its goals more effectively.  Example 3: Healthcare A healthcare provider that regularly sends appointment reminders, newsletters, and health tips was struggling with low patient engagement due to undelivered emails. By implementing email verification during patient sign-up and appointment scheduling, they ensured that only valid, up-to-date email addresses were added to their list. As a result, they saw a significant increase in email deliverability and patient interaction. This led to fewer missed appointments, improved patient communication, and a stronger overall relationship between the provider and their patients.  Why your business needs to invest in email verification All in all, the real-world benefits of email verification extend far beyond simply ensuring that your emails reach the right people. By verifying your email list, you improve deliverability, protect your sender reputation, save costs, increase engagement, and improve the overall quality of your data. These advantages can make a huge difference in the success of your email marketing campaigns and help propel your business towards success.  If you’re ready to take your email marketing to the next level, start by verifying your email list today. The benefits are undeniable, and the impact can be felt almost immediately.  Connect with a data quality rep today to learn more about how you can get started. 

Organizations rely on data to make everything from day-to-day operational decisions to long-term strategic investments. But simply collecting data isn’t enough. To get value from it, you need both high-quality data and a strong data governance framework. Although the terms data quality and data governance are often used interchangeably, they serve different purposes. Data quality focuses on the condition of your data, while data governance establishes the policies, processes, and accountability needed to manage it throughout its lifecycle. Together, they help organizations build trust in their data, reduce risk, improve compliance, and make better business decisions. What is data quality? Data quality refers to how well your data meets the needs of your business. High-quality data is: Accurate Complete Consistent Timely Valid Fit for its intended purpose Poor data quality can lead to duplicate customer records, failed deliveries, inaccurate reporting, compliance issues, and poor customer experiences. Data quality is maintained through ongoing processes such as: Data validation Data standardization Data cleansing Data matching and deduplication Data enrichment Data profiling and monitoring Rather than treating data quality as a one-time cleanup project, organizations should continuously monitor and improve data as it’s collected and maintained over time. What is data governance? Data governance is the framework that defines how data is managed across an organization. It establishes the people, policies, standards, and technologies that ensure data is secure, reliable, and used consistently. A successful data governance strategy helps answer questions like: Who owns this data? Who can access it? How should it be maintained? What quality standards should it meet? How do we ensure compliance with internal policies and external regulations? While governance sets the rules, it also creates accountability for maintaining trusted data across the organization. Data quality vs. data governance: Key differences Although closely related, data quality and data governance address different aspects of data management. Data qualityData governance Focuses on improving the condition of dataFocuses on managing data throughout its lifecycleMeasures accuracy, completeness, consistency, and validityDefines policies, ownership, standards, and accountabilityUses validation, cleansing, matching, and enrichmentUses governance frameworks, roles, policies, and controlsImproves trust in business dataEnsures data is managed consistently across the organization Think of it this way: data governance defines the rules, while data quality ensures the data meets those rules. Why data quality and data governance work together Neither initiative is fully effective without the other. Strong governance establishes the standards your data should meet, while data quality processes continuously measure and improve data against those standards. For example, a governance policy may require every customer record to contain a valid mailing address. Address verification and validation tools help enforce that policy by identifying incomplete, incorrect, or undeliverable addresses before they enter your systems. Together, governance and quality help organizations: Build confidence in business decisions Improve reporting and analytics Increase operational efficiency Strengthen regulatory compliance Reduce duplicate and inaccurate records Deliver better customer experiences Build a stronger data management strategy Data quality and data governance aren’t competing initiatives—they’re complementary parts of an effective data management strategy. Governance provides the framework, while data quality ensures the information within that framework remains accurate, complete, and reliable. With Experian’s data quality solutions, organizations can validate, standardize, enrich, and monitor their data to support governance initiatives and improve confidence in every business decision. Explore Experian’s data quality solutions to learn how you can improve data accuracy, strengthen governance efforts, and build greater trust in your data.