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Holding onto data is almost useless for a business if it does not have a proper data management strategy. A robust data management strategy relies on a methodical, step-by-step approach—much like how you'd approach building a house. We've used this analogy many times here at Experian Data Quality, but that's only because it makes a lot of sense when referencing data standardization. Data standardization is but one step to building a good data management strategy, but it is a fundamental step in making your data actionable. Just as a solid foundation is essential for a strong house, data standardization is necessary to build a strong data management program. As a result, it is in your best interest to invest in a data standardization system. Data standardization allows organizations that strive to be data-driven to make decisions quickly and efficiently. What is data standardization? Data standardization is the process of transforming or manipulating data into a consistent format. As businesses collect data, the information most likely settles into multiple, disparate systems, all of which may have slightly different rules and formats for how the data is stored. These small differences can result in misunderstandings and misinterpretations of your organization's data. Inconsistent data leads to distrust, second-guessing, and time lost completing checks to verify that the conclusions made off that data are actually correct. In a data-driven business, time will be far better spent acting on data than manually verifying and reformatting it. Standardization takes manual checks out of the equation. With the right data standardization tools, you can spend your time using your data rather than fixing it. How does data standardization work? The business data standardization process takes data from multiple disparate sources and, based on rules you define, transforms it into a consistent, usable format. It gets rid of anomalies and outliers, so that you can identify errors in your data and make it easier to analyze. Due to differing requirements across different systems, along with typos and human error, the data that flows into your organization comes in a variety of formats. Using multiple data entry systems can lead to inconsistent capitalization, punctuation, obscure acronyms, alpha-numeric characters living in fields they shouldn't be, and so on. Data standardization tools eliminate these inconsistencies and help you define how data should appear in your database. Unlike data cleansing, which periodically corrects and eliminates errors in data, data standardization is an ongoing process to connect and sync formatting across multiple data entry systems. Data standardization is helpful for properly formatting: Country and state abbreviations Email addresses Company names Addresses Common typos and mispellings Phone numbers How does data standardization benefit my business? Data standardization is crucial for a data-driven business. Any business can store data, but clean, clearly formatted data that can inform business operations will set a business apart. The advantages of data standardization allow your business to do the following: Improve data accessibility Data is most effective when it is accessible to as many people in an office as possible. When data can be easily shared between staff members and departments, businesses are more efficient in decision-making and developing action steps. Consistent data allows everyone to be on the same page at all times without needing to reconsider or reformat data. Save time and money Second-guessing your data has consequences. The need to manually verify and correct data uses valuable time that could be spent making decisions and taking action. Data standardization confirms that your data is formatted consistently regardless of which system was used to collect it, and consistent data means you can trust your investments. Make more informed decisions Data that follows a common format is easier to interpret, sort and analyze. Easy-to-interpret data allows you to recognize trends and gain further insight into your customer base, allowing you to better informed decisions as a result. When you make data-supported decisions, you are able to strategically target your spending and investments, providing you with a higher return. Reach your customers Standardized data plays a key role in reaching new and previous customers. Consistent formatting for data like email addresses and postal addresses ensures that you can reach your customers through targeted marketing campaigns. With reliable data, you position your campaign to be as successful as possible and do not waste money sending to incorrect or improperly formatted addresses. Why should my business standardize data? Ultimately, standardized data increases efficiency and potential. If you're still in need of convincing, I'd be happy to share a personal use case. My organization relies on a marketing automation platform, a CRM, and Google Analytics, in addition to more platforms that all collect and store data. This data is crucial for business-wide forecasting and projections. As we strive to gain insight from our data, it is imperative that everyone has a standardized view and understanding of the data being used to make these decisions. Unstandardized data would be a nightmare in these processes, leading to confusion between departments and wasted time spent manually converting data. It is necessary that everyone in the business is on the same page and is able to easily interpret and analyze data, otherwise, data is more of a burden than a value. If you're undergoing a data migration or modernization project or if you've been charged with cleaning up your customer database before initiating a loyalty program or marketing initiative, data standardization is a non-negotiable first step in the process. Data is one of the most important assets businesses hold today. It can either empower your organization to connect with new customers and reach new heights or be a deadweight that wastes time and drags your team down. I think the choice here is clear. Standardize your data for a higher return on investment Why run the risk of letting inconsistent data sabotage your success? Treat your data as a strategic asset. Easy-to-interpret and reliable data is invaluable for decision-making, systems efficiency and building customer connections. Standardization is the key to maximizing its potential and seeing higher gains from your data. At Experian, we can help you standardize your data to increase its value. 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High-quality leads are crucial for sales success. These leads are not just names and phone numbers on a list; they represent potential customers who have shown genuine interest in a company's products or services and are more likely to convert. By focusing on lead quality, sales teams can allocate resources more effectively, prioritizing leads that are more likely to result in successful sales, increasing the conversion rate, and enhancing overall productivity. Enter phone validation, the process of verifying that a phone number is accurate, active, and capable of receiving calls or messages. Ensuring it is correctly formatted and belongs to a legitimate carrier, and an essential tool in enhancing lead quality. This reduces time on invalid leads and improves the chances of successful communication and engagement with potential customers. Furthermore, phone validation can help identify fraudulent or duplicate entries, maintaining the integrity of the lead database. Benefits of implementing phone validation Implementing phone validation helps maintain a clean database, streamline operations, and maximize the return on investment in marketing and sales efforts. Here are some of the key benefits our clients have reported. Improved accuracy: By verifying the accuracy of phone numbers, including format, country code, and activity status, you can enhance your overall communication strategy, ensuring messages reach the intended recipients seamlessly. Enhanced efficiency: Phone validation allows you to quickly identify and eliminate invalid phone numbers from their contact lists, allowing sales and marketing teams to focus on leads with higher conversion potential. Efficient lead management translates to a more productive workforce and quicker response times to potential customers. Cost-effectiveness: Removing invalid or inactive phone numbers helps avoid costs associated with unsuccessful outreach attempts, allowing investment in quality leads with a higher conversion potential. Better targeting: Validated phone data enhances audience segmentation, enabling more effective targeting to specific customer profiles. With validated phone numbers, tailor marketing campaigns to specific demographics or customer profiles, ensuring messages are relevant and engaging. This enhances customer relationships, increases conversion rates, and drives higher revenue. Steps to implement phone validation Ready to onboard a phone validation solution into your existing tech stack? Keep these steps in mind when choosing the right solution for your business. Choose the right phone validation service provider: Consider deployment options, accuracy, reliability, user-friendliness, data freshness and advanced software. Integrate phone validation into your existing sales process: Prepare your CRM or sales software to incorporate the validation service, ensuring real-time verification without disrupting workflow. Train your sales team on the new process: Conduct comprehensive training to familiarize them with the technology and explain how it enhances lead quality and customer interactions. Experian Phone Validation offers simple and actionable validation responses, flexible deployment methods to suit any environment, and a user-friendly portal. Our phone validation solution covers 1500+ telecommunication providers in 240 countries and territories that standardize the format, add international dialing codes, and process data checks with telecommunication providers. In addition, we offer Phone Append that return the phone number associated with the user's name and address and Reverse Phone Append that helps tie your existing phone data to other important customer data. In today's competitive market, ensuring the quality of leads is crucial for any successful sales strategy. Phone validation stands out as a powerful tool in enhancing lead quality, improved data accuracy, cost efficiency, increased conversion rates, and improved customer engagement. By integrating phone validation, you can enhance lead generation processes, boost efficiency, improve client communication, and ultimately achieve higher success rates. Implementing this technology can help sales solidify a foundation for sustained growth and competitive advantage. Start today with a free trial of Experian’s Phone Validation solution. Reach out to one of our data quality experts to learn more about our comprehensive product suite. Fill out the form to learn more:

Data-driven decision making has become a necessity for the best businesses to stay on top of their daily operations and respond to areas for improvement. However, the quality of this data will greatly affect how useful it will be. Maintaining a high quality of data allows you to make decisions that improve customer relations and increase revenue. Poor quality data informs poor decisions and restricts access to customers while also using up time and resources to correct. Because of its capabilities, data should play a vital role in informing your business decisions. As a result, your business should have a clear and well-thought-out plan for how data will be collected, maintained and analyzed. Improving your data quality through careful data collection and maintenance should be a key part of your business operations and will set your business apart from the others. Benefits of improved data quality Improved data quality gives you a complete, accurate picture of your business and the customers you serve, allowing you to make more informed decisions that save time and money. High-quality data can be used to inform marketing campaigns that increase customer engagement, develop more trust in customer relationships and receive a higher return on investment in sales and marketing strategies. Access to accurate data takes the guesswork out of key business decisions, increasing efficiency and saving costs. By following just a few steps, you can set your business up for success with a clear plan for collecting more valuable data and using it to inform critical business decisions. Steps to improve data quality Many organizations manage data quality through separate departmental strategies, which can lead to inconsistent standards, duplicated efforts and less effective outcomes. Assigning a single data owner, such as a chief data officer, creates clear accountability for the quality, governance and standards of your data assets. Centralized ownership can also help align data quality initiatives with broader business goals and improve collaboration across departments. This central data owner should be supported by a team of data professionals—such as data stewards, data service officers, analytics professionals and data scientists—who can help enforce policies and promote the use of data to drive insights across the business. Implement proactive processes Improving your data quality requires careful and constant consideration to help your business maintain a strong and effective data strategy. Your business should develop a clear plan for using and analyzing data as well as keeping that data up-to-date and accurate. To improve and sustain your business’s data quality, you should carry out the following steps: 1. Develop your objectives Data quality means something different across different organizations. For some, it’s ensuring that customer contact data is accurate so that shipments are received in a timely manner. For others, it could be complete prospect profiles that help with marketing segmentation efforts. At its heart, data quality is about being fit for a desired purpose. In order to collect meaningful data, your business should have clear objectives in place for how this data will be used to improve decision-making and daily operations. When developing your objectives, you should consider the following factors: Your business goals How you measure progress towards goals What data you need from customers and clients How this data will be used and analyzed 2. Assess your current data Before implementing any data quality improvement plan, you need to understand where you stand today. Using the data quality sophistication curve, you can determine where you are related to data management efforts and what your next steps should be. There are four stages of sophistication your organization can fall into: Almost half of organizations today fall into the reactive or unaware stage, meaning there is a lot of room for data quality improvement. Data assessment should be a continuous process. The most successful businesses are constantly assessing the quality of their data and the effectiveness of their current data management plan. A constant reassessment of data allows a business to react to areas of concern and make improvements when necessary. 3. Cleanse your existing data Inaccuracies or inconsistencies in your data will harm your data quality and prevent you from using it for effective decision-making. Over time, data sets become riddled with out-of-date or incorrect information as customer data changes or information is improperly added to your database. Data cleansing is the process of correcting incomplete or inaccurate information, fixing formatting issues and more. Issues in your data set that require data cleansing include: Typos in data entries Incomplete data fields Inconsistent formatting of addresses or contact information Out-of-date contact information Duplicate data entries Addressing incorrect information in your database provides you with more confidence that your data provides an accurate picture of your customers and allows you to make appropriate business decisions as a result. There are a variety of tools available to help you cleanse your data. These tools include email address list cleansing, real-time address verification and more to help you cleanse your database of errors and also prevent incorrect information from entering at all. 4. Establish a data collection and management plan Because data collection issues are nearly inevitable, you should have a carefully considered plan in place to prevent these issues from arising and addressing them if they do. Being proactive with your data collection allows you to build a database of accurate and informative data instead of a database that needs to be fixed later. This will allow you to spend more time focusing on making decisions than fixing your data. Considerations for an effective data collection and management plan include preventing poor quality data from entering your database and consistently assessing the quality of the data you already have. Methods to include in an effective plan include: Using tools like real-time email verification to ensure accuracy upon entry Creating required fields on forms to avoid incomplete information Regular, periodic data cleansing to catch errors or outdated information Providing appropriate training to all staff involved in data assessment and decision-making Having a clear data collection and management plan will save your business valuable time and money correcting mistakes and allow you to be confident in using your data for strategic purposes. 5. Develop a plan for maintenance and improvement In order to maintain strong data quality and business growth, your business should have a plan in place to regularly assess the quality of data and its use in decision-making. Data-driven decision-making is a constantly evolving strategy. Effective plans for maintenance and improvement require consistent buy-in from everyone in the business. A data-driven business should foster a healthy culture of improvement where everyone is comfortable acknowledging when change is necessary. The ability to acknowledge when issues like flawed data collection methods or inconsistent data monitoring arise is monumental for business growth. Recognizing these issues and developing an appropriate response helps preserve your investments and will ultimately show greater returns than a business that is resistant to change. How to improve data quality for your business Implementation of data quality technology solutions across a company can streamline and unify data improvement efforts. This will result in the enforcement of consistent data standards across the organization, which means your data can be more easily used for advanced, comprehensive decision-making. To learn more about how to improve your data quality, download our paper on creating a strong and calculated data quality strategy. We also encourage you to try our email verification and data validation tools to strengthen your dataset. Contact Experian today to see how our tools and services can give you the help you need to collect, maintain and analyze accurate and meaningful data. Get help creating a data quality improvement plan

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