How Quality Data Let Businesses Grow

The growth of businesses depends on data metrics at present time. Data metrics show directions to the business by providing quality data analysis.

For quality data analysis, you need quality data by your side. Let's assess how you can bring quality data to your operations in this blog.

Organizations that highly rely on technology have the highest quality of data in their operations. Data quality standards must meet the current changes happening in the industry, as well as meet the current market demands. Having a reliable data flow into the system can change everything; it can improve the operation standards and get better outcomes.

When it comes to quality data for operations, companies have opined differently on different things. For some companies, it is the locational data, while some companies prefer contact information. Based on the working capacity and other staff, the demand for quality data in various operations changes.

For example, a company working in the advertising sector prefers more data related to marketing trends and customer needs. Or, a company in the logistics industry prioritizes locational data over anything. Hence, the pattern of choosing the data depends on the industry and work matters.

Data quality is essential and can directly impact the reliability and accuracy of information, which is used for decision-making. "Quality" of the data depends on various metrics. Let's talk about data quality dimensions to explain the importance of data quality further.

Reliability of data depends on various factors or dimensions. We have summarized all the factors here.

🔸Accuracy: Data must reflect real-world entities, and that would come out as accuracy. For example, name and other factors should come out authentically in the database. Suppose in medical records, the disease name or the medical conditions should come out as an existing one, not something no one has ever heard of. The medical condition must exist to be apparent in the medical records.

🔸Completeness: All the fields of the database must be completed with accurate and relevant datasets. Completless means filling up the data in real time. It can affect marketing strategies to a massive extent. Completeness is measured by the percentage of missing values to the total filled fields in a dataset. Businesses should always focus on maintaining the completeness of the data records. 

🔸Consistency: Data should be maintained consistently across the database in different data systems. Inconsistency can lead to many errors, and thus, it should not be there anymore in your database. Your database should follow a uniform format to remain consistent. For example, all your customers' contact information should be identical in both the CRM as well as billing system. Consistent flow of the data should be measured by comparing records of other databases. 

🔸Validity: Checking whether all the data follows the predefined format or not is the main task of the validity operations. For example, every email address on your mailing list should have an "@" symbol in it. Without this symbol, your email IDs are nothing but useless. Your datasets must be valid and have fewer errors while maintaining data integrity.

Improved data quality is the ultimate need of every business organization across all industries. Organizations nowadays are considering the best tools that fit their business goals. If you're the same and confused about where to start, here are some ways you can start to improve your data quality.

Email data should be entered into your database without any errors. Suppose you want to send an email to dwightshrut@shrutbeetfarm.com, but while you entered the data into your database, you maintained dwightshrut@beetfarm.com. This is a classic mistake and can happen when you put the records in the email database without any further revision.

To avoid such incidents from happening to your database, you need to verify your emails with experts. Or, you can follow some basic data verification methods and techniques to validate every single email ID before recording it in the database.

An email database plays a major role in marketing operations. Companies indulge in email marketing to get more connections and engage in conversation. Every single email costs them a lot when the operation size becomes huge. Hence, having a list of emails with accurate verification plays an important role here. The quality of the email ensures the business's success in email campaigns.

Similar to email marketing, text marketing can play a huge role in promoting your products if used correctly. Besides text marketing, phone numbers are used for cold calls and at the time of delivering the orders. Hence, you must have only validated phone numbers in your phone database. It's possible when you follow quality standards while recording your phone numbers into the database.

Phone numbers follow some dedicated formats. It must have area codes as prefixes. Each location in the world has a specific area code for phone numbers. When you have your prospects' phone numbers, you need to validate them by checking the prefixes before them.

Accurate location is extremely important to deliver items. Nowadays, delivery services are using GPS to find an exact match of the delivery location. The area code, PIN code, and other details should be maintained following all the protocols.

Removal of unnecessary information from the address database is also a part of the data quality enhancement program. Besides deduplication, other parts of the process are appending, validation, removal of junk, and other matters.

Maintaining the quality of the data becomes easy when you follow the data enrichment measures. Enrichment is a part of the data cleansing process, which is a broad thing overall. It helps update your existing information with current data and verify it with different sources. With the help of data enrichment, you can understand customer traits, their age, income, and other information strategically.

Lastly, implementing advanced data enrichment measures can help you get the right amount of data at the right data point with accurate measures. The quality of the data massively impacts the business growth. You must consider it.