What is data standardization?  Let’s find out more about the importance of data standardization for B2B aggregators, its benefits, steps implemented towards data standardization and the tools used.

In data standardization, data is transformed or manipulated to a consistent format. In business, data is likely to be stored in a variety of disparate systems with different rules and formats.
If it’s not organized then your organization’s data can be misinterpreted and misunderstandings might result  from these small differences. When data is inconsistent, trust is made, second-guessing occurs, and time is lost checking whether conclusions made from that data are correct.

If you’re working in a data-driven company, you’d be better off using the data rather than manually verifying and updating it. As a result of standardization, manual checks can be eliminated. It is easier to focus on using your data if you have the right data standardization tools at your disposal.

On a day to day basis, business contacts and data change at an incredible speed resulting in data decay, making data standardization critical for b2B data aggregators. Data standardization is the key to a comprehensive, accurate and up to date B2B database.

It is said that on an average business loses around 12% of their revenue due to bad data. Apart from revenue loss, bad data results in poor marketing strategies, misguided communications, and weak CRM and automation processes.

In simple terms, data standardization is a data processing technique that converts all the sourced data into a common, easy-to-understand format:

• Clean database
• Consistent database
• Organized Database

Importance of Data Standardization for B2B Aggregators.

• Allows for better marketing strategies
• Easy to automate workflows and processes
• Efficient monitoring of key performance metrics
• Promotes better data hygiene practices
• Standardization improves brand credibility and subsequently enhances revenues
• Compatibility with Machine Learning model requirements

Benefits of B2B Data Standardization

• Productivity Boost
• Better Customer Acquisition
• Centralized Availability
• Better Business Strategies
• Harmonious Flow to AI Tools

5 Important Steps to Data Standardization:

You have to define your standards by having a set of rules for each field of your database, based on your business requirements. In case you are using separate systems, make sure you have the same language across platforms.

Know your Data: Being aware of data auditing is an important step before you begin your data standardization. In a practice called data stewardship, a company can organize, collect, audit and ensure data quality. This process makes sure that the data is trusted and usable.

Know your source: Quality source will make it easier for you to standardize your data. Once you have collected all the data, make sure that the integration process itself involves standardization.

Automate the Process: B2B database enterprises require some form of autopilot to get through their vasy stored data,  Automatic segmentation and routing or automatic merging of duplicates allow for smooth data standardization.

Tools and Techniques of Data Standardization

• Data Normalization
• Distance-based Algorithms
• Z-Score Scaling
• Standard Deviation

infoAnalytica converts business contacts and company data to a common format to empower aggregators to have a comprehensive, accurate and up to date B2B database. We provide technology enabled data standardization services for enterprises and e-commerce giants like Amazon, Flipkart, eBay, etc.

You can reach us at inquiry@infoanalytica.com to give it a try!