Outdated, missing, or incorrect data can adversely impact customer experience. How can data hygiene streamline information and accelerate engagement?
Data forms the core of every business. Any gaps in it can hinder effective communication with the target audience. That’s why, all information needs to be accurate and error-free. Hygiene in data makes it possible for brands to seamlessly manage all critical information. When integrated with automation, it can swiftly improve customer experience and brand productivity.
For data hygiene, you need to focus on two types of data: dirty and clean. Dirty data refers to the information that piles up, duplicates, and eventually has no use. If most of your data is outdated and tough to access, it indicates that it’s time to implement a cleaning process. Dirty data can cost around $3 trillion per year in the US. The hygiene process must be implemented to maintain data quality. Clean data is clear, concise, and easy to access, increasing performance efficiency.
We have prepared a list of best practices to help you manage and maintain a clean business database.
How to implement Successful Data Hygiene
These 5 steps will enable you to minimize inaccurate information and maintain your brand’s integrity and reputation. Let’s dive in.
Audit data
As a B2B brand, your teams have most likely collated data from multiple sources, which can pool into siloes. And when this happens, the data is difficult to identify and may become prone to errors. Nearly 27% of business leaders have reported being unsure of their data accuracy. An audit helps to keep things in check and store high-quality data.
This step provides a clear overview of the brand’s database and finds gaps, if any. It involves identifying data fields critical for integration and monitoring the quality and completeness of each field. With data audit, you can easily identify consistencies, duplicates, missing values, and outdated information. Since manual audits can be time-consuming and tedious, automating data hygiene can go a long way.
Eliminate unnecessary files
Brands deal with so much data daily that unnecessary records may pile up. Excess data can produce clutter if not managed properly. And when you have irrelevant information, it becomes cumbersome to analyze and audit the infrastructure. This can be avoided by conducting a periodic review of your data. Removing outdated information would streamline your customer database and make it concise.
Validate Accuracy
Data accuracy is an essential element that promotes customer satisfaction. You can ensure accuracy by incorporating validation rules that verify data integrity and adhere to predefined criteria. Validate email addresses, phone numbers, and postal codes to double-check if they are in the correct format. If you run a data check regularly, you can avoid messy and fragmented information, transforming it into accurate and unified records.
Establish Standardized rules & constraints.
When standardization is not regulated, it may lead to the piling of dirty data. Studies indicate that around 60% of dirty data is due to human error, and you can reduce these instances with automated data hygiene. Standardization can take you a long way in preventing dirty data. All you need to do is look into the input fields. Simply put, all numbers and monetary values require standardization. And there should be no case sensitivity, spelling errors, or abbreviations. Data standardization and consistency are crucial elements in creating uniform databases. Applying rules and standards filters out unnecessary information while delivering brand consistency.
Update your data
Data, if not maintained, can become outdated, which makes it frustrating to sort through. Your prospects may change addresses, get new designations, or change jobs altogether. Studies suggest that nearly 21%of CEOs change every year. You may be surprised to know how fast data can decay —at the rate of 70% per year. If the data is not updated, you may deliver messages to the wrong contact. Updating your customer database in real-time with data hygiene prevents your teams from chasing dead-end leads and helps build strong relationships with prospects. Since you cannot predict when data will go outdated, opt for an automated data cleaning tool.
Final thoughts
Data is an asset for your business. Without a concrete strategy in place, it can create inconsistencies/errors, and require investment of resources to get it in order. These practices will build a solid foundation for data accuracy and reliability. The best bet is to be proactive about data hygiene, ensuring that all information entering a system is accurate, reliable, and comprehensive. It allows efficient integration of data in your system. Keeping your company database clean and compliant with regulations minimizes your chance of poor data.