Data Cleansing helps companies to use their data to increase ROI.
Organisations around the world depend on accurate data to fuel their communication and marketing campaigns. Whether it’s the customer’s contact information or buying history, these allow companies to create targeted campaigns to boost their ROI.
A study by the Harvard Business Review in 2017 showed that most companies don’t know how to make the most of their data. Organisations actively use less than half of their structured data, and analysts spend most of their time finding and arranging data.
This is where data management services like Azure’s come in. Through effective data management, you can make sure that the data you’ve collected provides significant value to your business.
Data Cleansing and Its Importance
Data cleansing is one of the methods used to ensure that data is accurate and valuable. It is the process of detecting, correcting and removing corrupt or incorrect records from a database.
Your business can achieve several benefits by cleansing data, some of which are:
- Better Decision Making: It helps provide information that supports better business analytics. This helps you make better decisions that will add to the success of your organisation.
- Enhanced Efficiency: By having a list of accurate data, you can get higher returns on your direct marketing efforts because you won’t encounter email bounces or returned mail.
- Improved Productivity:Your staff won’t have to contact customers with outdated information. It also helps your business to be GDPR compliant.
- Increased Results and Revenue: Clean data leads to a greater return on investment on marketing and communication campaigns. It helps you deliver a targeted and consistent message to the right audiences, which leads to a higher response rate.
How Data Cleansing Works
An effective data cleansing process is the key to gaining the benefits of clean and accurate data. Data cleansing can be done through these four simple steps:
1. Data Audit. Examine all databases to identify irregularities and inaccuracies.
2. Use of Multiple Data Cleansing Methods. This involves the removal of typographical errors, the validation and correction of errors and making data more cohesive (such as the change of “street” to “st”).
3. Data Consolidation. Customer information such as addresses, phone numbers and additional contacts are combined.
4. Data Deletion. Inaccurate information is deleted from the database.
Information like addresses, phone numbers and companies change frequently, so it is not a one-time process. By regularly updating your database, you can ensure that the data your organisation is using is consistently accurate.
Contact us now!
Through our data cleansing services, we help you prevent customer loss and improve target across your campaigns. Contact us now!