What are the different methods used for data cleaning?

What is data cleanup and why is it important?

Having an updated database is an essential requirement for organizations these days as most of the business comes through marketing. An updated database ensures contacts are correct and you can efficiently connect with customers while meeting compliance standards. Now, with daily use by different team members, chances are the data will get corrupted (incorrect or scrambled). It is also possible that some contacts become obsolete over time and need to be replaced.

That’s where data cleaning comes to the rescue because with this process, you can make sure you identify incorrect data and then correct it. Therefore, the data cleaning process aims to maintain a clean (stable and correct data) customer database by recovering inaccurate data (incorrect, outdated or incomplete) and removing the dirty data, creating a single record for individual customers with all their related information. Although manual maintenance is usually followed, the use of data cleaning tools is also increasing today due to the complexity of the database administrator. Before discussing the different methods used for data cleaning, let’s see why data cleaning and maintaining an accurate customer database is so important.

1. In order to comply with the standards of compliance, that is, the Data Protection Act is an important aspect for any organization and therefore data cleaning plays a crucial role here.

2. Regular cleaning of data ensures that there is a minimum of waste of information, ie fewer wrong emails. This automatically lowers shipping costs and helps your business save some resources.

3. Customer data is crucial to any business, so you need to ensure that you maintain a clean database that allows for quick repair of customer information, thereby shortening turnaround time.

4. Having all the data in one place, not only to improve the quality of service, but also to improve the customer experience.

5. Marketing your business to potential customers is the best survival strategy for all businesses, so a clean customer database ensures you have the right customer data to drive better sales goals and good management.

That said, managing a clean customer database is still a difficult task.

Customer information changes regularly and is therefore quickly outdated. In addition, in many companies, customer databases may have multiple information based on different parameters, such as purchase history, prospect list, or email list. This can cause a lot of confusion and confusion as the details of the same customer can appear in different databases with fragments of important information under each parameter.

So when asking about the methods used to clean up data, it is important for you to know that it depends entirely on the different software used by the company such as the type of CRM, marketing automation and other software you use. Regardless of the method you choose, cleaning data manually is usually quite challenging as it will take a lot of time and effort to directly impact the overall productivity of the business. But if you are looking for a specific method, you must first identify the type of data cleanup you want to perform. The method chosen depends entirely on whether you want to add data, remove duplicate entries, standardize data, delete useless contacts, check the email list, and so on. And that is the

Therefore, your life is much easier when you outsource the data cleaning process and seek help from various data cleaning tools available in the market. Data Ladder is such an efficient tool known for its advanced semantic technology that helps maintain the customer database by removing unjustified errors or duplicate entries which can cause confusion. It therefore reduces the time spent on the entire data cleaning process and significantly reduces costs, improving business productivity.

Methods used for data cleaning:

View data

The most important step for data cleaning should always be to fully view the customer databases from scratch. Check for any discrepancies or inaccurate data by analyzing / checking the database using the help statistics and database techniques. The data generated through these methods should then help you identify the location and characteristics of the anomalies so that you can identify the source of the problem.

Use different methods

Database revision should not be limited to the use of statistical or database techniques. The review process should also include methods such as buying data from the outside and then analyzing it against the internal data. But if that isn’t enough and the company faces a challenge with limited staff and time, using an external telemarketing company is a better idea. Here, however, it is important that the company is careful with their brand image and the work standards followed by the external organization (third party).

Data integration

Data cleaning is not just about finding and removing inaccurate data from the customer database, but rather it should be used for the benefit of the company to integrate customer information and added details like, phone numbers, email address or other contacts over and over again.

Reporting of information

Businesses must ensure that there is a robust management system within the organization that can identify and report incorrect data in a timely and effective manner and that it is updated in the database. This can be accomplished through a managed and feedback system intended for emails and any email that returns because it was not the right address. This discrepancy must be reported and the incorrect email address removed from the customer database.

Repeat the same process

It is a constantly progressive world where everything changes so fast that companies have to be able to keep up with the fast pace and so customer data such as the company’s email address, telephone numbers, postal addresses, etc. change very often. Therefore, simply running a one-time data cleaning process would not be the solution, and therefore regularly repeating the same data cleaning process is extremely important. Filtering such inaccurate data and regularly updating the customer database is the only way to ensure that the company has a clean database.

Yes, data cleaning is an important process that is critical and time consuming. Since it takes a lot of time, effort and resources, it is a wise decision to use the reputed data cleaning tools available today. Using the data ladder for de-duplication or managing the customer database along with cleanup is one of the best ways to keep clean data and ensure consistent business growth.

Source by Sohel Ather