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Customer data cleansing is the process of identifying, correcting, and removing errors, duplicates, and other inaccuracies in customer data. This process helps to improve the quality, accuracy, and completeness of customer data, which can have a positive impact on various aspects of the business.
By improving data quality, you can gain a better understanding of your customers' preferences, needs, and behaviours. This information can be used to tailor marketing campaigns, improve customer service, and build stronger relationships with customers.
By having accurate and reliable data, you can identify sales opportunities and target sales efforts more effectively. This can lead to increased sales and revenue.
CRM data cleansing helps to eliminate redundant data, which can help reduce storage costs, and eliminate the need for manual data processing, leading to cost savings.
Data cleansing enables you to segment your customer base accurately, helping to target marketing campaigns that resonate with customers and yield better results.
With accurate and reliable data, you can make informed decisions based on insights gleaned from data.
Duplicate detection and merging involves identifying and merging duplicate customer records to ensure that each customer is represented by a single, accurate, and complete record. This is important because duplicate records can lead to confusion and errors, such as sending multiple marketing messages to the same customer.
Data standardisation is another important task in customer data cleansing. It involves converting customer data into a standardised format, such as transforming data from all-caps to lower case or standardizing phone number and address formats. Standardised data is easier to analyze and work with, which can save time and reduce errors.
Data enrichment is the process of adding missing information to customer records, such as job titles, company names, and demographic information. This helps create a more complete customer profile, which can be used to tailor marketing messages and improve customer engagement.
Data validation is the process of verifying the accuracy of customer data. For example, businesses may check that postal addresses are correct and that phone numbers are still in use. This helps ensure that the data is up-to-date and accurate, which can prevent wasted resources and errors.
Finally, data suppression involves removing customer data that is no longer required or that is considered to be of low quality. For example, businesses may remove email addresses that have bounced multiple times or that are no longer in use. This helps keep the data clean and accurate, which can save time and resources.
Before starting the data cleansing process, it’s essential to identify the scope of the project. You should define the data that needs to be cleansed, the objectives of the project, and the timeline for completion.
Data cleansing software can help to make the task of cleansing your CRM data easier and faster.
If you are a Dynamics CRM user you can bulk cleanse, validate, verify and enrich your customer data with easy-to-use power automate data cleansing workflows using DQ for Dynamics Cleanse.
Our all-in-one data management solution – DQ Studio can connect to over 130+ sources and targets for bulk data cleansing in any CRM platform.
Customer data cleansing is a critical process for businesses that want to maintain accurate and high-quality customer data. By performing tasks such as duplicate detection and merging, data standardization, data enrichment, data validation, and data suppression, businesses can improve customer engagement, customer satisfaction, and overall success.