5 ways How Businesses can Use Data Cleansing for Maximizing ROI

Inaccuracy in databases is critical enough for costing businesses in the achievement of business goals and the audience where they aim to grow. Most businesses rely on CRM for the growth of their bottom line and nearly all B2B companies suspect their databases to be inaccurate.  

To be confident in the overall health and quality of databases, businesses must consider the incorporation of data cleaning. OURS GLOBAL’s Data Cleansing Services will manually check records, clean and update them on a time-to-time basis irrespective of project volume & complexity. We attend to requirements of diverse industry verticals such as retail, insurance, banking, marketing, transportation, and telecommunication with efficient management and cleansing of customer records for error-free format.

This article aims at acknowledging businesses how can they make their data be dated with ideal data cleaning practices and generate more sales & desired marketing efforts. Before drafting data cleansing practices businesses must have a clear outline of their goals and expectations. They should also have a plan for executing the same. Even though clarifying this can be a daunting task, businesses who haven’t yet thought through their plan can find this article very helpful.  

With the ability for detecting and eliminating errors & inconsistencies, while working with single data sources and combining multiple sources. By implementing data cleansing tools, businesses can eliminate manual inspection and programming efforts and streamline the process. Deploying relations with schema-related data transformations and specific mapping functions is also an effective strategy.

Why keep best practices for Data Cleansing?

• Smooth & effective customer segmentation
• Understanding of customer perspectives
• Compliance with GDPR or CSL guidelines
• Effective customer targeting 
• Minimum budget without wastage
• Maximum ROI

Following are the Ways How Businesses can Use Data Cleansing for Maximizing ROI: 

1. Development of Data Quality Plan

Businesses must set expectations for their data and develop data quality key performance indicators (KPIs). While committing data cleansing procedures, businesses must be well versed in tracking the health of their data and maintaining data hygiene on a time to time basis. They must also be aware of where the most data quality errors occur and identify incorrect data accordingly. This can enable them in understanding the prime reason for the data health problem and help them in developing methodologies for ensuring data health & locate where inaccurate data comes from. 

2. Standardization of Contact Data at the Point of Entry

The failure in maintaining healthy data engine hygiene will lead to unhealthy data persuing into CRM. Before data cleaning procedures, businesses must check important data at the point of entry. Thus ensuring information to be standardized while entering the database, making it easy to identify duplicates. Drafting a standardized operating procedure (SOP) will ensure teams be allowing quality data to CRM at the point of entry. 

3. Validation of Data Accuracy 

Businesses must ensure the validation of data in real-time. With the application of great tools for cleaning data, such as list imports. Businesses must find data hygiene tools for email verification. With the effective application of high-quality data and tools, businesses can seamlessly merge various data sets. Without the appropriate tools, businesses still validate the accuracy of their online data. But it requires a lot of manual work that most marketers are not skilled for. Businesses must have a specialized task force for verifying all data. Triple verifying all data, businesses must go through the web, human, and email verification for net-new contacts or clean up the existing database.  

4. Identification of Duplicates

Duplicate records in CRM are always a challenge for businesses. Wasting business efforts, dupes can also deteriorate campaign spending and general maintenance. Preventing businesses from essential Single Customer View, duplicate also damages the brand reputation, customer experiences, and reporting quality. Businesses must do everything for avoiding dupes by ensuring healthy data entry, validate it, and srub off any duplicates.  

5. Data Appending

Filling in void data with accurate and updated data for filling gaps in the database helps businesses to get rid of incomplete and inaccurate information is termed as Data Appending. Companies may have to save contacts by their first names, last names, and business addresses for contact recording. Title, phone number, annual revenue, their tech stack, and also the contact’s location, also find the same location. As per GDPR or CASL guidelines business location of companies must be attached to company contacts. Complete & comprehensive data for each record in the database is termed as ‘white space’. With appropriate software tools, businesses can clean and compile the data offering comprehensive information for business intelligence and analytics. With accurate and complete data, businesses and their team can make good business decisions.

We believe the readers of this article will be now equipped how to maintain the quality and health of business data. Discussing the best hygiene practices and success factors of data cleaning, businesses can make sure to get healthier data. Businesses must acknowledge the most critical step is to identify dirty data in business databases which will prevent inaccurate or duplicate data. We at OURS GLOBAL’s Data Cleansing Services, assist businesses to implement Data Cleanse best practices ensuring their efforts get the best return. Identifying dirty data sources, our offerings ensure business’s effort not to get wasted and get optimum ROI returns. Businesses who require our Data Cleansing Services, Ping us right away!