Data cleansing is all about correcting or removing incorrect, duplicate, or incomplete data that will be used for analysis. Data cleansing is not only about deleting information to make space for new data but maximizing the data accuracy that exists. With clean data, the analysis will come out correctly and provide accurate information. Data cleansing include fixing spelling errors, standardizing data sets, empty fields, missing code, and identifying duplicate data.
Data consist of everything from the company name, customer names, e-mail, phone numbers, addresses, and everything that qualifies someone as a sales lead and how to get in touch with them.
Data is the component that propels business success – but only if the data is of good, clean quality. Using insufficient data to guide you in business initiatives is like mending a leaky pipe with duct tape; it will not last, and the decision will damage the business in the long run.
Data cleansing aims to create data sets that are the same for everyone in the organization so that everyone has access to the same, correct information that can be used for marketing and sales.
The benefits of having clean data are several; it will increase productivity and provide quality information in decision making:
When the data is clean, it is vital to communicate how cleansing and data entry is done to ensure that the data stays clean. Clean data will help the organization strengthen and develop customer segmentation and send targeted information to the right people.
Determine the quality of data by looking at its’ characteristics:
A UK-based Account Manager at a global manufacturing company was hired to manage and grow sales in England’s southern part. When he logged into the CRM system and searched for his largest account, with more than 100 sites, he discovered that there were no address or contact details on any of the many sites. Surprisingly, he found that there have been logged activities with each site by his predecessor. If the data on the account level is not accurate, imagine how much time the salespeople need to spend on admin time that generates zero value. Insufficient data often lead to bad decisions and more workload.
Clean data helps increase the organization’s productivity since everyone is provided with the right information that can be used to make the right decisions in the daily job. With the correct data, everyone knows where to go and whom to communicate with at the company.
Quality data leads to better decision making. Suppose the data input and analysis are incorrect. In that case, your decisions will be inaccurate as well, and it could hurt the business, which is why data cleansing is of utmost importance.
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