CRM software or (Customer Relationship Management) software is one of the most widely used software applications used by businesses to store critical information related to customers or prospective customers it can be used for marketing, sales, customer service, and other areas of business that involve contact with potential or existing customers.
The CRM data stored within the CRM would include information such as contact details as well as other intelligence related to people, organizations & accounts as well as related records orders and communications linked to each of these. The basic data on a customer or potential customer would typically include names, location or addresses, and contact details while more comprehensive records can include a lot more detailed information on the person such as interests, preferences, biography, occupation, age, and so on. With respect to company or account information, the basic data would include the organization's name, location, website, contact information, and more comprehensive records, including details like the number of employees, annual revenues, industry, structure, description of business, and so on. CRM data plays a critical role in marketing, sales, and customer service areas of a business.
As a resource of very valuable information, is often treated as a business asset.
The Perishable Nature Of CRM Data
While data itself is not living or perishable in the true sense, CRM data is known to be perishable in nature. This is because information that is collected on a particular person or organization is accurate or true at the moment in time when it is recorded. This information is prone to become inaccurate with time as what holds true for one moment in time may change in future.
For example: A record entered today may state Mr John Smith works at General Motors Corp as Director, Global Marketing and his phone number is 490-234-2223. Two years later John Smith may be working at Toyota Motors as Vice President, Global Marketing and have a different phone number. So the record entered was accurate at the time but two years later, it is redundant or no longer valid. Hence the 'life' of such a record is only as long as there is no change since the time it was recorded.
What Is CRM Data Cleansing & Management?
Data cleansing & management is the ongoing process of locating inaccurate data, removing inaccurate data, updating records and enhancing the overall quality of the CRM data in order to ensure its usefulness and accuracy is retained. It involves checking the existing data for validity and filtering out what is redundant or replacing the bad records with newly updated records. It's also a maintenance process of ensuring that the CRM data remains as up-to-date as possible.
What Kind Of Issues Affect CRM Data Quality?
There are a number of issues that can effect the quality of CRM data and make them invalid. Issues related to inaccurate data which needs to be cleansed include:
A complete record is one where all the essential data points or fields related to a customer or prospect record is completed with a valid entry. Often, only part of the details for a record are entered or uploaded to the CRM and these records are either no longer useful or their value is reduced as some critical bits of information are missing.
For example: John Smiths name, company and job title are entered in a record but his phone number and postal address are missing. This means the record wont be useful to contact him via phone or send out a direct mail since the information is incomplete.
A duplicate record is repeated or identical records displayed or stored more than once in a CRM. On its own a duplicate record may not be inaccurate or harmful to the quality of the data but it is redundant and having multiple copies of the same record can cause confusion and also result in inaccurate reports or analytics generated from such data. The less duplication of data, the better the quality of the CRM data and also the more accurate the results of reports and analytics.
Expired Or Bad Data:
Expired or bad data refers to data that is no longer accurate and makes a record useless or invalid. This is caused by the perishable aspect of CRM data with time that we mentioned earlier and since information related to people and businesses can change over time, records stored about them can 'go bad'.
For example: A record entered today may state Mr John Smith works at General Motors Corp as Director, Global Marketing and his phone number is 490-234-2223. Two years later John Smith may be working at Toyota Motors as Vice President, Global Marketing and have a different phone number. So the record entered was accurate at the time but two years later, it is redundant or no longer valid.
Non-Standardized or Unformatted Data:
While standards for what is acceptable as a valid data entry is subject to a company's or individuals requirement, often these standards are not adhered to strictly and can result in data not neatly or correctly structured and formatted. This can be an issue especially if the data is to be re-used in an automated process such as mail merging or auto dialer software.
If some of the dates related to a record follow a DD-MM-YY standard and others follow a MM-DD-YYYY standard, the data will appear different and will have to be formatted before its useful. Similarly if some customer names are written in title case "John Smith" while others are written in small letters "john smith" then the data may have to be standardized before being used to print direct mail letters. Also if annual revenue figures for some companies are written in US dollars while others are written in Euros, these will need to be standardized so that users can compare and make sense of the values.
Junk Data / Garbage Data:
Junk or Garbage data refers to records where the fields that are supposed to hold valid data have been filled in with gibberish or garbage values. This data is usually a result of collecting data from various sources (especially online sources) and having them uploaded straight to the CRM without a prior screening for junk values. These records are redundant and serve no real purpose and can affect accuracy of analytics and reports similar to duplicate records other than consuming memory space
For example: If you have the first name entered as "jkg435fdsw" last name entered as "jhfoepwldf" and phone number of a record entered as "000-tyu-0000" this would be identified as a junk record.