Nobody would dream of going a year without washing their socks, but sometimes companies forget the importance of keeping their data clean. Possibly this is because the move towards digital marketing reduces the financial burden of sending out communications. While companies could see the cost of stamps, the costs of poor-quality data can be less obvious.
Data cleansing – a brief definition
Data cleansing is quite simply the act of ensuring that all information held by any organization is accurate and up-to-date. This is achieved by removing inaccurate and redundant information. Typical examples of this would be: duplicate records; records where the content has been superseded (e.g. where a woman has changed her name after getting married) and records which have passed their legal retention period. While data cleansing is absolutely vital with regards to customer records (which are covered by the Data Protection Act), it is also extremely useful in other areas. For example, having an effective data cleansing policy is a good way to avoid countless copies of outdated documents building up on company servers.
Data cleansing and the Data Protection Act
One of the key points of the Data Protection Act is that any and all personal data held by an organization on an individual must be accurate. While it is highly unlikely that Ms becoming Miss (or even Mr) will generate a severe reprimand, errors of this nature may be a sign of more serious issues, such as mistakes with a person’s date of birth, which could lead to inappropriate material being sent to minors.
On a similar note, the Data Protection Act also requires that information be held only for as long as it is required. Companies without clear policies and processes in place to ensure that data is regularly cleansed, are at great risk of violating this requirement.
Data cleansing and customer management
Companies can only survive, let alone thrive, if they manage their customers effectively. Incorrect customer data can have a direct impact on how the customer views the company. For example, if the same customer receives two copies of the same communication, one addressed to Ann Smith and the other to Anne Smith, then it implicitly sends out a message that the company does not manage its data properly.
Likewise, holding incorrect data on customers makes it more difficult to create and manage effective targeted-marketing campaigns. Whether a campaign is based around gender, age, geographical location or any other sort of segmentation, it can only work if it reaches the people for whom it is intended. Holding incorrect data not only risks communications failing to reach the right segment, but also reaching segments for which they were not intended, either of which will skew the results of any campaign.
Managing data cleansing
Data cleansing should be undertaken at least once a year, no matter what the size of the company. Companies which handle larger volumes of personal data may need to cleanse it more often. The amount of work involved in data cleansing will depend on various factors, most importantly the time since it was last done and the amount of data involved. At its simplest level, smaller companies may be able to achieve the desired result by contacting their customer database and asking customers to confirm their details. Larger companies will either need to create an effective internal process for managing data cleansing, or outsource it to one of the many specialist companies who offer this service.