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Databases, quality or quantity?

29 July 2019

According to statistics, in just one year almost 15% of the data in a database is obsolete, due to the various changes that take place in companies (retirements, changes of address, closure of the company, etc.). We have talked about database marketing previously and the importance of having a database that is as optimal as possible. While it’s true that it isn’t easy to build and maintain a database, keeping records up to date and well classified (correct segmentation is essential) is the key to making good decisions and sending the right information to each customer, using them for specific purposes. Quality takes precedence over quantity.

Qualitative improvement

Studies indicate that more than 30% of the records in a database are duplicated or inaccurate. Any lack of quality in your database – otherwise known as Dirty Data – means the presence of customer data that potentially can’t be used. It’s clear that implementing strategies to keep your data in the best possible health (perfection is impossible) is vital. You will save time and money as well as building a valuable asset for the company.

The LINK Collect tool allows you to collect relevant data in order to get to know your customers well and to find out their preferences. From that point, there are many considerations to keep the database in good condition. Here are some tips for improving quality:

Fewer fields, but updated: having a large amount of information is enriching, especially for segmenting, but keep in mind that the more fields you have in your database, the harder it will be to keep it up to date.

Constant analysis: periodically reviewing, detecting errors and correcting them is fundamental. For example, you should delete contacts that haven’t opened your communications for a long time.

Investment in data validation: with the right tools you can apply checking practices as data is entered, to confirm its validity.

Crossing information: crossing databases will allow you to enrich them and locate duplications.


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