Hidingbeneath is work that allows these campaigns to be truly effective . One of these activities is rarely mentioned and yet essential: the quality of job title email list customer data. I manage it personally at MailUp. The quality of customer data is still largely underestimated. Many companies perceive it as a “luxury”, too rigorous and meticulous a method to be accepted as continuous and constant. In fact, it has a key impact on the send and its performance.
It's about working at the base and ensuring a solid foundation for your communications. But let's start from the beginning. What is Customer Data Quality Customer data quality refers to a set of activities aimed at ensuring the quality and reliability of recipient data, whether real or potential. As mentioned, this is an underrated activity. In fact, data is generally considered acquired as something that, once acquired, does not require additional job title email list maintenance over time. On the contrary, it is this lack of maintenance that turns out to be the main reason for the ineffectiveness of the campaign . So, in a nutshell, why is customer data quality necessary?
Because email ROI and data quality go hand in hand ROI is the final metric, but it's entirely dependent on the previous metrics: opens, clicks, and conversions. This is why when your database contains a large amount of outdated or irrelevant job title email list information, the metrics never get a boost. As a result, ROI suffers as the last link in the chain. In addition, we know that the quality of customer data allows the most structured companies to increase their turnover job title email list by 70% compared to the average structured companies. Because otherwise any personalization and automation strategy would be thwarted Companies are increasingly beginning to invest in personalization, automation and artificial intelligence technologies. All of these resources can optimize every aspect of communication, with the goal of increasing performance and efficiency. However, if the technologies have to rely on poor quality data, then their outcome will not have the desired take-off. The more specific and targeted you want your marketing campaign to be, the more you need to rely on clean data. It's a fact that poor data quality is the number one obstacle to personalization.