Data accuracy is most important for companies.

April 24, 2020

It’s impossible for businesses to understand or stay in contact with their customers. While it’s easier to collect information about customers in this data-driven age, the question becomes whether this information is accurate, especially after a certain period of time. Data needs to be constantly checked and validated, allowing you to form closer bonds with your customers. Even if you have the most brilliant customer engagement strategy in place, it will fall apart without implementing proper data quality.

tips of data accuracy.

This rate is expected to rise, as mobile commerce and user reliance on smartphones keeps growing. While validating email addresses remains an important part of verifying a user, it cannot be trusted as a single identifier alone. Fake emails are rife and easy to be used for fraud — in comparison with phone numbers, which are unique and difficult to steal. For example, when someone loses a phone, they take proactive action to recover it, or even block access in case it’s lost forever.

why is data accuracy so important?

Well, the answer is obvious. Having access to accurate data ensures that your marketing efforts are not wasted in targeting the wrong demographic. It also makes sure that your resources are not wasted in creating a product that will not be in demand. Artificial intelligence makes sure that the data you are using is accurate. 

Data Quality and Intelligence!

The two need to have a symbiotic relationship. For example, customers are starting to take a keen interest in how their favorite products are being made. You could be left out of the loop if your business does not have access to the right information. 

Companies that incorporate automation should also pay attention to the quality of their applications. They have a certain expectation of how these tools must be produced. Some concerns include:

  • Stolen or duplicate information
  • Incomplete information
  • Corrupted information
  • Inconsistent data

The two need to have a symbiotic relationship. For example, customers are starting to take a keen interest in how their favorite products are being made. You could be left out of the loop if your business does not have access to the right information. 

Companies that incorporate automation should also pay attention to the quality of their applications. They have a certain expectation of how these tools must be produced. Some concerns include:

  • Stolen or duplicate information
  • Incomplete information
  • Corrupted information
  • Inconsistent data

The 5 R’s of Data Quality.

  • Relevance
  • Recency
  • Range
  • Robustness
  • Reliability