Today data management is a major topic and a crucial asset for businesses. Indeed, these same data are valuable resources that will allow organizations to make the right decisions about the strategies to be put in place, the products and / or services to develop, the definition of budgets, etc. For all these reasons, the Data Quality is essential in order to take advantage of it at the maximum.

What is Data Quality?

The Data Quality, involves the management and preservation in the reliable and precise data time concerning customers and/or prospects of a company. Indeed, the quality of these data strongly influences planning, the development of commercial and marketing strategies, as well as decision-making.

The six data quality criteria

Precision

It consists of ensuring that all the data are correct and that they perfectly reflect the reality of the results.

Completeness

It is essential that all the essential fields are completed so that the company has a most comprehensive dataset about its customers and prospects.

Validity

This is to determine whether all the data collected correctly follow the defined rules and standards.

News

Available data should be regularly updated to maintain accuracy and quality over time.

Availability

The up-to-date data must be easily accessible to the various employees of the company who need it, at the optimal time.

Consistency

The data on the same individual on one or other basis (s) must not contradict, but be identical in order to create consistency and to join between them.

The danger of the bad data: Why is the Data Quality important?

Measurement and monitoring of data quality are essential to allow the company to make quick and clear decisions about campaigns and allocated budgets.

Yet many organizations do not take the time to really look at the subject in accordance with the standards and criteria relating there. The consequences of bad qualities data can then be disastrous.

Indeed, in case of Erroneous data, redundant or incomplete, the risk is To put in place strategies and/or policies that do not match the preferences of targeted consumers, to make decisions based on inaccurate measures. This can lead to bad decision-making, a big loss of time and money, but also negatively impact the image of the organization as well as its relationships with its customers.

The advantages of the Data Quality

Maintaining high quality data presents different benefits for the company:

  • Righteous and informed decisions, leading to an improvement in results.
  • A better targeting of the audience (customers and prospects).
  • A better fluidity and efficiency in the work between the different teams, because the information they have is consistent and readily available.
  • An optimization of the effectiveness of content and marketing campaigns.
  • A global view of target information (identity, interest and needs), leading to better business / customer relations, and to offer appropriate products and / or services.
  • A step ahead of competition thanks to Best quality data.
  • Increased profitability.

Data quality management

The quality of data management includes several steps:

  1. The establishment of a specific plan of Collection of quality data By determining the type of data needed to ensure that the company reaches its objectives, as well as the methods that will be used to harvest and manage this data. The organization will also clearly define the role of each employee involved in the collection.
  2. The definition of data quality standards to create coherence within the company.
  3. The evaluation of the quality of the data, that is to say, examine them and verify that they respect the standards defined beforehand.
  4. Resolving data quality problems, identify and correct erroneous or incomplete data to ensure accuracy and therefore their quality.
  5. Tracking and data control in order to maintain their coherence and accuracy. It is a process that is done continuously and not punctually.