6 objectives pursued by a data quality project

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There are several objectives that are pursued with a good quality of the data. Let's analyze them:

A) Yes, first, the main objective of data quality projects is to help the company interact with the customer in a more efficient way and make the customer experience as pleasant as possible.

At the same time, a parallel goal is to increase customer retention and loyalty. These objectives belong to 100% to the business. The truth is, if the customer perceives a pleasant experience, increase the retention and loyalty ratio.

At the same time, if this is achieved, the counterpart will be to be able to market more and more products. The key market indicators in this regard are ARPU (average revenue per user), AMPU (average margins per user) y CHURN RATE (customer churn rate).

Another clear objective is to convince the entire company of the benefits of starting a data quality project. To that end, a strong sponsor convinced of the results will generate the confidence and the time to achieve it.

Finally, and as the last objective, it is about finding superior data quality software on the market and a company that explains with the experience and knowledge to carry out the project successfully.

To that end, DQ solutions have a predictable and measurable ROI: elimination of anomalies, errors and duplications in customer information. At the same time, provide a unique source of truth, clean and enriched for a single view of customers or products across the organization.

PowerData has accumulated extensive knowledge and experience in best practices in the field of DQ projects.. Certainly, we have the know-how and the knowledge that guarantee the success in the implementation of a CRM or a DWH, what is the quality of the data.

What do you want with good quality data?

  • Set realistic and measurable goals

  • Align business and IT expectations and in this regard, confirm that top management is the sponsor of the project.

  • Understand the cost of poor data quality.

  • Use a continuous improvement methodology

  • Use a phased deployment schedule

  • Measure ROI

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