Data has become a crucial element for any business. Its practical use can help an organization make better decisions to achieve its goals and continue to grow in an increasingly competitive market.

However, the latest study, “The State of CRM Data Quality,” carried out by Validity, shows that companies have difficulties having quality data in their CRMs.

According to the report, 75% of those interviewed say that an inappropriate approach driven by poor data has resulted in lost customers, while 44% of those interviewed estimate that their company loses more than 10% of annual revenue to the poor quality of CRM data. 

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Another 64% say they would leave their jobs if additional assignments are not made to have good CRM data.

To have quality data in an organization, it is recommended to follow these steps:

Convince management of the importance of data quality for the business. The first step is ensuring management is aware of the impact of CRM data quality on the organization. 

When the priority is the address to data management, it will be easier to obtain the necessary resources to make the required organizational changes and make the most suitable investment.

Appoint a person responsible for the quality of the CRM data. 

The sheer volume and speed of data that flows through most CRM systems make it a full-time responsibility to manage it. Companies must appoint a full-time gatekeeper of the CRM and its data to reap the full benefits of high-quality CRM data.

Create a CRM data management team: This study has revealed that many companies lack a defined data governance plan. A cross-functional data management team will significantly help the other teams in the organization. 

Although many think CRM is a tool intended primarily for sales teams, its scope, impact, and usefulness go much further. Members of a data management team can be a mix of sales, marketing, operations, and IT professionals.

Automate data management processes: More than half of this study’s interviewees reported using manual methods to identify and correct data quality issues. Attempting to scale a manual process to meet the needs of a growing organization is rarely successful. 

With the support of management, cross-functional teams can take advantage of tools and automation to make maintaining CRM data quality easier.

Look for technological alliances. Often the best way to avoid data corruption is with technology partners.

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