Data Quality Standards are systems and documented naming conventions. They represent, define, and format common types of data before database integration. Often enforced through standard templates, forms, or software, they are necessary to maintain and increase data quality within CRM systems.
Consequences of not having CRM Data Quality Standards
In a recent study by Econsultancy, they estimated that the bottom line of 88% of companies studied lost up to 12% of annual revenue due to poor data quality. The costs incurred were due to marketing, ad spend, and wasted resources.
The effect of poor quality data goes beyond just revenue. Bad data also affects employee morale and experience. When customer service representatives have inaccurate information, they have a difficult time providing help to frustrated customers.
Some of the biggest losers in the face of bad data quality practices are the sales representatives who go to meetings unarmed, having the wrong information regarding the client, and wasting their time creating proposals for the wrong kind of customers.
Without proper data quality standards, companies run the risk of both losing sales and losing the trust of their employees.
Benefits of Strong CRM Data Quality Standards
Creating a standard for all the data encoded into your CRM system is the first step in maintaining data quality. Through a consistent data entry structure, both the data encoders and the CRM system process data faster, more accurately, and effectively.
Besides saving time and money, it reduces the likelihood of bad data in all its forms – fraudulent, invalid, duplicate, obsolete, and incomplete. Strong data quality standards create reliable reporting and analysis.
Strong Data Quality Standards ensure that your company is compliant with data regulations and prevent miscommunication among internal teams. When employees know that the data given to them is accurate, they can contest unreasonable targets, focus on the high priority clients, and make sure that the right person is credit for their success.
Overall, data quality practices lead to better relationships with your customers. When customers feel heard and remembered, they are more likely to trust and engage with your brand leading to a more meaningful relationship and higher sales.
In conclusion, increasing data quality is not a one time job. It requires consistent enforcement of data quality standards. While this may sound straightforward, there are many reasons why upholding a data quality standard is not easy for every company.
Thankfully, you don’t have to do it alone. In recent times, there have many multiple service providers who can help you uphold data quality standards as painlessly as possible. With their machine learning-enabled voice to CRM technology, Hey DAN is the perfect partner to make sure that your data entry process is always up to standard.
Hey DAN eliminates the hassle of the data entry experience and allows your teams to integrate quality data with just a call. Additionally, Hey DAN can increase your overall data quality by providing you with regular data management, data cleaning, profile updating, and more.