Data quality is not just about good intentions. It’s about constant effort – and a helping hand from your data quality software. In this article, we’ll look at a tale of three companies. Let’s call them NoDQ, LowDQ and HighDQ.
NoDQ had no data quality policy in place. Its database was riddled with errors, and many customers were recorded more than once. Some data was muddled; some was incomplete.
NoDQ customers would call and ask that their data was recorded, but telephone handlers made mistakes. The company’s sales department blamed the telephone handlers and made no effort to contact the leads, resulting in lower income and wasted opportunities. Morale was low; profits were lower still.
LowDQ, the second company, recognised that data quality is a pressing issue in business. It had a policy in place that helped staff to recognise poor quality data, and the business was actively involved in a drive to prevent the creation of duplicate or incorrect records.
However, LowDQ had no software that helped the business to cope. Staff were unsupported in their aims to improve the quality of information and simply felt like they were fighting a losing battle. The sales department did their best to improve bad data that came their way.
The final company in the story, HighDQ, had a robust data quality policy backed with data quality software. Aided by automated data cleansing solutions, HighDQ was able to protect its CRM software against the virus of defective data.
The software deployed in HighDQ helped to automatically identify defects in its databases, and it flagged up duplicate information before it was allowed to fester in the CRM application. The sales team, bolstered by confidence in the data, closed more leads and brought in more money – thus securing the future of the business.
A business that is trying very hard to deal with its data problems is doing all the right things. But it cannot fight the battle alone.
LowDQ had the policy, it had diligent staff, and it understood the problem. Yet it never made any true inroads into sorting out its data quality challenges because it did not have the right support.
Only HighDQ had any chance of improving its situation long term, and it was solely due to its data cleansing software.
CRM systems are used widely in business, but they are nothing without good quality data. There are three fundamental components of healthy data in a CRM:
- Accurate information
- Correct format
Without any one of these components, your CRM software will fail to fulfill its purpose.
Better data means better decisions and better business outcomes. Your business cannot reach its true potential without some data quality assistance. By cleaning the database, then keeping the data clean on an ongoing basis, the business can make better decisions at every stage of the customer life cycle.
Video Link - Data Quality in your CRM System.
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