Why is inaccurate data a big issue?

Why is inaccurate data a big issue?

Accurate data also ensures businesses are prepared in the event of unpredictable change. For example, in the emergence of the COVID-19 outbreak, businesses quickly had no choice but to rely on customer data in order to operate their businesses online, and adapt in new directions.

This was no more apparent in the USA’s response and management of COVID-19, which was hindered as a result of health data quality issues. Reports highlight the underappreciated significance of healthcare data accuracy in the event of unprecedented change, where low-quality data made it difficult to cope and adapt.

Though, many organisations took proactive data-driven approaches to adapt their strategy in the wake of the pandemic.

For instance, Marie Curie partnered with REaD Group to incorporate COVID-19 risk data into their data strategy. This helped Marie Curie identify the impact of COVID-19 on the UK population, and manage their marketing strategy and future fundraising activities around this.

Incomplete data

Similar to inaccurate data, incomplete data can also have a negative impact on your business performance.

This data quality issue might not be as severe as having totally inaccurate data, but it is nonetheless another hindrance to your marketing capabilities.

If data is entered manually through form fields, the customer might not input their full details. Furthermore, some customers might opt to only input certain fields of information such as their name and phone number, whereas some might opt to input their name and email address. This results not only in incomplete information, but inconsistent information.

One way that organisations can help control this is by making certain form fields a required entry. That way, data entries will become more consistent and complete.

However, if your incomplete data is too far gone, this fix won’t be enough.

But not to worry. There are several ways to overcome this data quality problem. For instance, through data enhancement services – which is designed to fill in those important missing gaps in your dataset.

Fraudulent data

A less common but very serious data quality issue is fraudulent data. Sometimes, incorrect data is inputted for spam or fraudulent purposes. In no case is this information ever valuable to businesses.

This data quality issue has a serious impact on ROI, since there is no value in this kind of data. Keeping your data clean and preventing customer identity fraud is of the utmost importance.

That’s why it’s useful to regularly check the quality of your data, either through an online data management platform, or professional data cleansing service.

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