Data is one of the most important elements of any business’s performance. But there is such a thing as bad data and studies have shown organisations could lose an average of 15 million a year as a result of this.
With many companies having made large strides in their digital transformation, it’s all the more important that you’re aware of the data you’re collecting and how that data is being used.
But what exactly qualifies as bad data? Let’s discuss...
What is bad data?
Data can be considered bad for a number of reasons. Most commonly, it can be considered as incorrect or misleading information which can lead to missing goals and potentially infringing GDPR.
No organisation is immune to bad data and that’s where implementing a careful review of your data is crucial. Research shows that bad data costs businesses on average 30% (or more) of their revenue, that’s a significant amount of money whether you’re a small business or large corporation. Not only that, but the time employees spend on fixing this bad data prevents them from using their time more efficiently such as nurturing leads.
GIF Source: GIPHY
What are the types of bad data?
The most common types of bad data include:
- Duplicated data
- Outdated data
- Incomplete data
- Inaccurate data
- Incorrect data
The first step to cleansing your database is to understand the most common types of bad data that occur, only then can a plan be implemented to ensure all data is cleansed.
How to fix your organisation's bad data
Image source: Pexels
The data you store directly affects customer experience, that’s why it’s important to conduct regular data audits. It allows your organisation to review minor issues that might have been missed before they become a larger problem.
Auditing helps to improve the quality of your business data and allows you to perform more effective campaigns because you’re marketing to the right people.
In order to understand where your data has come from, it’s essentials to review with various teams within the business. By collaborating with the likes of the sales and marketing teams, you’ll have a better understanding of how they collect, store, use and update relevant data.
Once you’ve collaborated with the relevant teams, you can then begin to segment data into groups and evaluate the quality of the data you’re storing. The key things to look out for during a data audit is the accuracy of information. Make sure all data is up to date, relevant to your current market and there’s no missing information that could affect your ultimate business goals.
Get ahead of the problem!
As a business dealing with data is inevitable, the key takeaway is to continually review the data you’re collecting and segment it into groups. That way, if bad data makes its way into your database, you’ll be more likely to see the issue sooner and put actions in place to fix it.
Not sure where to start? Download our easy-to-follow, 10-point Data Cleanse Checklist for a healthy CRM!