Enough has been said about the importance of high-quality data for businesses. However, enough has not been done to ensure high quality of data for businesses. Though marketers are well aware of the benefits and impact of clean data, they often fail to maintain the quality. This leaves the organization with bad and unstructured data.
With the rise in digitalization of business processes, organizations need to handle huge volumes of data. Moreover, the data keeps accumulating on a daily basis. Lack of proper data management can mean that organizations have to pay a high cost for bad data. Before diving into the cost of bad data, let’s understand what is bad data.
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What is Bad Data?
Bad data resembles the incorrect, inaccurate, or irrelevant data. A variety of factors can lead to bad data – errors in data entry, incorrect data formatting, or data that is out of date. Bad data can have serious consequences on business outcomes. It can lead to inaccurate conclusions and prove to be a roadblock in informed decision making. It is important to carefully check and clean data to ensure that it is accurate and useful for business campaigns.
What Constitutes Bad Data?
B2B data may include information about companies, such as contact information, industry, size, location, and revenue. Bad B2B data can have negative impact on B2B sales and marketing efforts, as it may lead to misdirected or ineffective outreach, or even harm the reputation of the company.
There are several issues that can occur with data to make it ‘bad’ –
- Inaccuracy: Data may be incorrect or contain errors or inaccurate values.
- Incompleteness: Data may be missing important values or fields that are necessary for analysis.
- Poor Formatting: Data may be poorly formatted, making it difficult to understand and analyze.
- Inconsistency: Data may have different values being recorded in different ways, making it difficult to compare or combine data sets
- Irrelevance: Data may be accurate, but not relevant or useful for the specific purpose
What is the Cost of Bad Data?
To quantify the exact loss that businesses face each year due to bad data would be outlandish numbers. According to the International Data Corporation (IDC), the amount of data in the world will rise from 33 ZB in 2019 to 175 ZB by 2025. That is an astronomically high number. As much as 30% of that data will need real-time processing and cleansing to make it suitable for any business use. Though there is no exact formula to calculate the cost of bad data, we, however, can highlight some of the most affected business areas due to bad data and you do the math.
Disengaged Customer Base
93% of modern consumers receive marketing communication that has absolutely no relevance to them. This can lead to unsubscribes or backlisting of the entire domain and consequently lowering your sales. It’s always recommended to use a clean and updated B2B database to deliver personalized and relevant communication to your customer.
Loss of Reputation
The internet remembers. Even before the GDPR, a minor slip-up caused due to bad data was enough to hurt the business reputation. It takes years of consistent efforts to build your brand and reputation. Bad data can hamper that in no time.
Loss of Productivity
Cost of bad data isn’t limited to only your brand reputation and business conversions. It has a spiraling effect on your employee productivity too. Bad data can lead to wasted time and effort, as employees may spend time working with or trying to fix incorrect or irrelevant data. This can reduce productivity and efficiency, leading to lost time and resources.
Decreased Customer Satisfaction
As mentioned before, bad data can lead to misdirected or ineffective outreach campaigns, which can result in frustrated or unhappy customers. This severely impacts the customer trust and they believe you don’t understand their expectations and needs. This increases the probability of losing them to your competitors.
Inaccurate or Flawed Decision-making
Bad data can lead to incorrect or flawed conclusions, which can result in poor business decisions. This can lead to lost opportunities, reduced efficiency, and potentially even financial losses. Most of the business decisions are data-driven and that puts data at the core of every strategy. And a weak core can never yield great results.
Legal and Regulatory Issues
Bad data can also lead to compliance issues and potential legal problems, such as failing to meet regulatory requirements or data privacy laws. With GDPR and CCPA in place, businesses must be extra careful when it comes to handling customer data and contacting them.
Impact of Bad Data
According to a study by IBM, the cost of poor data quality for businesses in the US alone is estimated to be around $3.1 trillion per year. This includes the direct costs of correcting errors and the indirect costs of lost productivity and missed opportunities.
Another survey by Gartner states that bad data can cost an organization nearly $13 million per year. More notably, 60% of businesses are not entirely aware about how much bad data actually costs them as they don’t measure the business impact.
It is important to note that the impact of bad data can vary depending on the size, industry, customers, services, and other factors. The cost of bad data can be much higher for certain industries or types of organizations. The healthcare or financial sectors are more likely to face severe consequences of poor data quality as compared to the other industries.
Why you Must Invest in B2B Data?
Businesses must invest in data to avoid the consequences of poor data quality. The cost of bad data can be difficult to recover from. However, with technology at your disposal, bad data problems such as missing data, data duplication, inaccuracy and reliability can be easily addressed through data cleansing and enrichment services.
According to Sirius Decisions, it will cost businesses just $1 to avoid data duplication, which, if left unattended, could build up to a $100 expense. Additionally, the other reasons to invest in B2B data are –
How to Fix Bad Data Problems
There are several steps businesses can take to manage and avoid the cost of bad data:
Identify the Source of the Bad Data:
It’s important to determine where the bad data is coming from in order to address the root cause of the problem.
Clean and Validate the Data:
Once the source of bad data has been identified, it’s important to clean and validate the data to ensure that it is accurate and up-to-date. This can be done manually or using automated tools.
Implement Data Quality Controls:
To prevent bad data, businesses can implement data quality controls such as data validation rules and data entry guidelines.
Monitor Data Quality Regularly:
Regular monitoring of data quality can help businesses identify and address any issues as they arise.
Educate Employees on Data Quality:
Ensuring that employees are aware of the importance of data quality and the role they play in maintaining it can help reduce the incidence of bad data.
Conclusion
To avoid the high costs of bad data, organizations must create a reliable data ecosystem. It will attract a lot of investment in terms of time, cost and resources. Organizations can simply partner with a reliable B2B data solution provider. They have a deep understanding of data management and analysis, and can bring a level of expertise and experience that may not be readily available in-house.
Partnering with a data solution provider can help businesses access the expertise and resources they need to effectively manage and analyze data, enabling them to make more informed decisions and drive growth. Moreover, they can save the cost of bad data and nullify the business impact of bad data.
