How Does Poor Quality Data Impact Business Decisions?

Poor quality data poses significant threats to businesses, profoundly impacting their decision-making process. Inaccurate or incomplete data can lead to misguided strategies, diminished customer relationships, and erroneous forecasts, causing substantial financial losses and obstructing business growth.

Let’s understand the consequences with real-world examples and how can we help you overcome them with tech-led market research solutions.

Results of Poor Data Quality in Research

In today’s data-driven world, businesses heavily rely on accurate and reliable information to make informed decisions and drive sales and marketing strategies. However, poor-quality data can have a detrimental impact on these efforts, leading to lost opportunities, decreased customer satisfaction, and missed revenue targets.

The Impact of Poor-Quality Data on Sales and Marketing.

• Missed Opportunities- Inaccurate or incomplete customer data can lead to missed sales opportunities. According to a recent study, 20% of businesses believe that incorrect data prevents them from reaching their target audience effectively, resulting in missed leads and potential sales.

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• Reduced Customer Satisfaction- Poor data quality can adversely affect customer satisfaction. 91% of consumers are more likely to shop with brands that recognize, remember, and provide relevant offers and recommendations.

As per Komarketing, Approximately 42% of respondents claimed that poor-quality data leads to wasted resources and additional costs, while 39% stated that it has a negative impact on the customer experience. In order to address these potential issues, 97% of organizations have plans to enhance the flexibility and agility of their data management programs within the next 12 months.

• Inefficient Marketing Campaigns- Marketing efforts heavily depend on accurate data to target the right audience and personalize messaging. However, poor data quality undermines these campaigns. A recent report by Gartner estimated that poor data quality is costing businesses an average of $15 million annually in wasted marketing efforts.
• Inaccurate reporting- If your data is inaccurate, your reporting will be inaccurate too. This can make it difficult to track your progress and make informed decisions about your sales and marketing strategies. For example, a study by Gartner found that 50% of businesses believe that poor data quality has led to inaccurate reporting.

Real-World Examples Illustrating the Impact of Poor-Quality Data

• Inaccurate Data- According to an IBM study, poor-quality customer data costs the United States economy around $3.1 trillion per year.
• Data Decay- as per ZoomInfo, about 75 percent of companies experienced degraded performance in sales and marketing.

How to Fix the Poor-Quality Data Issue?

In this online era, companies drive most of the crucial information via online surveys. But it comes with the challenges of survey fraud, leading to inaccurate data. But how can a business ensure that they collect only the right data?

• Adopting the right technology to gather data

Businesses can leverage AI and many automated tools that can help them evaluate customers’ behavior accurately. This will help businesses in making informed decisions based on that information. Businesses can leverage the power of machine learning algorithms to analyze survey data and identify patterns that suggest fraudulent or inadequate responses. By doing so, it can help businesses save time and money by providing accurate and reliable data that can be used to inform critical decisions.

Artificial intelligence is created to help make decisions when the information, factors, and elements involved are too complex for humans to fully understand. In general, AI systems tend to make accurate decisions within their limitations. However, AI often struggles to account for intangible aspects of human decision-making, such as ethical, moral, and other human considerations that influence how we conduct business, live our lives, and shape society as a whole. In such scenarios, AI can be a threat to generate false data.

• Implementing Fraud Detection Techniques

As many companies place bots to attend and complete the surveys to get more rewards for each survey. In the process, the company gathers false information that might not even exist, resulting in false business decisions that can be risky for any business.

So, businesses can leverage platforms with fraud detection techniques that will identify the fraudsters and eliminate them from entering the survey and impacting results. Some popular fraud detection techniques are- fingerprinting, browser caching, GEO IP, mobile verification, open-ended/close-ended questions, red herring questions, address verification, and others.

To know more about how can you keep your research safe, read Safeguard Market Research: The Ultimate Guide to Fraud Detection

• Trusted Survey Panels

Most market research companies do not have access to global respondents who can play a significant role in their research. One way to ensure that you are gathering information from the right people is by integrating survey panels. They have a list of respondents who are prescreened based on some qualifications.

• Data Cleansing and Standardization Techniques

Users often make errors when filling out various forms, particularly when it comes to spelling. For instance, they might type “roda” instead of “road” and not even realize it. However, these mistakes can greatly impact the overall quality of the data set when it is used for analysis.

To prevent such errors, it is advisable to provide users with predetermined choices or a specific list of values for these fields. This helps ensure that users do not make any mistakes. In cases where predefined options are not feasible, normalization tools and techniques can be used to address inconsistencies in the data and enhance its quality.

Get Beyond Data Quality with OnGraph

Researching the market and getting to the core of customers to extract relevant information to curate a thorough sales and marketing strategy, all depends on data you collect. So quality matters a lot.

We believe data quality should be the top priority for a business, as it only leads us to more informed decisions and helps in creating solid campaign strategies. A great market research development software can help you eliminate data challenges.

If you have encountered a scenario where poor-quality data has impacted your business, and you are struggling to find effective solutions, get in touch with our experts to develop next-gen technology-led market research software solutions.

Related Market Research Blog:

Safeguard Market Research: The Ultimate Guide to Fraud Detection
The Fundamentals of Market Research.