How To Avoid Data Fraud & Improve Data Quality

Data fraud.

Two words that strike fear into any business that deals with data. Which, let’s face it, applies to 99.99% of businesses these days. Data fraud is a nasty business that involves unscrupulous people deliberately skewing data for personal or professional gain. For example, the same respondent may duplicate a high quantity of survey entries or use a bot to do the job for them. Sadly, this deceptive and malicious practice is becoming more and more common.

Fortunately, if you want to avoid data fraud and maintain data quality, there are a number of precautions you can take. In this article, we’ll describe the dangers of data fraud, and how to establish and maintain high data quality to combat it.

Why is data fraud a big concern for business? 

The main cause for concern is that fraudulent data can easily affect the quality of business decisions and performance analysis. If someone deliberately feeds you bad data or tampers with it, you may incorrectly choose the wrong target group for your next ad campaign. Another example is that data fraud may corrupt the key performance indicators (KPIs) of an email blast.

The stakes may be high, especially if your business is in a highly competitive industry or vertical. For instance, banking or financial services companies may miss out on a lucrative competitive edge if they rely on poor quality data for an ad campaign. Data fraud can also negatively affect a company’s reputation. According to the KPMG Global CEO Outlook, 84% of CEOs are worried about the quality of the data they are using and how it will affect the reputation of their business.

Data quality – the key to beating data fraud

Avoiding the negative effects of data fraud can be achieved by establishing and maintaining high levels of data quality. Data quality refers to data that meets the following criteria:

• Accurate – Recorded correctly and not corrupted by data fraud
• Valid – Gathered or taken from a relevant source
• Complete – Minimal or zero missing data points
• Consistent – A steady flow of accurate, valid, and complete data
• Accessible – Needs to be readily available and on-demand

Businesses should strive to meet a benchmark of high data quality. The ones that manage this will benefit in many ways, including:

• Improved decision making and problem solving – the old software programming rule “garbage in, garbage out” also applies to data quality. Accurate and reliable data will lead to better results.
• Productivity boost – employee time is freed up by eliminating the need to fix errors and track down missing data, allowing them to focus on more meaningful tasks
• Improved marketing – high-quality data allows businesses to focus and target marketing campaigns across different channels
• Meet data compliance – to comply with data regulations (such as GDPR) and avoid fines, businesses must maintain accuracy and security throughout their operations.

How to maintain high levels of data quality

Establishing and maintaining high levels of data quality relies on three main actions:

1. Ensure the use of accurate data sources

Accuracy is the most important factor when it comes to maintaining data quality. If you are relying on third party data, such as buyer intent data, to inform your marketing, then you need to make sure that the data is coming from legitimate research and surveys. Some market research companies have well-established panels that are reimbursed for their time to make sure they get consistent and accurate data samples. It is also important that the panels are made up from a diverse cross-section of society to give fair and unbiased data results.

2. Apply cutting-edge technology

For online market research you need to maintain the integrity of your survey data by using market research security software. The technology used in the newly launched dtect, from Quest’s sister company IRT, helps protect your data collection from professional survey respondents or people with malicious intent. It helps to spot device mining, bot usage, and other types of automated fraud through pattern detection and intelligent analysis.

3. Work with trusted data partners

Most businesses use third party providers for market research and analysis. Before partnering with a market research data provider, you should do some basic vetting and checks. Start by checking out the company history, experience, and any feedback or testimonials from other clients. Next, conduct a thorough review of their methodology and processes to make sure that they prioritize data quality and have the skills and technology available to meet your needs.

4. Assign data quality roles 

To make sure that data quality remains a key focus within your business, it is recommended that you assign data quality responsibilities throughout your company. For instance, you can appoint data stewards in each team, whose job is to monitor the quality, accuracy, and reliability of incoming and outgoing data.

Get high-quality market research insights from a trusted source

Quest works with some of the biggest brands in the business, including Amazon, CBS, Chevron, and Forrester, to provide valuable and accurate market insights. Quest has access to cutting-edge technology and security systems, as well as an engaged and motivated panel of respondents.

Discover how Quest can help you to high-quality data and beat data fraud. Contact us today.