Data Quality

Why data quality is important

The word “data” gets thrown around a lot – and for good reason. In this fast-paced, hyperdigital world, more information is available to companies than ever before. Everyone from small team startups to Fortune 500 can benefit from this data, if it is used properly. It can majorly impact your company from informing you on the products you develop to increasing sales numbers of existing products or even assessing risk management.

However, it’s important to note that it doesn’t matter how well your data is used if it is not high quality. In fact, poor quality data can have a long-term negative impact. Research from Gartner found that organizations that fail to resolve their issues with poor data quality lose an estimated $9.7 million every year.1

This doesn’t have to be the case if you are able to properly assess your data quality. First, let’s address what qualifies data as “poor” or “high quality”, and then, we’ll look at the benefits of leveraging data. Finally, we’ll discuss how to get started collecting high quality data to use.

What goes into “data quality”?

Looking at your data quality is critical. Research by the Harvard Business Review found that only 3% of the data quality scores from the study were rated as “acceptable.”2 This means that the problem is more prevalent than many companies realize.

As you start to assess the data your company is collecting, there are several factors that influence whether or not the information is valuable and actionable. You’ll want to start by looking at the accuracy, recency, and whether or not it is compliant and comprehensive.

Accuracy

This refers to how well the data collected reflects the real-world conditions it aims to describe. You’ll want to take into account what sources were used, as well as what processes were employed to verify the data collected.

With accurate data, you are able to make the most informed business decisions. Inaccurate data, on the other hand, can steer your company in the wrong direction. For example, if you’re pulling from an inaccurate data set that tells you your customers are primarily in their mid-20s, but your product is actually resonating more with people in their 40s-50s, you’re at risk for alienating your current customer base with the decisions you make.

Recency

Our world is ever-changing, which means your data is, too. High quality, useful data should be recent. If you need data on the pain points of first time homebuyers in 2022, you don’t want to be pulling from data collected in 2017. Between technological advancements and Covid-19, that process has changed significantly and to most effectively serve that customer base, you need to have recent data to inform your decisions.

Compliance

In response to a data-driven world, people have started to become (rightfully so) concerned about exactly what information is being collected about them and who is using it. As a result, companies need to place a heavy emphasis on compliance when it comes to assessing their data quality. Non-compliant data is considered poor quality because it can end up costing companies monetarily down the road, not to mention the potential for damage to company reputation.

Comprehensive

For data to be high quality, there needs to be no gaps in information and complete coverage to give companies truly actionable data. For example, if the majority of survey respondents skipped multiple questions or left them blank, the data is not actually complete as it does encompass the entirety of the data needed to fulfill a specific purpose.

What high quality data can do for your company

The benefits of using high quality data cannot be overstated as it can influence decisions made regarding marketing, product development, financial decisions, customer experience, and more. To stay competitive in today’s market, companies need to be data-driven, and we know a data-driven approach only works with quality data.

Beyond keeping up with the competition, there are other concrete benefits for companies who only use high quality data:

  1. Making informed decisions to reach business goals

    Leveraging the right data is critical when it comes to achieving your company’s goal whether that is a sales number or a customer satisfaction target. According to PwC’s Global Data and Analytics Survey, data-driven organizations are 3x more likely to report significant improvement to decision making.3

    With accurate and relevant information, businesses are able to be smarter such as creating more accurate customer profiles or making important pricing decisions.

  2. More accurate audience targeting

    There are numerous benefits to taking an audience-first approach, and we know that using high quality data is the first step in this process. With a more holistic, accurate view of your audience, you’re able to create a more personalized and targeted experience. With an accurate view of your audience, you can align your marketing and content strategy to what your target audience is looking for.

  3. Increased profits

    Regardless of your industry, using high quality data can lead to increased profitability. With it you are able to craft effective marketing campaigns which leads to an increase in sales numbers. In fact, a McKinsey report highlighted that companies who prioritize the use of high quality data are 19 times more likely to achieve and maintain a profitable status, compared to companies which don’t use data.4 At the end of the day, collecting high quality data and properly leveraging it can be a game changer for a company.

How to start collecting high quality data

The process of collecting high quality data can be tricky to navigate to ensure the information is accurate, relevant, compliant, and comprehensive. This is why using a third-party data provider like Data Axle can help take stress out of the process while providing your company with the necessary data you need.

Want to learn more about how we can help? Check out our Data Licensing Solutions.

Jennifer Bova
Strategic Account Director, Data Licensing

Jennifer Bova is an experienced sales and account management professional. Jennifer’s expertise guides Data Axle clients to achieve new heights of success through strategic data application. She has a Bachelor’s of Science in Business Administration and Marketing from Doane University and is working towards her MBA from the University of Nebraska at Omaha.

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