Start by Examining the Health of Your Data

Having poor-quality data is like buying a new car and never changing the oil. That’s what Adam Nenning, Executive VP of Personalization and Marketing Automation at Inte Q, thinks. Other industry experts agree, and the data backs this up — recent Gartner research has found that organizations believe poor data quality is responsible for an average of $15 million per year in losses¹. In fact, IBM estimates that the cost of poor quality data in the United States was $3.1 trillion in 2016 alone².

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What Is Data Quality?

The definition of data quality varies depending on who you ask. According to Profisee, data is of high quality if it is fit for the intended purpose of use and/or correctly represents the real-world construct that it describes.

Data quality takes the following factors into account:

  • Accuracy
  • Completeness
  • Relevancy
  • Validity
  • Timeliness
  • Consistency

Why Is Data Quality Important?

You already understand the value of using data to make decisions for your business. Whatever your industry — retail, financial, healthcare, food and beverage, etc. — your marketing team must have access to the right data at the right time in order to be effective. And yet, ~27% of business leaders aren’t sure how much of their data is accurate

In the Forrester Consulting report, Why Marketers Can’t Ignore Data Quality (PDF), 37% of respondents said poor data quality contributed to wasted marketing spend, 35% said it produced inaccurate targeting, 30% said it lost customers, 29% said it reduced productivity, 28% said it resulted in a poor customer experience, and 24% said it resulted in inaccurate marketing performance results.

Whether your business has customer data from one source or many, the possibility of waste and loss due to “dirty data” has serious implications. We’ve established what data quality is, but data hygiene is the flipside of that coin. TechTarget defines data hygiene as “the collective processes conducted to ensure the cleanliness of data. Data is considered clean if it is relatively error-free.” So, how can your team ensure your data is “clean?” You’ll have to conduct a data quality audit.

37%
of respondents said poor data quality contributed to wasted marketing spend
35%
of respondents said poor data quality produced inaccurate targeting
30%
of respondents said poor data quality lost customers
29%
of respondents said poor data quality reduced productivity
28%
of respondents said poor data quality resulted in a poor customer experience
24%
of respondents said poor data quality resulted in inaccurate marketing performance results

Whether your business has customer data from one source or many, the possibility of waste and loss due to “dirty data” has serious implications. We’ve established what data quality is, but data hygiene is the flipside of that coin. TechTarget defines data hygiene as “the collective processes conducted to ensure the cleanliness of data. Data is considered clean if it is relatively error-free.” So, how can your team ensure your data is “clean?” You’ll have to conduct a data quality audit.

What Is a Data Quality Audit?

A data quality audit is a business rules-based approach that incorporates standard deviation to identify variability in sample test results. Conducting a data audit might seem like quite the undertaking, but it’s simpler than you think. Just ask yourself the questions Capterra coins as the “ABCs of Data Auditing:”:

  • Accuracy: Is your data factually correct? For example, human error is inevitable. Can your team find a way to automate certain tasks to cut down on human error?
  • Breadth: Does your data include your desired scope and represent your population of interest? Is there a segment of your customer base that’s missing from your data collection process?
  • Consistency: Does your data adhere to specific formats and methodologies without deviations? Consistency can simply mean making sure everyone is using the same format for coding or storing information — or it may mean taking a closer look at your methodologies to ensure each data point has been consistent.

How to Sway Stakeholders

Your business may need a data quality audit if you’ve determined you need to:

  • Better understand your customers to improve your business decisions
  • Save money on budget or resources
  • Improve campaign performance
  • Retain existing customers
  • Acquire new customers

But how can you make your case to key stakeholders in your company? Research and advisory company Gartner spells out the steps:

1) Nail down your business priorities

What are your organization’s goals? How will improved data quality contribute to the bottom line? Lay the foundation here before bringing it to the attention of leadership.

2) Determine performance metrics

Once goals and KPIs are established, your team must determine how to measure results. Which metrics will best demonstrate the importance of high-quality data? How will you “prove” the value?

3) Assess your current state of data quality

Once the scope of the business case has been agreed on, initial data profiling can begin. Carry out data profiling early and often. Establish a benchmark at the initial level of data quality, prior to its improvement, to help you objectively demonstrate the causal impact on business value and justify ongoing funding.

4) Describe the target state of data quality

Define your target state for data quality. Describe it in terms of how it can positively impact your business’ KPIs (and bottom line). It’s crucial that your team and your key stakeholders understand the necessity for a sustainable environment for data quality improvement. Without a plan, your data quality will rapidly revert to its previous state.

5) Think about budget and ROI

How much will the data audit cost your business? How much potential return could it provide? How much waste and loss will be eliminated by improving your data quality? Answer these questions and loop in stakeholders.

Inte Q’s Data Quality Audit

At Inte Q, our team of seasoned experts will analyze your data to uncover insights and hidden opportunities to drive strategy and achieve a higher ROI. Along with our Data Health Dashboards, an Inte Q data audit provides a powerful way to understand your customers, better predict their behaviors, and determine how to best serve them.

With our data audit, you’ll be able to:

  • Enhance your 360° customer view and increase your understanding of customer behavior
  • Increase accuracy in analytics and targeting, leading to better insights and higher ROI
  • Review your data to identify opportunities for improvement
  • Increase your advertising reach across direct channels including direct mail, email, and more
  • Increase first-party data onboarding match rates at Google, Facebook, etc.
  • Enhance your customer service experience

Is your team ready to start creating stronger customer connections? Contact us today to get started.