Sureshot’s 6-Step Guide to Performing a Marketing Data Quality Audit

The benefits of conducting a marketing data quality audit are manifold, from optimizing your marketing strategies and identifying gaps in your data processes (tools, integrations, shareability, etc.), to ensuring the accuracy and reliability of your data, which has a high impact on campaign performance, sales won, etc. With so many benefits, you would think data quality audits would be a regular practice of most B2B’s, and yet conducting a marketing data quality audit is the kind of task we marketers love to put off. We tend to see audits as something better suited for mathletes or those with an IQ of 140+ and an EQ score somewhere south of 85. Fortunately, it’s much easier to execute than you might have imagined, especially when you consider that we’ve got each step of the process you need to take outlined for you—nice. So, let’s get your audit party started and prime your marketing data to produce some serious results.

Step 1: State the Purpose of Your Marketing Data Audit.

Ask any goal-setting guru what the difference is between rockstars and wannabees and they’ll tell you all about the importance of defining what you want from life and then writing it down. Our next steps somehow become much clearer when we write down precisely what we hope to achieve. In our case, we’re going to define what we want from our marketing data audit. A few common reasons to conduct an audit include:

• I need to enhance the accuracy of our data and measurably boost campaign performance.
  30% per year is the average rate of data decay for most B2Bs. (Source: SiriusDecisions)
• I need to identify gaps in our data processes and fix our email deliverability rate.
  80% is the average email deliverability rate across all industries. (Source: DMA)

• I need to ensure our data complies with GDPR.
  63% of companies say ensuring data quality and complying with data regulations is their top data management challenge. (Source: DQM GRC)

• I need to have more accurate customer segmentation, targeting, and personalization.
  66% of companies say their customer and prospect data is unreliable. (Source: Demand Metric)

Whatever your reason for taking stock of the current state of your data, if you make it a priority to state your goals from the get-go, it will help you stay on-track throughout your data audit. Heck, you may even finish your audit in record time.

Step 2: Define the Scope and Measurements of Your Audit.

Keeping your objectives in mind, it’s time to decide which marketing tools, data sources, channels and campaigns you want to assess. The more narrow (focused) your scope, the more targeted and efficient your audit will be. Next, you need to identify the key metrics and data points that match the marketing objectives you established in Step 1. The metrics and Key Performance Indicators (KPIs) you choose will vary based on your specific goals and the marketing data sources you’re auditing. For example, if you’re assessing the quality of your email marketing data, key data points might include open rates, click-through rates, and conversion rates. Create a checklist of these metrics to ensure you cover each one during the audit.

Step 3: Assess Your Data Tools, Sources and Collection Methods.

Now, you are ready to evaluate the data collection methods employed across your marketing technology ecosystem. You will want to note for each tool that you audit how data is collected, stored, and processed. Next, you need to review all tools, software, and platforms used for data collection and ensure your martech is properly configured and integrated. Look out for any potential issues that might compromise data accuracy, such as duplicate entries, missing data points, competing data standards, etc. Be sure you note how data is entering each tool, how often it is cleaned and updated, and what checks and balances are in place to maintain its integrity as it travels throughout your martech ecosystem.

Step 4: Verify the Accuracy, Completeness and Relevance of Your Marketing Data.

One of the primary goals most marketers say is their reason for conducting a data quality audit is to ensure data accuracy and completeness. If this dynamic duo is at the top of your to-do list, then you will want to start your verification process by analyzing a small sample set of your data and measuring its accuracy against reliable sources, such as third-party data providers. While measuring your sample set, be sure to check for any inconsistencies, anomalies, or outliers as these typically serve as red flags for data quality issues. Make sure you measure the completeness of your data, which you can do by noting whether or not all necessary data points you want for campaigns and decision-making are captured and recorded. Lastly, review your data points and metrics to determine if they provide actionable insights and remove any irrelevant data that may add noise and hinder future analyses.

Step 5: Assess the Current State of Your Data’s Security and Compliance.

Given that the news seems to report a new data breach every week at some unfortunate company that is then forced to pay fines to hundreds of thousands of customers, it’s easy to see why data security and compliance is almost always listed as a top priority in any data quality audit. To ensure you aren’t the next cautionary tale on the six o’clock news, you will want to evaluate the measures you have in place to protect your data from unauthorized access or breaches. You may need to refresh your knowledge of data protection regulations, such as GDPR or CCPA, to make certain that the compliance measures you have in place are solid. In the event you identify any gaps in security or compliance, drop everything else on your to-do list and take immediate action to address them.

Step 6: Report Findings and Implement Improvements.

As you progress through your marketing data audit, documenting findings and outlining possible solutions to issues, make it easy for fellow executives to get on board with your mission for higher quality data by creating a detailed report for them that highlights:

• Issues Identified – Share which data sources and processes are causing problems, i.e. outdated data collection forms, misconfiguration of tools, training for new staff members on data tools.
• Improvements You Recommend – List actionable steps that can be taken to address all data quality issues and enhance data that is used enterprise-wide.
• Impact of Data Quality – Outline opportunities available and ones that have been missed due to underperforming data quality.

Be sure to collaborate with relevant teams and departments across your company (sales, customer service, etc.) to address data quality issues and implement changes. Data quality is an ongoing process, so it’s essential to conduct regular audits in order to maintain the kind of data that produces the results you want. Finally, put a plan in place to continuously monitor your data quality and ensure its quality is maintained. Consider automating ongoing improvements to your data quality to ensure your campaigns are perpetually powered by data that is clean, complete, standardized and enriched.

Bonus Step: Add a Mathlete to Your Team

Measuring data quality is not a one and done deal, but more of a lifetime commitment with daily checks and balances to ensure health and longevity. If the thought of audits, metrics and analytics leaves you sweating like a math flunkie in a calculus class, Sureshot can help. We love helping folks, like you, get a grip on marketing data and showing it who’s boss!