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Measure Your Marketing Data Quality in 8 Steps

Superior data quality is the secret weapon of every marketing program that ever boasted an enviable performance record of slaying competitors. Below, we’ve outlined eight great metrics you need to measure now in order to make sure your data is robust, reliable and ready to rock-n-roll.

Data Validation Is a Measure of Accuracy

  1. Data Validation Rate

The data validation rate measures the percent of accurate data within a dataset. It also assesses the extent to which the data you have collected conforms to your predefined criteria or standards. For instance, you can compare the number of valid email addresses against the total number of email addresses collected. A high data validation rate indicates a higher level of accuracy.

2. Error Rate

The data error rate tracks the percentage of errors or inaccuracies found in your data. Common errors include missing values, incorrect formatting, and duplicate entries. Calculating your data’s error rate allows you to identify and fix data inconsistencies, so that your campaigns will perform better.

Completeness Metrics

3. Data Entry Completeness

This metric evaluates the extent to which data is complete in terms of the required fields. For example, if you collect customer information, you can assess the completion rate of essential fields such as name, email address, and phone number. A high completeness rate ensures that you have the information you need to perform accurate analyses and make better decisions.

4. Missing Data Rate

The missing data rate measures the percent of missing or incomplete data points within a dataset. By identifying areas with high missing data rates, you can take appropriate steps to collect the missing information by acquiring reputable second- and third-party data. It is crucial to have a low missing data rate to ensure reliable insights and avoid biased analyses.

Consistency Metrics

5. Duplicate Records

Duplicate records are the evil echo of poor data quality. This metric reveals the number or percentage of duplicate entries you have within a dataset. The problem with duplicate records is they have the power to skew results, lead to inaccurate insights, and cost you big-time with regards to campaign spends. By identifying and removing duplicate records, you can enhance your data consistency and reliability and save your budget for bigger and better things.

6. Standardization Rate

Standardizing data elements, such as names, addresses, and product descriptions, enhances your data consistency. The standardization rate measures the percentage of data that has been standardized according to predefined rules or formats. By increasing the standardization rate, you can improve the reliability of your marketing data.

Timeliness Metrics

7. Data Latency

Data latency refers to the time delay between data generation and data availability for analysis. It is crucial to monitor data latency to ensure that marketing decisions are based on the most up-to-date information. By reducing data latency, you can respond to market changes more effectively and gain a competitive edge.

8. Data Freshness

Data freshness assesses how recently the collected data reflects the current state of your market. This metric is particularly relevant for time-sensitive marketing campaigns or industries that experience rapid changes. Timely data updates and regular data refreshes help maintain data freshness and enable accurate decision-making.

I’ve Got My Measurements, Now What?

It’s one thing to be armed with information, but it’s quite another to know what to do with it. Having a rock-solid marketing analytics strategy in place is essential to your marketing department’s ability to make a measurable contribution to the overall performance and growth of your company. Of course, the key word in the previous sentence is “measurable.” As you monitor various metrics, you should be able to see patterns, anomalies and results that lead to insights that inform your actions.

Develop a Marketing Data Analytics Strategy

A few of the benefits a marketing data analytics strategy provides include: 

A. Understanding Customer Behavior

  • Know how customers are searching for your products/services
  • Map customer journeys and plan accordingly
  • Reduce your cost per lead

B. Optimizing Marketing Efforts

  • Adjust ad campaigns to produce better results
  • Know which channels and devices are bringing in the most leads
  • Enhance the content of blogs, landing, and product pages, etc.

C. Planning for the Future

  • Understand the ROI of various marketing efforts
  • Enable sales to close more business
  • Invest your budget where the ROI is greatest

Sureshot’s Three-Step Data Prep

Before you invest time developing and pursuing a marketing analytics strategy, you need to prepare both your data and the various tools, apps, systems and platforms within your marketing technology stack. After all, you can’t make data-driven decisions based on disparate data and disconnected tools. To ensure your decisions are based on the best-possible data we recommend taking three critical steps:

Step One: Locate and Integrate All Data Sources Throughout Your Company

It’s vitally important to your ability to make informed decisions to integrate both major and minor databases, from marketing automation platforms (MAPs) and customer relationship management systems (CRMs), to content management systems (CMSs), analytics tools and more. If you’ve got data that’s buried inside any of the tools in your martech stack, consider adding a data management tool that centralizes your view and access to all of the data contained within your stack.

Step Two: Get Your Data Results-Driving Ready

According to Experian, the average business loses up to 25 percent of revenue thanks to inaccurate, incomplete or inconsistent data (aka dirty data). These days, there’s no excuse for having dirty data when you can keep your data perpetually clean, complete, standardized and enriched by adding a data dashboard that monitors and maintains data quality. Beyond driving better results, using clean data will also save your budget and enhance your customers’ experience, loyalty and lifetime value.

Step Three: Connect Your Content Sources and Channels to Data Sources

The best way to track the performance of your marketing efforts is to measure campaign performance across all channels. When you connect your data and content to the various channels you use, it empowers you to scale personalized campaigns. which perform much better than non-personalized campaigns. In fact, 86 percent of customers are more likely to make a purchase when companies provide personalized experiences.

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 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!