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Marketing Data Quality Video Series

Episode 1: Marketability

sureshot marketing minute

Episode 1: Marketability

There are six primary metrics for measuring data quality and you can check out all six now when you watch our webinar, Marketing Data Answers On Demand.

In today’s marketing minute, we are covering your reach or marketability  In short, your marketability is measured by whether or not you have the data needed to market to contacts and accounts across various channels. What you want to look for when you’re thinking about your data’s reach/marketability is: Do I have values in specific fields that I can leverage to do outreach or outbound marketing to my target audience? To measure your reach, you need to think about data such as email addresses and mobile phone numbers.

For example, if you’re running a multichannel campaign that includes SMS, you will need mobile device IDs. If you’re doing push messaging through a messaging app, then the data you need will include business phone numbers, addresses, social media handles, etc. There are lots of different data elements to consider when using messaging apps. Again, to measure your reach and marketability  (the first metric in measuring data quality), ask yourself: Do I have the fields that I need to reach different contacts and accounts across channels? 

Check out the other videos in this series that cover the six metrics essential to measuring your data quality.

Episode 2: Validation

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Episode 2: Validation 

There are six primary metrics for measuring data quality and you can check out all six now when you watch our webinar, Marketing Data Answers On Demand.

The second metric that is critical to measuring your data quality is validation. Validation measures the quality of the elements of data in your database that can be verified. Data validation is critical to your ability to ensure data is in the proper format, which heightens the chances of campaign success. It is typically performed by a third party service.

One of the most basic data fields that needs to be validated regularly is email addresses. You need to know if the addresses you have are properly formatted. Once they are properly formatted, a third party data service can tell you more about the validity of the email addresses you have, answering questions such as: Is it a spam trap? Can the address receive email? etc. Other fields that you will want to regularly validate include: phone numbers (mobile, office, business) and mailing addresses.

As you strive to improve your data quality, make a habit of inspecting various elements of data to see if they are valid and in the proper format. Having your data validated by a third-party data service will help you ensure that the data you intend to use is comprised of real and usable contact information. After all, you want to equip your sales and marketing teams with phone numbers that they can call and speak to a person, emails that allow their messages to get through, and addresses where contacts can receive the information they need to say yes to your offering.

Check out the other videos in this series that cover the six metrics essential to measuring your data quality.

Episode 3: Standardization

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Episode 3: Standardization 

There are six primary metrics for measuring data quality and you can check out all six now when you watch our webinar, Marketing Data Answers On Demand.

The third metric essential to the measurement of your data quality is standardization. In simple terms, standardization evaluates the level at which your data adheres to a standard set of values. Examples of data sets that benefit from standardization include things like: state, province, country and ZIP codes. If you have 1,000 country values in your country code field, this is a sign that your data is not standardized. 

Standardized data is important to the success of your segmentation strategy. With segmentation, the data that you want to set a standard for will include things like jobs, titles and industry. Questions you will want to ask yourself are: Do I have a standardized set of job titles or industries that I have put into my database that will help me to easily segment that data out as I go to market? Can I use the data I have to personalize campaigns and send dynamic content? Having a standard set of values that your data adheres to dramatically improves the quality of your marketing data. Standardization is a metric that you should track on an ongoing basis.

Check out the other videos in this series that cover the six metrics essential to measuring your data quality.

Episode 4: Total Addressable Market

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Episode 4: Total Addressable Market

There are six primary metrics for measuring data quality and you can check out all six now when you watch our webinar, Marketing Data Answers On Demand.

The fourth metric for measuring data quality is known as the total market or total addressable market (TAM). This metric refers to the available universe of contacts and accounts that match your target audience.  As you consider the breadth of the data that you have, ask yourself: Do I have all the contacts and accounts in my database that actually match the types of audiences I’m going after? In the predictive analytics world, TAM is often referred to as lookalike modeling.

To position your campaigns for maximum success, you need to be able to measure your TAM at the segment level. For example, if you have an enterprise account segment, do you have the total enterprise accounts that you actually could be marketing to, or only a segment of that number? You can leverage third-party data sources to get TAM data. Knowing whether you have 50 or 100 percent of the accounts you should be targeting will make a big difference in your marketing efforts. 

Check out the other videos in this series that cover the six metrics essential to measuring your data quality..

Episode 5: Enrichment

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Episode 5: Enrichment

There are six primary metrics for measuring data quality and you can check out all six now when you watch our webinar, Marketing Data Answers On Demand.

In today’s marketing minute, we are covering data enrichment, which is the addition of data beyond what is captured through traditional methods, like web forms, purchased lists, etc. In short, data enrichment is about accessing data that you can’t get through the aforementioned methods. Some of the information B2B companies might want to enrich their data with include: predictive scoring, buyer intent, account-based marketing elements, etc.

When you think about the quality and completeness of your database, ask yourself, do I have the data I need to:

  • Reach each target audience
  • Create smarter segments
  • Get the best results from marketing campaigns

If the answer for any of the above questions is no, then you need to enrich your data with the missing elements. In the marketing world, results are driven by data and enriching your data is critical to your success.

Check out the other videos in this series that cover the six metrics essential to measuring your data quality.

Episode 6: Completeness

sureshot marketing minute

Episode 6: Completeness

There are six primary metrics for measuring data quality and you can check out all six now when you watch our webinar, Marketing Data Answers On Demand.

In today’s marketing minute, we are covering data completeness. The completeness of your data is measured by the percentage of data elements you have in key fields, such as:

  • Job Titles
  • Industry
  • Annual Revenue
  • State/Province
  • Country
  • Language

The data in these fields is what most B2B marketers use to segment their lists and personalize campaigns. If you are looking to enhance your segmentation strategy and campaign personalization, then you are going to need to know that you have all the data you need in the fields that are important to you.

Data completeness is critical to your ability to create better campaigns that produce better results. You need to be able to measure whether or not you have data completeness across the key fields that are important to you.

Check out the other videos in this series that cover the six metrics essential to measuring your data quality.