B2B Marketing Fit Data

What is B2B Marketing Fit data?

B2B marketing fit data is a set of static data that helps organizations define if a contact or lead is a good fit in its total addressable market. It consists of demographic data of a contact such as job function, level, skills, and responsibilities. It also contains technographic data of a business lead such as technology stack, and firmographic data such as size, revenue, industry, and budget. 

While this data can help determine if a lead fits your product or services, it does not indicate context or timing.

Marketing fit data is commonly used in B2B marketing strategy and decision-making.

Where does the data come from?

B2B Marketing Fit data is a collection of demographic, firmographic, technographic, and other verticalized datasets. This data comes from various data providers and third-party data sources and includes employment data, consumer surveys, customer data, company data, social media data, and identity data, to name a few. 

What types of attributes should I expect when working with B2B marketing fit data?

These data points help with the creation of an Ideal Customer Profile (ICP). Data management of demographic, firmographic, and technographic data together creates the foundation for B2B marketing strategies.

The data attributes you can expect are:

• Demographic data: name, age, gender, email address, telephone number, location, employment history, skills, job department, job function, job level, job title.
• Firmographic data: company name, company location, company budget, company revenue, industry, number of employees, company revenue, vendors, products, product categories.
• Technographic data: technology stack, ownership type (public, private, government), SEC filings (changes, specific classifications, etc.), use of agencies or contract services.

How should I test the quality of the data?

A good way to test the quality of the data is to check the success or conversion rate in campaigns where it is used. The composition of the data makes it flexible and fit for use by sales and marketing teams, who can refine it by permuting attributes to match their campaign needs.

Note that using this data does not give results overnight, and should be tested for the following conditions:

• Check how recent the dataset is and how well it matches your requirements.
• Data should be complete and consistent, without many missing values or records.
• Check how frequently the data is updated.
• Good quality data will include a significant volume of firmographic, company, and intent data.
• Check with the vendor on how the data is collected and if it is compliant with privacy regulations. 

Who uses B2B marketing fit data?

B2B marketing fit data helps define ICP and forms a trifecta with intent and opportunity data. This trifecta is the premise for layering marketing strategies, designing advertising and digital marketing campaigns, and improving sales. These data points are also used to create and run lead generation campaigns, track leads, grow the customer base, identify customer pain points, and improve lead conversions. Marketers need good quality data to optimize their marketing efforts and marketing budgets. 

This data is used widely by B2B companies and their marketing, sales, and analytics teams. 

• B2B marketers and sales teams use B2B marketing fit data to  build marketing plans and run data-driven marketing campaigns that help identify valuable prospects and move them through the buyer’s journey. It also helps them build content marketing strategies and segment their audiences for email marketing campaigns. 
• Data and analytics decision-makers use B2B marketing fit data with intent data and customer data to map trends or patterns in customer behavior.
• Risk and fraud leaders use this data to build better risk models for detecting fraud.  

What are the common challenges when buying this type of data?

This type of data helps identify target audiences and leads that are a good fit. Along with intent data, it forms the base for marketing strategies and campaigns. 

Some of the common challenges and pain points that come up when buying B2B marketing fit data include:

• Source credibility and quality: One of the biggest challenges when buying B2B marketing fit data is assessing its sources. Determining data quality remains difficult and buyers must establish that data vendors are regularly testing for quality and that the sources are trusted.
• Data Integration: Before B2B marketing fit data can be used in any capacity, it must be fully integrated into enterprise analytical and business intelligence systems. 
• Date recency and timeliness: The modern-day customer experience moves quickly – from awareness, to purchase, to post-purchase.  A major challenge for B2B marketers is obtaining the most current and accurate data for their campaigns.  It is important to know how frequently the B2B marketing fit datasets get updated to ensure that by the time you utilize it, it’s not already obsolete. 
• Scale issues: This data may not account for all potential customers or capture all businesses that may be interested. Confirm with your vendor about the scale of their data and their sources.
• No immediate returns: Purchasing B2B marketing fit data does not guarantee immediate returns. It may take some time to arrive at the right solution to avoid false positives and reach the defined goals.
• Legal implications and compliance: B2B marketing fit data includes PII information that should be compliant with different privacy regulations such as GDPR and CCPA. 

What are similar data types?     

B2B marketing data is frequently used with B2B intent data to design effective marketing strategies.  

You can find a variety of examples of B2B and company data in the Explorium Data Catalog.

Sign-up for Explorium’s free-trial to access the data available on the platform.

We also have several resources and white papers for you to learn more. 

What are the most common use cases?

B2B Marketing fit data forms an important part of the intelligence layer in sales and marketing. Some common use cases include: 

• Account Based Marketing for sales teams (ABM): Sometimes called Key Account Marketing, B2B marketing fit data is used to improve marketing and promotional campaigns. Successful sales and marketing organizations recognize that good quality B2B marketing fit data is essential for audience and customer segmentation.
• Lead Nurturing and Scoring: One of the key responsibilities for the sales team is to identify and nurture qualified leads. Lead scoring identifies good leads, and lead nurturing enables sales to pursue the qualified leads that can increase productivity and give better ROI. B2B marketing fit data is combined with intent data for sales campaigns.
• Campaign Strategy and Promotion: Marketing and sales teams create campaign strategies to build brand awareness and augment the process of lead generation, and other marketing goals such as customer engagement and collecting feedback. Using the right data is also essential for marketing automation. 

You can use B2B Marketing fit data for many ML (Machine Learning) use cases such as enhanced recommendation models for eCommerce, and demographic data for lead scoring.  

Explore all the use cases listed on our site and contact us for your specific requirements.

Which industries commonly use this type of data?

It is widely used across industries as it is often used as a base for marketing and sales campaigns. Some of the key industries include retail, consumer goods, financial services, insurance, and eCommerce.     

How can you judge the quality of your vendors?

With growing industry demands, navigating the data vendor landscape can be challenging. Here are a few things to consider for choosing a vendor:

• Customer reviews and testimonials: All vendor websites will have a section on their website that shares detailed reviews. These reviews can discuss various metrics such as quality, integrations, ease of use, or comparison with other products.
• Success stories and case studies: Vendor websites can provide an in-depth view of work done, relationship with the vendor, consistency of quality data, as well as pros and cons.
• Trial run or demo: Many vendors offer a demo run to showcase the quality. The demo can help determine the quality of the data, such as the accuracy of the email addresses or other contact information.