Key Takeaways:
- B2B direct mail data is complex and differs significantly from B2C – Challenges like identity resolution, data quality, and employee turnover require a different approach to data acquisition and management.
- Understanding B2B data types is essential for effective targeting – Firmographic, contact, transactional, technographic, and intent data each play a role in optimizing B2B direct mail campaigns.
- Best practices in B2B data strategy improve accuracy and response rates – Frequent remailing, careful suppression management, and multi-touch attribution are critical to maximizing ROI.
Direct mail B2B data is complex and has its own unique challenges compared to B2C. Many of our clients with experience in B2C data can be taken aback by how planning, analyzing, and purchasing B2B data differs from B2C. Based on years of experience purchasing and analyzing data for numerous clients across industries, we’re sharing this topline guide on B2B data types and differences with B2C data sets.
Introduction
Currently, overarching challenges for B2B data partners include work-from-home and its impact on identity resolution, differentiators in data quality and compliance, the role that generative AI is beginning to play in how insights are obtained and pursued as well as business firmographic update schedules and annual telephone business data verifications.
Some of the main B2B data sources, according to a Forrester report, “The Marketing and Sales Data Provider Landscape, Q4 2023” include: 6sense, Identified, Anteriad, Science, Clearbit, DataAxle, Dunn & Bradstreet, Leadspace and Zoominfo.
But not all of these providers are appropriate for DM, nor will they all allow a mailer to purchase data without long-term commitments.
Types of B2B data
There are five broad categories of B2B data:
- Firmographic data
- Definition: Information about a company’s characteristics, such as size, industry, location, and revenue.
- Use cases: Market segmentation, targeting, lead generation, and competitor analysis.
- Contact data
- Definition: Details about key decision-makers and employees within a company, such as names, roles, email addresses, and phone numbers.
- Use cases: Personalized marketing, sales outreach, and account-based marketing (ABM).
- Technographic data
- Definition: Information on the technologies and software that a company uses.
- Use cases: Identifying tech adoption trends, competitive intelligence, and tailoring technology-specific product offerings.
- Intent data
- Definition: Signals that indicate a company’s interest in a particular product, service, or solution.
- Use cases: Prioritizing sales efforts, personalizing marketing campaigns, and accelerating sales cycles.
- Transactional data
- Definition: History of product and service purchases, subscriptions and more
- Use cases: Targeting, retargeting, and predictive sales models.
Firmographics, contact data, and transactional data are most typically used by B2B marketers for targeting and custom model builds. Intent data is often low volume and some types of signals require immediate attention so are best served by other marketing channels.
B2B vs. B2C data — A comparison guide
Often our Gundir clients will ask about the differences between B2B and B2C data and why the two often require different strategies and solutions.
Please see a comparison below of some key differentiators of B2B compared to B2C data.
Comparing B2B and B2C data
| Topic | B2B | B2C |
| Aggregating and deduping data | Typical: Employee, company/site, site address. B2B can have challenges with high rise buildings and corporate office parks, which necessitates using a reputable data partner. | Typical: Individual, household (last name/address), address only. Aggregating and deduping is less complicated for B2C. |
| Data elements for targeting | B2B data is rich with data elements, such as firmographics, contact details and transactional data, for analysis and modeling at both a contact and a company/site level. This requires a partner with robust data quality, database maintenance and data modeling capability. | B2C can exceed B2B in terms of elements for analysis of an individual prospect. However, some data elements are also limiting in that they are reported only at a household or head of household level. Not all elements are available on every record. And data privacy also limits the use of certain personal information that can be used for targeting. |
| Linkage for group/family marketing | B2B vendors will have various levels of expertise dealing with the complexity of linking employees to company/site and companies to enterprises (which can be useful and lead to overarching account based marketing strategies). | Most B2C vendors are unable to link families to allow for group type marketing (family members not in the same household, for example). Some products can provide this linkage; however, coverage can be limited. |
| Turnover and transition | Changes to employee status are common — company ownership/structure changes, location changes, employee turnover, role transition, etc. These changes can have a significant impact on contact info and an employee’s purchasing role within the same company. Contact data decay is estimated to be much as 70% annually. | Data decay is much less of an issue. Turnover (moving) or transition (changing purchasing influence) is not as significant a challenge with regard to consumer prospects. Note that individual level demographics will move to a new address, with other demographics catching up within an update cycle or two after a move/NCOA has occurred. |
| Mailing frequency | To stay ahead of turnover and transition, best practice in many cases is to continually remail offices, keeping contact-level data as fresh as possible. In our experience, this higher DM contact frequency has been successful from a response and ROI perspective. Additionally, tests can be conducted to mail to add a slug under the contact name addressing the functional title of interest; for instance “HR Manager.” | For B2C, fresh names are often more important than remailings. Remails are best done with strategic messaging or used as a way to increase targeting inventory. In our experience, B2C remails do not typically outperform fresh data. |
| Accuracy | There are more challenges in maintaining accuracy at the individual (employee) level than there are with B2C due to the turnover and transition of employees. | Generally, identifying individuals and the head of household is less challenging than identifying accurate employee information in B2B. Multiple public record sources can provide API based updates to data compilers, catching changes in data at a faster pace than B2B. |
| Suppressions | Suppressions for B2B can be challenging if implemented at the site level. Due to continual employee turnover and transition, it is important to be careful not to oversuppress. | Suppression at the individual, household or address level is relatively straightforward. Usually household suppression will suffice and will rarely lead to over-suppressing across time. |
| Interests and intent | Interest and intent can be difficult to identify in large volumes in B2B. At scale, the most reliable behavioral data is often purchasing history and transactional data, which often requires participating in COOP databases. | Interest and intent can be identified in larger volumes for B2C; however, caution needs to be used to ensure the data is timely (and not decayed survey data or other kinds of sources.) |
| Purchasing drive | Purchases are typically driven by company need and often involve multiple decision makers. Therefore, remains often make sense in order to capture the moment of need. | There are a broader range of buyer motives, such as lifestyle, desire, and wants, in addition to true needs. For many purchases, there is most likely only one decision-maker leading to shorter timeframes and a more transactional approach. |
| Optimization using geography | B2B lends itself well to creating organic business footprints depending upon the product and services being offered. However, challenges in high-rise building data often complicate this strategy. | B2C can also be optimized geographically since like prospects tend to live in similar neighborhoods, but we find it less pronounced than with B2B businesses. |
| Using offers and coupon codes | It is sometimes possible that offers or discounts are not allowed for certain employees or industries. In general, we find that offer codes are ignored (perhaps in lieu of saving time and no perceived personal advantage). This is a challenge for B2B marketers and impacts response attribution. | Offer and coupon redemption can also be ignored by consumers who go straight to a website to buy. But in general, prospects are more likely to use a trackable offer or coupon code in their personal lives than for B2B purchases. |
| Data sources | B2B data is often built using complex integrations of county and other public records, SEC filings, publications, directories and more. This enriches the dataset but it requires a data vendor to implement and maintain data quality. The best data resources do telephone verification sweeps annually across their databases. | B2C data attributes can be considered sensitive and would be more limited due to data privacy regulations. For example, race, ethnicity, children information and even sometimes date of birth will not be available for various use cases. |
| Data COOPs | B2B COOPs will have strict rules with regard to sharing data for marketing efforts and will often require a third party to handle data for direct mail marketing efforts. COOPs rarely release email data for use by other parties due to agreements made with companies that contribute valuable transactional data to the COOP. | B2C COOPs will also have strict rules with regard to sharing data based on agreements with COOP contributors. However, B2C COOPs will sometimes release data for use in pre-populating a CRM or other specific uses if agreements are in place. |
B2B attribution best practices
Although Gundir is focused on direct mail, many of our clients apply the best practices below across channels. Each layer adds complexity to accurately tracking which interactions ultimately influence a business’s purchasing decision:
- Mail unique employees, but measure at the office level when possible
- Integrate data from multiple sources to create a unified customer view
- Employ multi-touch attribution models or even fractionalized attribution models that take into account, where possible, an attempt to determine the lifetime value of customers by channel
- Use advanced visitor identification technologies to track anonymous website visitors, as top-of-the-funnel activity can often help calibrate marketing efforts
We hope you find this guide useful and share it with your colleagues. If you have any questions, we’re here to help you understand and grow your own B2B direct mail program.
Please stop by our contact page for more information on our direct mail services!
Alexa has over 30 years in Direct Marketing experience – B2B, B2C and government. From direct mail catalogs to marketing CRM databases, she has always believed in the power of targeting the right audience in the right way. She partners with clients in data strategy, measurement and stewardship. She is passionate about connecting marketing investments to a positive impact on sales. When she is not digging into a new challenge, she likes listening to live music, practicing her short game, exploring the new marketing technology advancements coming out of the bay area, and visiting her family.
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