B2B firms now have the capacity to become leaders in customer insight driven analytics.

B2C firms have long led customer insights initiatives, driving innovation in marketing analytics. These innovations have amassed customer insights from daily social media, website and ecommerce interactions to advance marketing, transform customer support and boost sales.

B2B insights have traditionally suffered from a paucity of data, but this is no longer the case, and hasn’t been for some time. With the expansion of B2B data sources and web-scraping platforms, the data are no longer an issue. B2B firms are now able to leverage ample data to become leaders and innovators in customer insights.

In this blog we are going to explore some methods of segmentation that are helping B2B firms better understand their buyers and increase ROI.

Customer Segmentation Using Firmographics

Firmographics help B2B businesses with market segmentation by categorizing firms along relevant variables. Similar to the ways in which B2C companies segment their customers with demographics and psychographics, B2B businesses can better understand their target markets through firmographic segmentation.

As Tim J. Smith notes in The Wiglaf Journal, firmographics define target markets by grouping individual firms into segments along key variables. By aggregating firms, B2B companies can identify firms that are likely to purchase.

There are five general categories of firmographics:

  1. Industry

Industry firmographics are information about a firm’s primary activities. For instance, a point-of-sale platform firm’s primary industry targets may be retail and food service. Whereas a firm dedicated to data security may target a much wider set of industries including banking institutions, public sector organizations, education, engineering and manufacturing. For a final example, a grant database such as Foundation Directory Online might primarily target non-profit and research organizations.

2. Location

Location firmographics refer to firm location. Segmentation can occur at many different levels of analysis: city, county, state, country or continent. Segmentation can also include aggregated regions of these location units. For example: Western Washington state, central Los Angeles or Southeast United States.

Firm location affects a potential buyer’s likelihood to buy in many cases. For B2B firms that sell material goods, construction or installation services, increasing geographical distance often diminishes sale likelihood. Recently, I’ve been looking at camper van conversion companies — for my own recreational purposes. Because there are none particularly close by, I immediately became aware of the difficulty of negotiation and delivery. While I was certainly not a serious buyer, the distance took all wind out of those sails. Distance may take the wind out of would-be sales, too. This is a B2C example, but the principle is the same for B2B.

Digital platforms and providers, as well as companies that produce goods that are easily and inexpensively shipped suffer less from the geographical distance. Though, in some cases, psychological factors such as trust may be affected by distance, and some firms may simply prefer buying local.

Location is an important firmographic to keep in mind when segmenting.

3. Size

Size firmographics allow segmentation on firm size as determined by two variables: number of employees or total revenue.

Your segmentation can follow either of these measures, but results will be quite different depending upon which you choose. For example, some mid-sized companies will show up in your target segments if number of employees is your variable of choice. These same firms may fall out of your target segments if you are grouping on revenue. Some mid-sized firms will have higher than average revenue and some will have lower than average revenue.

For this reason, some marketers choose to use both, leaving size and revenue as distinct firmographic categories. It is also possible to build a composite weighted segment using both variables.

Whatever approach you choose, it is important that you do so with your marketing strategy in mind.

4. Status or Structure

Firm status and structure firmographics denote the legal status of the firm (e.g., sole proprietorship or LLC) and the firm’s relation to other firms (e.g., parent company, subsidiary or independent business).

Your marketing content will vary based upon status and structure within your targeted segments. Treating a 50-person subsidiary as a 50-person independent company will result in content that is not personalized for each account. Subsidiaries may have significant capital from a parent company, for example.

5. Performance

Performance firmographics measure firm change. This can include raw increases and decreases in revenue, employee growth, profits and losses and rates of change in these measures.

Performance firmographics can help your segmentation by determining which firms are likely to need products or services. For example, if a firm experiences high loss rates, they may be looking for new solutions. If it experiences high revenue increases, it may be considering an automation solution they have been putting off.

Putting Firmographics to Work

You now have great data for the most important firmographic variables. Now what? It’s important, and I’m sure this is something you’ve already done, to identify your ideal customer. Look at existing customer data to determine your most and least active accounts.

There are probably reasons that your best accounts are your best accounts (and the same with the lower performing accounts). What are those reasons? Surely there are quirks of buyers, unseen social ties and other data you will never get your hands on, but this is data that is not generalizable and would be pretty useless to know.

With firmographics, you already have the data you need to start putting out that stellar, targeted content.

There are some key benefits of firmographic segmentation including increased sales and ROI. Firmographic segmentation is very effective for top of funnel lead generation.

Predict Behavior Using Propensity Matching

Another approach to segmentation is the propensity approach. There are a number of propensity models and a number of ways to compute them. For illustrative purposes, we will focus on a general outline of propensity matching. To learn more technical detail and about other propensity models, check out this white paper on propensity modeling for business from Data Science Foundation.

Propensity models rely on a fairly simple logic. There are a number of variables (let’s say firm industry, location, size, status and structure and performance to keep continuity with the firmographic example) that contribute to the likelihood that an actor will take a specific action. In our case we will be interested in the propensity a firm has to buy a given product or service.

A propensity model looks at prior behaviors of actors and the covariate values for those actors to assign individual probabilities that they would perform a given action. Let’s say you use data on purchases made within the last quarter (substitute whatever makes sense for your sales cycle).

Because each of these existing behavior values is either 0 or 1, either customers did or didn’t buy, the model needs to assign new probabilities in order to predict future buying propensity of your existing customers and firms that are not yet customers.

Probabilities are assigned by estimating each covariate’s (industry, location, etc.) contribution to an actual purchase. With these probabilities, you can then match accounts based on their covariates to have a good sense of purchase propensity.

Because you have the original data (0s and 1s) and the new probabilities, you can verify the accuracy of your model.

Here’s a visual example with covariates omitted for simplicity’s sake:

We can see that customers who did not buy in the last quarter have a probability of purchase of .55 or less, whereas those that did have a propensity of .72 or greater. Now that you have propensity scoring, you can match lead firms with your existing customers to determine which leads are most likely to purchase.

This can, of course, be made more granular by determining which firms are most likely to buy which products, so that your marketing resources can be deployed in the most effective ways.

Marketing to high propensity firms will increase ROI and sales, including cross- and up-selling opportunities.

If you have additional data from AI assistant chats, sales calls or content engagement history, then you are more likely to have the insights needed to push the right content to the right people.

Beyond the Firm — Buyer Insights Through Role Targeting

Firmographics and propensity matching are wonderful tools for identifying target segments and leads, but so far we have only addressed account marketing at the firm level. Let’s dig a little deeper and see how we can get past the firm to the buyers.

Marketing to a firm as if every buyer and employee is identical is not an effective strategy. Delivering irrelevant information will waste your investment. To remain competitive, it is important to stand out by delivering the right content to the right people.

The good news is that gaining role-specific information is now easier than ever. Web-scraping services have made individual data more accessible. For example, name, role, interests, posts and post interactions can all be scraped from LinkedIn. This data can provide a great foundation for buyer insights but knowing individual role information is just a first step.

It is important to consider the complexity of the average B2B purchase. B2B buying decisions often rely on a team of decision-makers. As Gartner notes, buying groups typically include six to ten decision-makers, who have to consider an ever-expanding array of potential solutions.

Gartner identifies six purchasing jobs in the buying process:

  1. Identifying the problem
  2. Exploring potential solutions
  3. Generating requirements
  4. Selecting a supplier
  5. Validating the service or product
  6. Reaching consensus

The buying process is non-linear, however. This means that buyers will share with others within the organization (e.g., the C-suite) and the development of the purchasing process is guided by other constraints (e.g., budget). Because each stage reoccurs, it is important to continue to provide relevant content throughout the process.

To determine the type of content to provide, first identify needs and pain points consistent with roles typically involved in the buying process. By doing so, you will address any concerns that may arise and address all of the problems that your products or services solve.

To continue to deliver top-notch content, it is helpful to use a content playlist to gain insights from consumption behavior. This data can be added to AI assistant chat data and any call data you have for the account.

Using a Content Playlist to Deliver Relevant Content to Buyers

Using a content playlist can be an effective part of highly personalized B2B marketing campaign. Content playlists provide all of your content for a given product or service up front. With this binge-first approach, buyers can take a deep dive into your product information and you can learn about their problems, needs and their solution interests. We have termed the binge-first approach “flip the drip.”

When buyers begin to interact with your content, your analytical insights become more precise. With this precision, you can deliver highly personalized role-based content. By delivering content that responds in real-time to buyer needs and concerns, you are likely to move them through their buying jobs more quickly.

This is no small feat. Gartner reports that buyers who received information that helped them move through their buying jobs were 2.8 times more likely to experience greater ease of purchase. Informative and relevant information accelerates the B2B buyer’s journey, just as it does for the B2C journey.


B2B marketers are now in a place to compete with the explosion in B2C marketing innovations. With greater access to firm data and individual role-based data, in addition to greater computing power and more widely accessible ML models, B2B marketers are able to leverage analytics to create highly personalized content.

Market segmentation with firmographics, propensity matching, and role identification represent some intelligent segmentation solutions, but not all.

If you want to learn more about content playlists or intelligent AI transformation, check out our recent videos and blogs or visit our website: social27.com.


Which approach would work best for your organization? Let me know why in the comments! I’d love to hear your thoughts.

About Social27

Social27 is an AI powered Automation, Augmentation and Analytics platform. Social27 Playlists empower B2B marketers to deliver a personalized and ‘binge-worthy’ content experience in real-time. Our AI Assistant identifies buyer intent, qualifies leads, and schedules meetings; accelerating sales and revenue growth. Social27 Deal Room automates all the repetitive and time-consuming processes in the deal workflow, keeping all calls, contracts, and compliance in one place. And finally, the Partner Ecosystem Accelerator enables velocity across your ecosystem by enabling a #NoFriction customer journey.