Three Types of B2B Sales Segmentation
Segmenting your customer base according to their shared characteristics will allow you to tailor your sales messaging and approach to every target audience’s priorities and problems. SaaS companies use sales and market segmentation to make data-backed decisions that help boost conversion rate, profitability, and customer retention.
The B2B customer base is commonly segmented based on demographic, firmographic, and behavioral profiles. Let’s look at each segmentation method in detail, and how B2B companies can use them.
I. Demographic Segmentation in B2B SaaS
Demographic data involves information about the decision-makers with whom your sales team will interact along the purchase journey. This includes their name, role, and purchasing power, indicating whether they're the right person for your sales teams to engage with.
Segmentation data is required to create the buyer persona. As the B2B buyer journey is complex, the go-to-market strategy will require multiple personas. You cannot narrow your positioning based solely on demographic data. Supplementing with other common characteristics and data like behavioral and firmographic data in the target market is crucial for successful B2B sales.
A few parameters to consider while looking at demographic data:
- Where is your buyer based?
- The age of your buyer
- The role of your buyer
- If they are a decision-maker?
II. Firmographic Segmentation in B2B Sales
Firmographic segmentation is based on organizational attributes, such as:
- Industry: The nature of the products the company sells
- Location: Geographic segmentation based on country
- Employee count: The number of employees in the organization
- Size: Is the company a startup, medium-sized or large business?
- Legal structure: Whether the company is a sole proprietorship, limited liability company, corporation, or non-profit?
- Performance: Create customer segments based on annual revenue, capital raised, profit/loss, and market share
Companies are different regarding what they need and the problems they’re trying to solve. Market segmentation based on organizational attributes allows you to create the right sales messaging for the right customers based on their requirements, pain points, priorities, goals, and preferences.
Publicly available information lists business names, locations, estimated annual revenues, and other firmographic data. But the data may be outdated or not sufficiently relevant.
- Company X is a C-Corporation software subscription business in San Francisco, with 80 employees and an annual revenue of $10M. The relevant decision-maker is the Chief Technology Officer (CTO).
- Company A is a growing start-up with less than $1M in annual revenue and ten employees. The relevant decision-maker is the Head of Strategy.
III. Behavioral Segmentation in B2B Sales
The focus here is the behaviors of the different types of customers around the buying process. Behavioral segmentation identifies customers' purchase behaviors and patterns, including how they use products, preferred communication channels for engagement, and frequency of engagement.
Understanding how customers buy helps shape the sales process and find opportunities to shorten the sales cycle. However, as customer behavior can change with requirements and time, making room for deviations from the norm is essential to adjust sales messaging and outreach strategy.
- Identify customers that are highly involved in the buying process and try out competing products to seek confirmation before purchasing.
- Group customers based on how actively they engage with your product content. For example, have they downloaded any resources from your website or contact your sales representatives before?
IV. Comparing Demographic, Firmographic, and Behavioral Approaches
A. Focus and Data Sources
B2B demographic data is available publicly on the company’s website, social media profiles, third-party websites, and news articles. Firmographic data is collected from the company’s website, market research and business intelligence websites, and data-as-service providers such as Zoominfo, Apollo, and Clearbit. Behavioral data is usually logged in tools such as Amplitude, Mixpanel, and Segment and clock every action users and accounts take within your product.
B. Use Cases and Targeting Strategies
- Useful in the outbound sales process when your salesperson contacts decision-makers via phone, email, or social selling. You can personalize your sales outreach efforts, ensuring your pitches are tailored to their interests and needs.
- Helpful in improving sales effectiveness. Your sales team can tailor sales messages and conversations to the industry’s unique challenges or the company’s size. For example, suppose you offer a subscription management platform. In that case, you can position it as a solution to the inevitable recurring billing, payment reconciliation, and financial compliance struggles that growing companies face.
- Useful to plan channel-based engagement. If you find that potential customers do not interact as much with your social media ads, pricing page, or the resources on your website, they may be looking to get in touch directly with a sales representative. So, you can frame your marketing messages and calls to action on ads, blog posts, and other brand content to reflect this tendency.
V. Choosing the Right Segmentation Approach
A. Rule-based segmentation
Heuristic-based segmentation is a b2b market segmentation that involves setting certain rules, which when reached, trigger specific GTM touchpoints to your users and accounts to nudge them to conversion, expansion, or custom outcomes you want your users to achieve within your product.
B. AI-based segmentation
Predictive segmentation is an algorithm-based machine learning segmentation strategy that uses all historical customer data to continuously calculate a score for each lead in real time.
Tools like Toplyne, continuously segment and score your leads to surface conversion and expansion pipeline in your CRM for your sales teams to go after. This helps your reps prioritize the right leads and save dozens of hours every sales cycle. The key difference between predictive lead scoring and other manual methods is that it can be automated. Its fast-paced, self-learning algorithm is the basis for predictive segmentation’s speed and accuracy making it ideal for B2B companies. Read more about predictive lead scoring here.
Here’s how companies like Canva and Vercel use AI based segmentation to generate sales pipeline from their self-serve funnel using Toplyne:
- Step 1/7: Create monetization playbooks to surface conversion and expansion opportunities (leads most likely to convert to paying customers, and teams most likely to grow into larger teams)
- Step 2/7: Choose the right leads to target – users (individual users) or accounts (a group of users with an organization).
- Step 3/7: Select the frequency at which you would want leads synced in your GTM apps.
- Step 4/7: Define how many leads you want by either the number of leads or your expected win rate, depending on your sales capacity and GTM strategy.
- Step 5/7: Build custom segments - Build custom segments based on And/Or logic at the deepest level of sub-properties within your product analytics.
- Step 6/7: Validate your GTM strategy - Hold back some users as a control group to test your GTM strategy.
- Step 7/7: Sync your product qualified pipeline into your GTM destinations - CRMs, sales & marketing execution tools, and customer engagement platforms.
Effective B2B sales segmentation helps SaaS companies segment their audience better. This leads to improved sales messaging around customers’ needs, more conversions, and improved retention of existing users.