B2B Customer Segmentation: Six Best Practices

B2B customer segmentation

B2B customer segmentation gives you the power to customize your service and even personalize it for individual clients. This yields superior customer satisfaction, translating into higher revenue for your business. This article will give you six best practices for optimizing your B2B customer segmentation.

What Is B2B Customer Segmentation?

B2B customer segmentation is a method of dividing business clients into categories based on selected characteristics. This lets B2B businesses customize their operations for groups of customers with common characteristics or personalize them for individual clients. This type of customization provides customers with better service while yielding better results for B2B teams working in marketing, sales, customer service, and customer success.

B2B customers may be segmented based on categories, including:

  • Demographics: such as location, language, and job title
  • Firmographics: such as company size, industry, and annual revenue
  • Behavioral characteristics: such as prior web visits or purchase history
  • Knowledge level: as defined by how informed the customer is about a given stage of a buying process or product feature
  • Customer needs and wants
  • Ideal profile fit: such as using a scoring system to rate marketing and sales prospects based on an inclination to buy
  • Product usage: which segments customers based on how they are engaging with your product

While customer segmentation predates digital technology, segmentation today relies heavily on digital databases and data analytics. Databases store customer data in organized categories for efficient retrieval and use. Data analytics allows stored information to be scanned for patterns that reflect useful business intelligence. For example, a marketing team might study the social media activity of all website visitors who purchased a specific product to identify the characteristics of visitors who are most likely to buy. A marketing campaign can then be optimized to appeal to social media users fitting these characteristics.

This type of data usage depends on syncing customer data collected from multiple channels and apps. For instance, a sales team might synthesize data from communications with a customer via social media chat, email, texting, phone conversations, and live appointments. Data from multiple sources must be stored in a common database to be retrieved, analyzed, and segmented.

To use segmented data for practical applications, teams may use tools such as key performance indicators (KPIs), dashboards and reports. This makes it easier to see trends in data and plan strategic actions. Actions based on data trends can be automated using a tool such as a customer success platform that triggers workflows based on KPI monitoring.

Why Should You Use B2B Customer Segmentation?

Customer segmentation provides B2B companies with a deeper understanding of their customer base, providing actionable business intelligence supporting more customized and personalized operations. This has numerous applications, including:

  • Market research: Segmentation helps you understand who the different subsets of your market are, what characteristics define them, what actions they engage in, and what needs and benefits motivate them.
  • Research and development: Market research segmentation lets you develop products and services geared toward the needs of specific groups within your customer base.
  • Marketing: Market research segmentation further enables you to develop marketing campaigns targeted at specific groups or even hyper-targeted for individual prospects. Additionally, you can segment campaign performance and split-test the results of different campaigns to optimize your marketing for particular market segments.
  • Sales: Sales teams can use customer segmentation to group prospects and customers based on propensity to buy, potential transaction value and upsell opportunities. This can help teams prioritize high-value opportunities and tailor sales presentations for personalized appeal. Additionally, sales teams can match customer segmentation data with sales representative segmentation data to optimize the pairing of prospects with representatives and scheduling sales meetings.
  • Customer service: Support teams can utilize segmentation in several ways. For example, customers can be grouped based on potential support issues and preemptively sent relevant self-service tools, like tutorial links. Teams can also analyze support data to identify frequently encountered problems, fix bugs and reduce ticket volume.
  • Customer success management: Customer success teams can use segmentation to customize automated and manual support for specific customer groups and individuals. For example, all customers who have been in the onboarding phase for more than a week without completing setup might automatically receive an email providing tips and links to assist with completion. Success teams can also use segmentation to promote subscription renewal, spot upsell opportunities and analyze trends in customer product usage to better understand behavior.

Overall, these benefits promote more customized service and personalized attention, delivering higher customer satisfaction. This enables more repeat business, more upsell opportunities, referrals and higher revenue.

What Are the Objectives of Customer Segmentation?

In a B2B context, a customer segmentation strategy typically aims to achieve several key objectives. These may vary by company, industry, department and product, but common goals include:

  • Developing buyer personas: Segmentation can be used to analyze buyer characteristics and develop ideal buyer personas quickly. Once personas have been developed, segmentation further serves to test and refine them.
  • Improving the targeting of decision-makers: B2B sales depend heavily on the persuasion of critical decision-makers, whose identity is not always apparent. Segmentation can help sales teams better identify decision-makers, understand their buying behaviors and pinpoint the factors that motivate their buying decisions.
  • Differentiating customer journeys: Customer journey maps outline the steps in your clients’ interactions with your brand and the actions you should take at each stage to promote a satisfying experience. Segmentation lets you customize journey maps for different customer segments for more personalized and enjoyable experiences.
  • Comparison of multiple variables: Segmentation can be used to correlate any desired variables to discover patterns that might be overlooked using conventional analysis.

Which objectives are a priority for you will depend on the needs of your business, so you may have other goals in addition to these. Segmentation is a highly flexible tool with many applications.

Six Best Practices for B2B Customer Segmentation

Effective B2B customer segmentation depends on adhering to best practices. Here are six of the most important guidelines to follow:

  1. Collect all the data you need
  2. Keep your data accurate and current
  3. Focus on actionable data
  4. Sync your data with actionable workflows
  5. Fill out the right segmentation buckets
  6. Use segmented data to optimize customer journeys

Let’s break down how to put each of these tactics into practice.

1. Collect All the Data You Need

Good segmentation depends on both the quantity and quality of your data. It’s important to collect sufficient data to have an adequate sample size. This is especially important if you have a small customer base and a limited amount of data. Collecting all the data you can is a good rule of thumb.

At the same time, the quality of data you collect is critical. Ensure you’re collecting data from all relevant sources, including customers, channels, apps and phases of your customer lifecycle. For example, if you’re collecting marketing data, make sure you’re collecting data from all your customer’s devices, platforms and channels.

2. Keep Your Data Accurate and Current

Your data segmentation is only as good as the accuracy of your data. Inaccurate or outdated data can be useless at best and misleading at worst, potentially skewing your results.

Develop procedures to keep your data accurate and up-to-date. For example, you might do automated address correction of client addresses or use an automated credit card updater service.

3. Focus on Actionable Data

While collecting large volumes of data is important, you’re not just collecting data for its own sake. It’s imperative to bear in mind what you’ll be using the data for after you collect it. This will help you decide which data to collect and how to organize it.

For example, let’s say you want to collect data so you can segment customers based on customer health score, a composite metric assembled from multiple KPIs that reflect SaaS customer engagement and satisfaction. You can customize your customer health score to include different KPIs, such as license utilization, product usage and Net Promoter Score. If your purpose is to deploy customer health scores, you’ll need to make sure you’re collecting data on all relevant KPIs.

4. Sync Your Data with Actionable Workflows

Once you’ve got the data you need, to put it into practical deployment, it needs to be integrated into actionable workflows. For example, let’s return to the customer health score example from the previous item. What are you going to do with your customer health score data?

One thing you could do is group customers who are within 60 days of their subscription renewal deadlines based on health scores. You can then pursue segmented responses based on how healthy their accounts are. For customers with low scores displaying churn risk, you might send an automated alert to an account manager to pursue intervening action. For customers with moderate scores, you might send automated notifications to increase engagement, such as tips on using advanced features. You might extend special offers for customers with high scores, such as discounts on upsells customized to fit their usage patterns.

5. Fill Out the Right Segmentation Buckets

For data to be actionable, it’s critical to fill out the right segmentation buckets. These will vary with the purpose of your segmentation strategy. Possible buckets could include:

  • Demographics: client location, language, job title, years of experience, salary, etc.
  • Firmographics: Company size, industry, years in business, annual revenue, etc.
  • Behavioral characteristics: Social media activity, website visitor behavior, purchase history, etc.
  • Knowledge level: How much does the client already know about your product, service, or sales process, and what gaps need to be filled to make a buying decision?
  • Customer needs and wants: What problems does the customer face, what solutions do they need, what benefits are they seeking, etc.?
  • Ideal profile fit: How well does the customer approximate a profile, such as an ideal buyer, as measured by a scoring system?
  • Product usage: How many licenses has your customer utilized, how often do they log in, what features do they use, etc.?

Your segmentation goals will determine which buckets are needed for your purposes. Consider which actions you will put your data toward when deciding which buckets to fill.

6. Use Segmented Data to Optimize Customer Journeys

One of the most powerful ways to integrate your data into actionable workflows is to correlate data from segmentation buckets with your customer’s journey stages. Your customer journey map provides a framework for organizing all the steps in your engagement with your customer, from pre-sales marketing activity to sales decisions to post-sales purchases, product usage, renewals, upsells and referrals. This lets you systematically link data from your marketing, sales, support, and customer success departments into a unified whole covering your entire interaction with your customer. You then can establish KPIs that let you put your data to practical use throughout the phases of your customer’s journey.

Totango’s customer success platform includes out-of-the-box modules for all phases of your customer journey designed to help you leverage data segmentation. KPIs help you automatically monitor collected data, while automated workflows use KPI data to trigger best practices appropriate to a particular segment. For example, customers who have just started using a specific product feature for the first time may receive an automated email with a link for tutorial tips. This use of segmentation can promote outcomes that align with customer goals, ensuring that customers receive high value from the use of your product.

Optimize Your B2B Customer Segmentation to Maximize Client Satisfaction

Best practices for B2B segmentation include collecting all relevant data, keeping data accurate and updated, focusing on actionable data, syncing data between apps, filling out appropriate segmentation buckets and using data to optimize customer journeys. Automating these best practices will help you maximize the value your clients and your company gain from segmentation.

Totango’s platform includes built-in tools to help you sync data from different sources and deploy it for customer journey optimization at each stage of client engagement. Start for free to begin harnessing the power of data segmentation today.

Share Post:

    Get the latest in customer success best practices

    Ready to get started?

    Learn how Totango can help you achieve your customer success goals.