How to Segment by Past Purchase Behavior in B2B

Segmentation is one of the core strategies for driving effective business-to-business (B2B) marketing and sales efforts. By grouping customers with similar attributes, needs, or behaviors, businesses can tailor their offerings to each group more effectively, resulting in increased conversion rates, customer loyalty, and overall business growth. In B2B, one powerful way to segment customers is by their past purchase behavior. This method offers unique insights into customer preferences, product demand, and future purchasing tendencies.

In this article, we will explore the importance of segmenting by past purchase behavior in B2B, methods to approach this segmentation, the tools and techniques used to track behavior, and how to apply the insights gained to enhance business strategies.

The Importance of Segmenting by Past Purchase Behavior

In a B2B context, the purchasing decisions are often more complex, involve multiple stakeholders, and tend to be driven by long-term business needs rather than impulse buys. Segmenting by past purchase behavior offers several benefits for B2B companies:

1. Increased Relevance: By analyzing what customers have purchased in the past, businesses can predict future needs with greater accuracy. This allows them to create highly personalized offers that are more likely to resonate with specific customer segments.
2. Customer Retention and Loyalty: Understanding purchase history helps identify which customers are repeat buyers, which products are most popular, and which customers might be at risk of churning. Tailored retention strategies can be deployed to strengthen relationships with high-value customers.
3. Improved Sales Forecasting: Past purchasing data provides valuable insights into buying patterns. Understanding the seasonal, cyclical, or transactional nature of customer purchases enables businesses to make more accurate forecasts, plan inventory, and optimize pricing strategies.
4. Effective Cross-Selling and Upselling: Segmenting by purchase behavior can highlight opportunities for cross-selling and upselling. For example, if a customer has consistently purchased a certain type of software, they might be interested in complementary products or services.
5. Optimized Marketing Campaigns: Targeting customers based on past purchase behavior leads to more effective and efficient marketing campaigns. It helps businesses focus their resources on high-potential segments and avoid wasting effort on less profitable ones.
6. Enhanced Customer Experience: By anticipating customer needs based on their past purchases, businesses can improve the overall customer experience, making customers feel valued and understood, which strengthens brand loyalty.

Methods of Segmenting by Past Purchase Behavior

B2B companies can segment by past purchase behavior using several methods. Each method depends on the nature of the data available, the business model, and the specific objectives of the segmentation strategy.

1. Recency, Frequency, and Monetary (RFM) Analysis

RFM analysis is a widely used technique for segmenting customers based on their past purchasing behavior. The method evaluates three key metrics:

• Recency (R): How recently did the customer make a purchase? More recent purchasers are typically more likely to buy again.
• Frequency (F): How often does the customer make a purchase? Customers who make frequent purchases are often considered more loyal.
• Monetary (M): How much does the customer spend? High-spending customers are typically considered more valuable.

Using RFM analysis, B2B companies can categorize their customers into different segments, such as:

• High-Value Customers: Recent, frequent, and high-spending customers. These are typically the most profitable customers.
• Loyal Customers: Customers who purchase frequently but may not always spend as much as high-value customers.
• At-Risk Customers: Customers who have made a purchase in the past but have not engaged recently or purchased frequently. They may require re-engagement tactics.
• New Customers: Customers who have made their first purchase recently and may require nurturing.

RFM analysis can help businesses identify the best prospects for upselling or cross-selling opportunities and also pinpoint customers who may need special attention to maintain a healthy relationship.

2. Product or Service Category Segmentation

Another common method of segmentation is based on the type of products or services a customer has purchased. This segmentation approach divides customers into groups based on their product preferences, usage patterns, or industry needs. By analyzing purchase history, businesses can create segments like:

• Product Type: Customers who have consistently purchased a particular category of product, such as raw materials, finished goods, or software solutions.
• Usage Level: Segmenting based on how often a customer uses a product. This segmentation can help identify high-volume users versus occasional purchasers.
• Industry: If the business offers a broad range of products or services that cater to different industries, segmenting customers by the sector they belong to can be highly effective.

This segmentation approach allows businesses to tailor product recommendations, communication, and sales strategies to the unique needs of each group.

3. Lifecycle Stage Segmentation

Segmenting by lifecycle stage takes into account where the customer is in their purchasing journey. For instance:

• Prospects: Potential customers who have shown some interest, perhaps through a request for a quote or a demo, but have not made a purchase yet.
• First-Time Buyers: Customers who have made their initial purchase and may need nurturing to encourage repeat purchases.
• Repeat Buyers: Customers who have purchased multiple times, showing a level of trust and loyalty.
• Lapsed Customers: Customers who have not made a purchase in a specified period. Special strategies are needed to re-engage these customers and bring them back into the fold.

Lifecycle segmentation enables businesses to develop targeted marketing strategies for each stage, from awareness-building to post-purchase follow-ups.

4. Purchase Volume Segmentation

Volume-based segmentation is based on how much a customer has bought over a given period. It helps to identify:

• High-Volume Purchasers: Customers who consistently make large orders. These customers may warrant special discounts, loyalty programs, or dedicated account management.
• Low-Volume Purchasers: Customers who buy infrequently or in smaller quantities. These customers may be more price-sensitive, requiring a different set of incentives or messaging.

This segmentation is particularly useful for companies that sell products in bulk or whose sales are significantly influenced by order volume.

5. Seasonal and Cyclical Purchase Behavior

Some B2B purchases are influenced by seasonality or industry cycles. Businesses that operate in industries such as agriculture, construction, or retail may experience seasonal demand spikes. Segmentation by seasonal or cyclical purchasing behavior can help companies plan their marketing efforts and inventory management.

For example, a supplier of HVAC systems might segment customers who tend to make large orders in advance of the summer or winter seasons, whereas a supplier of office supplies might see higher demand at the beginning of the fiscal year.

Tools and Techniques for Tracking Purchase Behavior

To effectively segment by past purchase behavior, B2B companies must have the right tools and processes in place to track and analyze customer behavior. Some essential tools and techniques include:

1. Customer Relationship Management (CRM) Systems

A CRM system is essential for collecting, storing, and analyzing customer data, including past purchase history. CRMs like Salesforce, HubSpot, or Zoho enable businesses to track each customer’s interactions, order history, and even engagement with marketing campaigns. This centralized data allows for more accurate segmentation and personalized communication.

2. Enterprise Resource Planning (ERP) Systems

ERP systems integrate various business functions, including sales, inventory management, finance, and customer service. By analyzing ERP data, companies can gain insights into purchasing patterns, order frequency, product popularity, and other important metrics for segmentation.

3. Data Analytics Platforms

Data analytics tools like Google Analytics, Microsoft Power BI, or Tableau can help businesses analyze customer behavior in more depth. By integrating purchase data with other behavioral data, such as website visits, customer interactions, or social media engagement, companies can develop more nuanced segments.

4. Predictive Analytics

Predictive analytics uses historical data to forecast future trends. By employing machine learning models and algorithms, businesses can predict which customers are most likely to make repeat purchases, identify upsell opportunities, or forecast customer churn.

5. Marketing Automation Tools

Marketing automation platforms such as Marketo, Pardot, or Mailchimp allow businesses to create personalized campaigns based on past purchase behavior. These tools can send targeted emails, offer personalized discounts, or create specific content tailored to each segment’s needs.

How to Apply Past Purchase Behavior Segmentation to Strategy

Once you’ve segmented customers based on past purchase behavior, the next step is to apply these insights to business strategy. Here are several key areas where this segmentation can make a significant impact:

1. Personalized Marketing Campaigns

Use the segmentation to craft targeted marketing messages. For example, high-value customers can receive exclusive offers, while at-risk customers might be targeted with re-engagement campaigns. Personalized content, such as product recommendations based on past purchases, can increase conversion rates.

2. Sales Strategy Development

Sales teams can use purchase behavior data to prioritize leads. For example, customers who frequently make purchases might be more receptive to upselling efforts. Additionally, sales reps can focus their efforts on high-value customers, tailoring their pitch to the specific products or services that the customer has purchased in the past.

3. Customer Service and Support

Customer support teams can use segmentation to offer proactive service. High-value customers or those with complex needs might receive more dedicated support, while lower-volume customers might receive more automated assistance.

4. Product and Pricing Strategy

By understanding purchase volumes and customer preferences, companies can adjust product offerings or pricing strategies to better meet the needs of each segment. For example, businesses could offer volume discounts to high-volume buyers or bundle products for repeat buyers.

5. Inventory and Supply Chain Management

Segmentation based on past purchase behavior can help businesses optimize their inventory and supply chain. For example, if certain segments are likely to make large purchases during specific times of the year, businesses can ensure they have adequate stock levels in advance.

Conclusion

Segmenting B2B customers based on their past purchase behavior is a powerful tool that can enhance marketing efforts, improve sales performance, and increase customer retention. By understanding how customers have interacted with your business in the past, you can predict their future needs and tailor your strategies accordingly. With the right data, tools, and approaches, businesses can leverage segmentation to build more targeted, effective, and profitable relationships with their customers.