5 types of customer data B2B companies need for personalized experiences

Highlights

You’ll learn about key customer data types for B2B personalization

• Behavioral: Tracks online activities to understand customer needs and interests
• Transactional: Captures purchase patterns for tailored content and offers
• Technographic: Identifies tech tools B2B customers use
• Engagement: Measures content interactions across all platforms
• Intent: Reveals buying readiness through customer actions

Enhance B2B sales outcomes by integrating these insights through a real-time customer data platform.

According to research, 72% of B2B companies collect customer data for personalized customer experiences. This data enables B2B brands to understand and segment their customers for proactive marketing.

Aside from that, the use of customer data allows businesses to optimize the buyer’s journey and gain a competitive edge. So, what types of data should businesses prioritize, and what is that one tool to bring it together? 

Types of customer data to capture

Customer information comes in different forms. Hence, B2B companies must understand what kind of data to collect and utilize to tailor customer experiences. Here are the main types of data that they should focus on.

Behavioral data

Behavioral data consists of online interactions across platforms. It shows buyers' intent and preferred products and services. Sales teams can use this information to market suitable products to decision-makers. When collecting behavioral data, capture:

• Website interactions: Track the specific web pages your customers view and their click paths—this could give you a hint of their interests. Click paths can also reveal web drop-offs, helping you to understand bounce rates.
• Content engagement: Monitor how far visitors scroll, what they download, and activities they perform. These show the buyer's decision stage, allowing you to segment, score leads, and personalize funnels. 
• Purchase patterns: Note the products customers like, how much and how often they place orders. These details make it easy to predict demand and boost ABM and proactive outreach.

You can use these data points to:

• Optimize customer journeys: By mapping customers' paths through various touchpoints, you can identify pain points and experience gaps and design tailored solutions to address them.
• Personalize dynamic web content: Businesses can use behavioral data to retarget users who previously engaged with the brand. You can also use this data to arrange menu items and enhance CTAs to be more engaging.
• Predict buyer intent: Tracking behaviors enables sales teams to identify high-quality leads and target follow-ups.

Transactional data

Transactional data includes purchases, payment cycles, subscriptions, and financial information. Key data points to capture include:

• Purchase history: Track AOV, product preferences, and demand trends, enabling you to suggest products that match or complement their previous orders.
• Contract terms: Monitoring service levels, price agreements, and renewal dates help B2B companies to know when to send reminders for renewals and upgrades.
• Recurring orders: Knowing when buyers place new orders enables accurate demand forecasting. This helps B2Bs to send reorder reminders at the right time and prepare payment documents.

Here are use cases of transactional data:

• Personalize upselling: B2B companies can analyze past purchases to suggest upgrades and complementary products to their buyers.
• Build customer retention strategies: Lower orders or late payments are signs of low engagement. B2B businesses can craft offers to re-engage these customers when they notice this. 

Technographic data

Technographic data refers to the tools and technologies a customer uses. Understanding this helps B2Bs identify customers' tech needs and offer proper solutions. Key details to capture include:

• Software stack: Knowing the tools a client uses makes it easier to find alternatives and add-ons that improve workflow.
• Integration capabilities: B2Bs can identify tools that integrate poorly and offer replacements.
• Trends in technology adoption: Learn how your customers use new technologies. Consider the adoption rate, speed, and usage patterns to determine when to send targeted offers.

These data points are used to create solutions for distinct IT environments. For example, a B2B SaaS can pitch a data analytics tool that integrates with a customer's software, enabling fast adoption and improved performance. 

Engagement data

Engagement data tracks how customers interact with your content on different platforms. This shows which content buyers enjoy, enabling you to send them ads recommending suitable products. Indicators to capture under engagement data include:

• Email open rates: Data such as email open rates helps identify active buyer accounts, allowing you to tailor follow-up.
• Webinar attendance: Participation data helps B2B companies to identify services that potential customers like, enabling you to send valuable offers.
• Social media interaction: Social media metrics help you discover the type of content that attracts buyers.

Tracking these metrics enables you to:

• Refine targeted messaging: Use engagement levels to create buyer groups and send messages that address issues at different stages. 
• Improve conversion rates: Send buyers messages that promote products that they like. This encourages leads to buy.

Intent data

Intent data shows which customers are researching products to gather more information and which customers are ready to make a purchase. To discover intent, B2B teams should track:

• Content downloads: When leads visit your website, check which resources they download to know their needs. This way, you can position your product as the ideal solution.
• Search queries: Search terms reveal customers' needs, enabling you to promote matching content.
• Competitor research: Study the products that buyers compare to yours and check for gaps in your offering. Refine your USP so your product meets buyers' needs.

B2B organizations use intent data to identify and nurture leads. For example, a supplier can offer a personalized demo or service package when a buyer downloads a product guide. After capturing data, you need the right tool to make sense of it, and this is where a customer data platform comes into play.

The role of a customer data platform (CDP)

A CDP is a centralized software that collects, organizes, and unifies customer data from multiple sources to create clear, unified profiles. It displays real-time data that B2B teams can access and use.

According to research, 79% of companies that use CDP generate more revenue within 12 months. CDPs support personalization initiatives and enhance sales outreach by unifying data and providing holistic customer profiles. It also links decision-makers' data to their companies for account-based marketing (ABM).

How CDPs unify customer data from multiple sources 

CDPs collect data from various sources like analytics platforms, ERPs, and websites. They then standardize and clean the data to improve its structure. Next, the CDP uses identity resolution to match data points to the correct customers. After structuring data, the CDP merges it to form a profile that informs decisions.

Key features of a B2B-focused CDP

A CDP designed for B2B companies should have the below features:

• Multi-source data (first, second, and third-party) collection.
• Real-time data processing and profile updates.
• Account-based data structuring.
• Customizable dashboards to visualize data.
• Identity resolution, customer segmentation, and lead scoring.
• GDPR compliance and secure integration.

Integrating your CDP with your current marketing tech stack

Opt for CDPs that support APIs and provide pre-built connectors to integrate with your existing marketing tech stack. That way, you do not have to reconfigure your system or incur technical debt.

Contentstack’s real-time CDP allows you to build a real-time pipeline from all data sources. It is also API driven, enabling you to establish data flows between systems.

After integration, test data synchronization in small batches before you fully deploy. Set up automated governance to maintain data quality and deploy unified reporting dashboards to track the performance of the integrated systems.

Turning data into personalized experiences

A McKinsey study shows that personalization can boost revenue by 40%. To unlock this value, B2Bs must utilize data to create services, offers, and messages that cater to buyers' needs and preferences. Here are ways to use data for personalization:

Apply data segmentation strategies 

Use firmographics, customer behaviors, or funnel stages to segment customers and target interactions by industry, actions, or buying stage. This ensures you can target each segment with content tailored to them.

Use role-based content delivery 

Map stakeholders and send content aligned with their responsibilities to increase engagement. 

Use a customer journey-based approach

Map customer touchpoints to identify their thought processes, needs, and experience gaps. Then, use the data to deliver content that matches their progress and addresses their needs from awareness to retention. 

Personalize across channels 

Align content across platforms to build a consistent customer experience. There are several ways to do that. For instance, you can personalize web interactions using customized product pages or triggers, such as pop-ups or chat prompts, based on behaviors like scroll depth and pages visited.

In email interactions, you can recommend content based on customer activities on other channels or use triggers in email campaign sequences. You can also activate segmented campaigns.

In sales interactions, you can use contextual data to facilitate outreach and tailor invitations and follow-ups. You can also deliver dynamic sales content, such as demo scripts that highlight features most relevant to specific customer or account needs.

Personalize interactions in real-time 

This process enables you to deploy real-time data to fine-tune customer experiences on the go.

In essence, you respond to actions instantly with dynamic content, customized content, and landing pages, as well as optimized recommendations and live support to address customer service issues. These real-time engagements lead to seamless customer journeys.

Effective personalization begins with a strong customer data strategy. Let’s look at strategies to build one.

Implementing a B2B customer data strategy

A strong customer data strategy transforms data into actionable insights, improving personalization and engagement. It outlines methods for collecting, organizing, and governing data.

Data collection

It is best for B2B companies to collect first-party data using systems like:

• Website trackers
• Lead capture and survey forms
• CDPs for omnichannel data unification

While the right tools are essential, you must use them to segment customers and for identity resolution, enabling you to improve customer experiences and drive growth. 

Data governance and privacy

B2B companies must obtain informed consent before they collect customer data. This fulfills ethical standards and also complies with the GDPR and other data privacy laws. They must also limit data collection, maintain transparency, and train teams on clear data policies. 

Aside from that, they must also set up robust enterprise security measures. For instance, Contentstack offers multiple enterprise security protocols, like HTTPS, a virtual private cloud, data encryption, and SOC 2 Type II, among others. Data transparency and security build trust and enable compliant personalized experiences. 

Personalization tactics

To complete the implementation process, B2B companies must employ relevant tactics to enhance customer engagement and drive conversions. Role-based personalization targets stakeholders by tailoring content and suggestions to their needs.

B2B companies in e-commerce can use dynamic pricing and reorder prompts to personalize sales offers. For example, a wholesaler can use special discounts to reward loyal customers and set tiered price plans for new customers. They can also automate restock reminders with purchase history. These approaches increase satisfaction and retention.

Case studies

Industry Dive

Industry Dive sought to gain deeper insights about its readers beyond Google Analytics.

They chose Contentstack's real-time CDP to analyze each customer’s journey and to get deeper user insights. This allowed them to collect the right data, segment readers, and personalize content. The changes increased conversions and click-through by more than 40% for specific campaigns.

"We want people to see the value we get from Contentstack's real-time CDP because, for us, it's a strategic investment and a differentiator." Robin Re said.

Read more to see how Contentstack's real-time CDP powers Industry Dive's data collection and personalization efforts.

Land O'Lakes

Land O’Lakes Purina brand struggled to target varied buyers with personalized content to boost conversions. They opted for Contentstack's real-time CDP to enable them to harvest behavioral data and convert anonymous website visitors into specific audiences using tailored content.

The changes resulted in a 30% increase in conversions and a 29% increase in click-through rate (CTR).

Read more on how Contentstack's real-time CDP supported Land O'Lakes' data collection and personalization initiatives.

FAQ section

How does customer data improve B2B personalization outcomes?

Customer data provides valuable insights into customer behaviors, trends, and patterns, enabling B2B marketing teams to create content that resonates.

What are the risks of relying on outdated customer data?

Outdated data provides inaccurate insights, leading to poor decisions, disjointed interactions, and missed opportunities.

Which customer data types are most critical for B2B customer experience?

Key data types include behavioral, transactional, technographic, engagement, and intent data.

How can B2B companies ensure data privacy while implementing data-driven personalization?

Enterprise B2Bs must obtain consent to collect data and comply with GDPR and CCPA. They must also ensure that they have robust security frameworks to protect customer data from breaches and other security risks.

Learn more

Capturing customer data enables B2B companies to personalize the buyer's journey. The data insights enable accurate targeting and messaging that drive engagement, sales, and retention. This is essential as research now shows that the modern customer demands more personalized experiences. 

A customer data platform (CDP) is the ideal tool to support this process, as it enables you to collect, harmonize, and activate customer data for personalized insights and customer journeys. Talk to us today to learn how our real-time CDP can help you maximize customer data for personalized interactions.