The Top 5 Customer Data Use Cases B2B Marketers Need to Know

March 11, 2024 | 5 minute read
Jake Spencer
Principal Product Strategy Manager, Oracle Advertising and CX
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The complexity and importance of B2B customer data doesn’t get enough attention.

While it’s compelling to hear about a massive B2C retailer with millions of customers and hundreds of engagement, B2B marketing, CX, and analytics teams must navigate a data landscape that spans entire companies, typically with multiple entities, not just individual consumers. In Forrester’s Marketing Survey, 2023, B2B respondents cite lack of trust in the quality of data supporting analysis (40%), insufficient understanding by their teams (39%), and too many unconnected data sources (38%) as the top obstacles to executing measurement and analytics.

B2B data complexity is compounded by the diverse array of data sources that B2B customer journeys entail, including emails, zoom/phone calls, in-person meetings, conferences, and digital touchpoints. Not to mention all of the operational customer and account data that exists in the back office such as transactions, buying patterns, financial health, inventory. and more. Each of these channels generates valuable data points, but they often exist in silos, leading to fragmentation and challenges in integrating a cohesive view of the customer journey.

To untangle the mess of data, marketing and sales teams are increasingly looking to customer data platforms (CDPs) like Oracle Unity CDP. Customer data platforms are purpose built to bring critical customer data sources together and organize it in actionable customer and account profiles. The goal is to help businesses attain the marketing holy grail—the right message, to the right person, at the right time.

So what are the specific use cases you can achieve with a CDP, and why does that matter? Here are the top 5 CDP use cases.

 

Top 5 CDP Use Cases

1. Building a Single Customer and Account View

Customer relationships and buying journeys are complex in B2B, often involving multiple stakeholders and touchpoints across various channels. A CDP unifies data from disparate sources such as CRM systems, marketing automation platforms, website interactions, email engagements, data warehouses, ERP systems, and more to build actionable profiles. These account and customer profiles contain attributes, and the CDP applies AI-based predictions and analytics to help marketing and sales teams absorb that vast amount data in ways they can act on them, in ways relevant to the customer. This comprehensive understanding enables B2B companies to tailor their communication and offerings to meet the specific needs and preferences of individual clients, fostering stronger and more valuable relationships.

Why does this matter? Data operations around customers and accounts are commonly inefficient and therefore costly. A CDP creates a customer data playbook—so every time,CX or sales teams know a customer’s history and how to best engage them in the next step of their journey.

A major telecommunications provider used Oracle Unity CDP to connect more than 40 unique data sources (including first and third party sources) to create a single view of its customers and accounts. This let the marketing team eliminate manual data processes, quickly turn around hyper-targeted campaigns—in days rather than weeks—and increase the number of successful opportunities by 20%. That success came from understanding purchase intent signals and engaging customers while they’re ”in the buying moment.” and.

 

2. Predictive Scoring, Analytics, Recommendations and Predictions

Identifying high-quality leads is paramount for B2B sales and marketing teams. CDPs leverage predictive analytics algorithms to analyze historical data and identify patterns indicative of future buying behavior. By scoring leads based on their likelihood to convert, B2B organizations can prioritize their efforts and allocate resources more effectively, ultimately driving higher conversion rates and revenue growth.

Why does this matter? No more guess work. Are you using manual scoring models to attribute revenue? Taking your “best shot” at the right list for a new campaign? Sending half an audience down a multi-step nurture when they’re not ready to buy? We’ve all been there and probably still are. Let’s face it, AI and machine learning  can help in making predictions on who is ready to buy and recommending what might interest them. The right customer data platform will run AI/ML models against a rich set of customer data to let marketers ditch the manual math equations. Instead, these CDPs use AI to help marketers and sellers measure campaigns, score accounts, and predict what they should be doing next.

 

3. Granular Segmentation for Account-Based Marketing (ABM)

Account-based marketing has emerged as a powerful strategy for B2B companies to engage key accounts and deliver tailored experiences. CDPs play a crucial role in ABM by helping marketers segment and target accounts based on firmographic data, past interactions, and behavioral insights. By delivering personalized content and messages that resonate with the specific challenges and objectives of target accounts, B2B marketers can significantly enhance engagement and drive conversions.

Why does this matter? Segmenting your customers manually is difficult, time consuming, and costly. Proper segmentation is the foundation of marketing campaigns, and ultimately what makes a brand relevant to its customers. But relevancy has a time limit. This means marketers need fast access to actionable data that can be used to identify the right audience and quickly understand what matters to them. Customer data platforms enable marketers to slice and dice segments in minutes, not months.   

 

4. High Converting Cross-Sell and Upsell Campaigns

For B2B companies with diverse product portfolios or service offerings, cross-selling and upselling present significant revenue opportunities. CDPs analyze customer behavior and purchase history to identify cross-sell and upsell opportunities based on complementary products or value-added services. By proactively recommending relevant offerings at the right time, B2B organizations can increase customer lifetime value and strengthen their competitive position in the market.

Why does this matter? Because leads, pipeline, and revenue are being left on the table. McKinsey & Company found that 80% of the value creation achieved by the world’s most successful growth companies comes from their core business—principally, unlocking new revenues from existing customers. CDPs create the complete “customer playbook” that helps marketing and sales evolve toward an account-centric growth engine, leveraging their greatest revenue opportunity: their existing customer base.

 

5. Improved Customer Retention and Loyalty

Retaining customers is often more cost-effective than acquiring new ones, making customer retention a top priority for B2B organizations. CDPs support proactive customer engagement by tracking key metrics such as customer satisfaction scores, renewal dates, and usage patterns. By identifying at-risk accounts and deploying targeted retention campaigns, B2B companies can mitigate churn, foster long-term loyalty, and maximize the lifetime value of their customer base.

Why does this matter? It’s far more profitable to focus on keeping customers and keeping them happy. That same McKinsey & Company study found that compensating for the value of one lost customer can require the acquisition of three new customers. CDPs aren’t just helpful for new revenue, it can also help customers stick around for the long haul as well.

 

Learn More:

If you’re an enterprise wondering how a CDP could help you, start here by testing your customer data maturity or request a demo to speak with us!

 

Jake Spencer

Principal Product Strategy Manager, Oracle Advertising and CX

Jake Spencer is a principal product strategy manager at Oracle. He has spent the majority of his career working for enterprise technology brands like SanDisk and Talend in all aspects of branding, digital marketing, and web analytics. At Oracle, Jake helps manage product communications, solution building, storytelling, and enablement for the Oracle Unity Customer Data Platform, Oracle Audience Segmentation, and other CX products.


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