B2B Marketing Data: Capturing and Managing Data for Actionable Insights
B2B Marketing Data: Capturing and Managing Data for Actionable Insights

B2B Marketing Data: Capturing and Managing Data for Actionable Insights

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WHAT’S IN THIS REPORT? This report includes a breakdown of all the different types of data B2B brands can capture on their audience. It will also cover best practices on how to source this data and the best ways to manage and integrate it for actionable insights.

As account-based marketing and the delivery of targeted, personalized content become more prevalent for business-to-business (B2B) marketers and sellers, data is of utmost importance. Without a proper marketing data management strategy in place, B2Bs cannot execute these programs.

  • Many B2B companies cite a lack in data expertise as an obstacle to implementing a true data-driven strategy.
  • B2Bs use a variety of first-, second- and third-party data sources in order to build profiles on their audience at both the buyer- and account-identity level.
  • Marketers need to ensure data is accurate, valid and up to date. Additionally, data compliance is a big concern to multinational B2B firms in the wake of the EU’s General Data Protection Regulation (GDPR).
  • All data sets must be integrated in a centralized system of record. A variety of vendors claim to give a complete view of the customer, but B2Bs are skeptical and confusion remains in the marketplace.
  • Collecting data is an important first step. From there, analyzing and putting those data-driven insights to work becomes table stakes. More advanced brands are using intent data and artificial intelligence (AI) to model customer lifetime value, build lookalikes and implement targeted account-based programs.
  • A dedicated team with a data science background is needed to manage and execute against this data. This group must be aligned with business goals for maximum success.


  1. Marketing Data Management Strategies: In Search of ‘Perfect Integrity’
  2. Building a B2B Marketing Database: The Data
  3. Ensuring Data Accuracy
  4. Making Data Actionable
  5. Key Takeaways

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