Skip to main content
    Beta — Features may not work as expected.
    Back to Podcasts

    Second-Party Data: AI Unlocking Ecosystems

    BM
    Bob MooreCrossbeam — Co-Founder and CEO
    0 views
    Share:

    Morning everybody. I'm super excited to welcome Bob Moore, founder and CEO of Crossbeam. Bob, welcome to our podcast today. Great to Be here. Uh, long You know, we've had so many conversations in private, it's great to, uh, have them all over again, uh, for the, for the world to see And many new things of course. So, but before we get started, I'd love to have you take a minute and introduce yourself. Alright, hey, yeah, I am Bob Moore. I'm the CEO and Co-founder of Crossbeam. Uh, if you're not familiar with Crossbeam, I'm sure we'll talk about it a bunch, but we're basically, uh, the leading platform for helping companies, uh, account map with each other.

    TL;DR

    Bob Moore, co-founder of Crossbeam, discusses his journey from venture capital analyst to serial entrepreneur. He explores the evolution of data analytics, the shift from internal business intelligence to shared ecosystem data, and how companies leverage account mapping to unlock hidden revenue opportunities within their partner networks while maintaining strict data privacy and security.

    "The most valuable data for your next stage of growth isn't actually inside your own company; it's sitting in the CRM of your partners waiting to be safely unlocked."

    — Bob Moore

    What We Discussed

    The Evolution of Business Intelligence and Analytics

    Bob Moore began his career at Insight Partners, where he noticed a massive gap in how companies understood their own performance. Many successful businesses were growing rapidly but remained unsophisticated regarding their data. Bob spent his early years manually crunching numbers using SQL and Excel to provide world-class analytics to portfolio companies. This manual work eventually became the foundation for his first company, RJ Metrics, which sought to productize venture-grade insights.

    • •Early growth companies often lack the internal expertise to conduct deep cohort analysis.
    • •Customer Lifetime Value (LTV) is one of the most critical yet misunderstood metrics in SaaS.
    • •RJ Metrics automated the manual tasks of a VC analyst for the broader market.
    • •Building a business around SaaS delivery for analytics was considered novel in 2008.
    • •Data visualization techniques help non-technical stakeholders make better decisions.
    • •The transition from manual spreadsheets to automated products defines the modern data era.
    • •Success in analytics requires a focus on clean data and actionable insights.

    Solving the Data Fragmentation Problem

    A recurring theme in Bob's journey is that each company solved a problem created by the previous one. Stitch Data was a spinoff of RJ Metrics designed to fix 'data plumbing' issues. In the modern tech stack, a company's data is scattered across Shopify, HubSpot, and Facebook Ads. Without a way to centralize this information, answering simple questions about marketing ROI becomes nearly impossible. Stitch provided the infrastructure to move this data into a single source.

    • •Modern businesses utilize an enormous universe of disparate systems of record.
    • •Shopping carts like Shopify hold transaction data but lack marketing context.
    • •Ad spend platforms often remain siloed from the actual revenue data in the CRM.
    • •The mission of Stitch was to suck data out of various platforms into one spot.
    • •Effective attribution requires connecting the dots between sales and marketing tools.
    • •Data specialists often find themselves in the business of technical plumbing.
    • •Integrated data allows for a 360-degree view of the customer journey.

    Unlocking Revenue Through Account Mapping

    Crossbeam represents the next step in data evolution by looking outward. Instead of just analyzing your own data, Crossbeam helps you find value in partner data. This process, known as account mapping, allows two companies to compare their CRM records securely. By identifying overlapping pipelines, sales teams can prioritize leads that already have a relationship with a trusted partner, creating a more efficient and effective sales process through ecosystem-led growth.

    • •Account mapping is the primary use case for Crossbeam's partnership platform.
    • •Identifying sales pipeline overlaps reveals high-probability targets for sales teams.
    • •Second-party data collaboration is the logical next step for mature SaaS companies.
    • •Partners can provide warm introductions that increase conversion rates significantly.
    • •The platform acts as a trusted third party to facilitate secure data comparisons.
    • •Ecosystem data provides competitive advantages that internal data cannot match.
    • •Traditional partnership management was often manual and error-prone before automation.

    Maintaining Data Privacy in the Ecosystem

    Security is the biggest barrier to sharing data between companies. Bob explains how Crossbeam uses privacy-first technology to ensure that sensitive CRM data is never exposed. Companies can determine exactly what information they want to share and with whom. By using secure hashing and granular permissions, the platform allows for collaboration without the risk of a data breach or competitive intelligence leaks, making the 'partnership world' much safer.

    • •Data privacy is a non-negotiable requirement for enterprise SaaS collaboration.
    • •Crossbeam ensures that companies only see the intersections they agree to share.
    • •Protecting sensitive CRM data is essential for maintaining trust within an ecosystem.
    • •Secure hashing allows data to be compared without revealing the underlying records.
    • •Granular permission settings give users total control over their shared assets.
    • •Compliance with international regulations is a core component of partnership tech.
    • •Building a safe environment for data sharing encourages more robust collaboration.

    Frequently Asked Questions

    Key Takeaways

    Data CollaborationShare data with partners without exposing sensitive CRM details.
    Account MappingIdentify overlapping sales pipelines between partner organizations.
    BI EvolutionAutomate business intelligence with modern SaaS platforms.
    Product DevelopmentSolve specific technical hurdles with new SaaS products.
    Operational TransparencyBuild stronger revenue channels through clear partner operations.
    Data IntegrationImplement ETL processes to overcome e-commerce data silos.
    Growth StrategyUse strategic partnerships as a primary growth lever.
    Onboard