B2B Marketing with Fexingo: Enterprise Demand Gen, ABM, and Long Sales Cycles

B2B Marketing with Fexingo: Enterprise Demand Gen, ABM, and Long Sales Cycles

By FexingoBusiness
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B2B Marketing with Fexingo: Enterprise Demand Gen, ABM, and Long Sales Cycles episodes

  • How B2B Podcasting Delivers 4x the Pipeline of Webinars

    In this episode, Lucas and Luna dive into a specific case: how the cybersecurity firm Darktrace used a branded podcast to generate qualified pipeline at four times the rate of their webinar program. They break down the math — $12,000 per episode versus $25,000 per webinar, a 52 percent lower cost per qualified lead — and discuss why long-form audio builds trust in complex B2B sales cycles. Luna pushes back on the time commitment, and Lucas explains the repurposing playbook that turns one episode into 12 content assets. If you're in enterprise marketing and tired of low webinar conversion, this one's for you.

    #B2BMarketing #EnterpriseMarketing #BrandedPodcast #PodcastROI #DemandGen #Darktrace #ContentMarketing #SalesCycle #ABM #PipelineGeneration #PodcastStrategy #B2BPodcast #MarketingROI #BusinessPodcast #FexingoBusiness #PodcastTips #ContentRepurposing #LeadGeneration

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    7 min
  • How ABM Cut Customer Acquisition Cost by 30 Percent at Snowflake

    In this episode of B2B Marketing with Fexingo, Lucas and Luna dive into how Snowflake used account-based marketing to reduce customer acquisition cost by 30% while increasing deal sizes. They explore the specific tactics: tier-one account selection, personalized content journeys, and sales-marketing alignment. Lucas breaks down the numbers from Snowflake's 2025 fiscal year and explains why ABM works best for high-value enterprise deals with long sales cycles. Luna questions whether the approach scales and whether the 30% CAC reduction holds up across all tiers. They also discuss the role of intent data from companies like 6sense and Bombora, and the importance of measuring engagement metrics beyond pipeline. If you're in B2B marketing or sales, this episode gives you a concrete framework and real benchmarks to apply.

    #Snowflake #ABM #B2BMarketing #DemandGen #EnterpriseSales #CAC #IntentData #SalesMarketingAlignment #MarketingOps #BusinessPodcast #FexingoBusiness #AccountBasedMarketing #SaaS #GrowthStrategy #MarketingROI #DataDriven #Podcast #SalesCycle

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    9 min
  • How Sixsense Shortened B2B Sales Cycles by 28 Percent

    In this episode, Lucas and Luna dive into the specific tactic that Sixsense used to cut its average sales cycle from 145 days to 104 days — a 28 percent reduction. They break down the exact changes Sixsense made to its lead scoring model by incorporating intent data from third-party sources, how it re-sequenced its email nurture tracks for the top five account tiers, and why it stopped sending generic ROI calculators to accounts that were already in active vendor evaluation. You'll hear concrete numbers on response rates (up 38 percent) and close rates (up 19 percent) after the change, plus a comparison to Demandbase's cycle-slicing playbook from episode one. No vague theory — just a single case study with enough detail to borrow the idea for your own ABM program.

    #Sixsense #B2BMarketing #AccountBasedMarketing #SalesCycle #IntentData #LeadScoring #DemandGen #EnterpriseMarketing #MarketingOps #ABMStrategy #RevenueOperations #SalesAndMarketingAlignment #NurtureSequencing #CaseStudy #FexingoBusiness #BusinessPodcast #MarketingPodcast #SaaSMarketing

    Keep every episode free: buymeacoffee.com/fexingo

    10 min
  • How Demandbase Sliced Its Sales Cycle by 40 Percent

    In the premiere episode of B2B Marketing with Fexingo, Lucas and Luna dive into a single, revealing case study: how Demandbase, a leading account-based marketing platform, compressed its enterprise sales cycle from nine months to just over five. The conversation explores the specific tactics the company used—from intent-data scoring to a radical restructuring of its sales development team—and what those moves mean for B2B marketers wrestling with long, opaque deal cycles. Lucas breaks down the numbers behind Demandbase's win rate improvement, while Luna presses on whether the approach can scale beyond tech companies. No theory, no fluff: just one concrete example that changes how you think about ABM execution. Welcome to a show that earns your commute.

    #Demandbase #ABM #B2BMarketing #SalesCycle #IntentData #EnterpriseSales #DemandGen #MarketingOps #SalesDevelopment #Business #Marketing #Podcast #FexingoBusiness #BusinessPodcast #CaseStudy #Gartner #TechMarketing #AccountBasedMarketing

    Keep every episode free: buymeacoffee.com/fexingo

    8 min

About B2B Marketing with Fexingo: Enterprise Demand Gen, ABM, and Long Sales Cycles

From the publisher's feed

Lucas and Luna cut through the fog of B2B marketing hype to focus on what actually moves enterprise revenue: demand generation for six-figure ACV deals, account-based marketing that aligns sales and marketing, and navigating sales cycles that stretch six to twelve months. Each episode takes one core challenge—building a tier-1 ABM program from scratch, measuring pipeline influence without vanity metrics, structuring a lead-scoring model that sales trusts—and examines it through real company cases: how Snowflake’s ABM team orchestrated 200+ target accounts in a quarter, how Salesforce revamped their demand-gen engine after a pipeline slump, or how Gong used intent data to shorten their enterprise sales cycle. Lucas brings the journalist’s rigor—citing specific cost-per-opportunity figures, conversion rates from industry benchmarks, and budget-allocation examples from public earnings calls—while Luna tests each idea against the messy reality of marketing ops, sales alignment, and resource constraints. The show is for heads of demand generation, ABM program managers, and B2B marketing leaders who are tired of platitudes and want the math behind the playbook. Why do so many ABM programs spend 80% of their budget on the bottom 20% of target accounts, and how do you build a data-driven account tiering system that doesn’t require a PhD in statistics?