Episode

Best of LinkedIn: Field Marketing CW 28/ 29

Podcast
Best of LinkedIn: Strategic B2B Marketing
Published
Jul 22, 2026
Duration seconds
1469
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Canonical source
https://frenus-marketing.podigee.io/208-best-of-linkedin-field-marketing-cw-28-29
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https://audio.podigee-cdn.net/2553343-m-e87c03f350dd39d0d953616b7e14fce3.mp3?source=feed
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/v1/public/podcasts/best-of-linkedin-strategic-b2b-marketing-7370361/episodes/best-of-linkedin-field-marketing-cw-28-29
Markdown
/podcast/best-of-linkedin-strategic-b2b-marketing-7370361/best-of-linkedin-field-marketing-cw-28-29.md

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Summary

We curate most relevant posts about Field Marketing on LinkedIn and regularly share key takeaways. We at Frenus supports clients with identifying target attendees for events, crafting outreach that cuts through the noise, and driving qualified registrations through strategic LinkedIn engagement. You can find more info in the description: https://www.frenus.com/usecases/linkedin-event-outreach-attendee-acquisition This edition collectively examines the evolving landscape of corporate events and field marketing in 2026, shifting the focus from mere logistics to strategic revenue generation. Experts argue that successful trade shows depend on extensive pre-show preparation and disciplined follow-up rather than expensive booth designs or passive lead collection. The texts highlight a growing preference for intimate, community-driven micro-experiences and distributed event strategies over traditional, high-volume "mega-conferences". Emerging AI tools and platforms are showcased as vital for automating lead capture, enriching data, and proving measurable ROI to stakeholders. There is also a strong emphasis on human-centric design, where authenticity, cultural intelligence, and emotional connection are viewed as the primary drivers of buyer confidence. Ultimately, the sources suggest that events are no longer standalone marketing activities but integrated business motions that must align sales, marketing, and leadership to build lasting trust. This podcast was created via Google Notebook LM.