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Honing In podcast artwork

Business

Honing In

Business · EN

9 recent guestsAudience: 3
Apple PodcastsWebsite

About this Podcast:

Honing In is a podcast for creative thinkers where we’ll hone our skills, explore our passions, and nurture our dream projects into being.

Pitch Analysis

Required Pod Score for this podcast. PitchCentric checks your profile against host openness, topical fit, and audience signals before you generate a pitch.

Contact path

Verified email

Booking probability

31%

Guest openness

Selective

Verified email on file
80/100
Required Score

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Questions about Honing In

What is Honing In about?

Honing In is a podcast for creative thinkers where we’ll hone our skills, explore our passions, and nurture our dream projects into being.

What has Honing In covered recently?

Recent episodes include "When Coffee Becomes Your Career: From Barista to Author with Morgan Eckroth of Morgan Drinks Coffee" (14 October 2026, 43 minutes), "Portals, Paradoxes, Numerology, and Turning 40 with bee scolnick" (23 September 2026, 67 minutes), and "We have a lot to learn from plants! Exploring Milpa Culture with Keitlyn Alcántara, PhD" (9 September 2026, 50 minutes).

How often does Honing In publish?

Honing In publishes roughly every two weeks, with episodes averaging 47 minutes.

How hard is it to get booked on Honing In?

Booking probability for Honing In is 31%, and the host is rated Selective on guests. Honing In requires a Pod Score of 80 or higher. Honing In's contact route on record: verified email.

About the host

Honing In is a business podcast.

Verified host email: ████████@████.comSign in to unlock →

Recent episodes

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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Recent guests

Recent guests on Honing In. Study who booked and why before you pitch.

Best industries to pitch Honing In for

Based on semantic analysis of episode topics and host coverage, this podcast is a strong guest fit for executives in:

Businessstrong

Industry fit is computed by PitchCentric using vector embeddings of the podcast's episode catalog.

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