The Digital Marketing Podcast by Exposure Ninja

Human First Marketing: Rethinking Marketing in the AI Era

·56 min·5 clips

Phil shares that over $950 million in ad spend was wasted last year because no one can remember it.

The episode begins with Charlie introducing Phil Trugas-Evans, CEO of Giraffe Social Media, to discuss his book 'Human First Marketing'. Phil defines the concept as shifting from B2B or B2C to human-to-human marketing, emphasizing that marketing involves real people. He explains that data and short-term pressures have caused marketers to overlook the human aspect. The conversation moves to AI, where Phil distinguishes between 'lazy AI' and using AI as a tool, advocating for transparency and a human-plus-AI approach. They discuss ad fatigue, with Phil citing a study that people see about 362 ads daily but only recall 12, highlighting wasted ad spend. Phil advises brands to use empathy and native advertising to cut through noise. He introduces the EMPATH framework as a detailed alternative to customer avatars, focusing on emotional understanding and audience feedback. Phil critiques the traditional marketing funnel, noting it was created in 1898 and doesn't reflect the non-linear modern consumer journey. He proposes the 'pinball method', where marketing tactics act as boosters to keep customers engaged. The discussion covers advocacy, with examples like Harley-Davidson tattoos, and how B2B brands can build loyalty through founder visibility. Phil concludes by recommending putting human faces in marketing content to increase trust.

As heard by us

A grounded case for treating authenticity as a marketing asset in AI-era content.

Human First Marketing looks at AI-era marketing as a people issue before it becomes a tooling issue. Phil Trugas-Evans, CEO and co-founder of Giraffe social media agency, makes the case for putting people back at the centre of marketing, arguing that data and new methods can…

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Why you'd press play

You want your marketing to feel human while AI and overloaded feeds make realness harder to prove.

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