Love In Tokyo(1966), AI Visibility & E-E-A-T

2023 : Change in consumer behavior and advent of GEO

Since 2023, I noticed something interesting post the ChatGPT moment. Visitors to my travel website were no longer finding it because they searched for it. Increasingly, they were arriving after asking ChatGPT, Gemini or another AI assistant about a 1960s Bollywood film called Love in Tokyo. Why? Lets step back a little. For more than 25 years, marketing has been built around a familiar question:

"How do we get customers to visit our website?"

That still matters today, but, the mechanics have shifted from Google ranks to a very different question:

"How do we become the source that AI trusts when answering our customers?"

That is a profound shift. As the world was busy figuring out "lets create more content with AI", I am more interested in learning " What makes AI cite my content ". Below is a graphic which shows for a quick prompt "show me locations for a Bollywood fan in Japan", it brings in my Experience Tokyo website recommendation as "Hibiya Park".

Love In Tokyo (1966) : Human Curiosity & Social Impact  

2016, over the new year holidays, I did a casual personal project. Out of curiosity, I retraced the filming locations of the 1966 Bollywood classic Love in Tokyo, photographing the same places 50 years later and documenting how Japan had changed over time. The post quickly spread across India, being featured by India Today, Indian Express, Loksatta, Scroll.in, travel websites and thousands of social media users. My site was FLOODED with traffic. Below is Indian Express running a photo story of their site.

"Human Experience" as the Ultimate Anti-AI Signature

It was my first observation, that original and human experience-led content has a remarkable ability to travel far beyond its intended audience. Long before I began talking about Generative Engine Optimization, this article had already illustrated its fundamental principle: create something genuinely unique, and people and increasingly AI, will find and reference it. In the world of AI-slop, value will move back to original human experiences but augmented with AI (I will talk about that augmentation at the end)

The E-E-A-T Strategy for Content Marketing

So let me get this straight, I am not talking about E-E-A-T because we are in the age of AI, but that is the fundamental logic of human communication and I will deconstruct this in the context of the Love In Tokyo blog article. 

E-E-A-T Experience (体験): AI extremely selective about trusting exceptional content

LLMs are smart enough to catch generic, AI-written or generated content. The "Experience" part of E-E-A-T is a marketers best defense against getting filtered out. Because I physically went to these locations, in Hibiya Park, Haneda, Tokyo Tower etc., and also cross-referenced old layouts, and captured original photography, the text has a natural, unique semantic signature. AI models recognize that this content cannot be auto-generated by a script. See an example below for a "human touch" content, which is not hi-res nor flashy, but experiential value.

E-E-A-T Expertise(専門性): Building a body of knowledge

If experience is about what I have created as an original human story, expertise is about what a marketer does consistently updated, documented and shared over time. Over time, I expanded the project beyond blog posts. I published detailed location guides, recreated historical photographs from the exact camera angle, contributed verified information to Wikipedia (see image below), added historical context to Google Maps, and documented locations that had never previously been identified online. Each new contribution reinforced the previous ones, creating a network of consistent and verifiable information. This is what expertise looks like in the AI era.

E-E-A-T Authority(権威性): Becoming the source others refer to

Authority is often misunderstood as popularity. They are not the same thing. A social media post may receive millions of views and still have little authority. True authority develops when other credible people and organizations consistently reference your work. Every citation, interview, publication reinforces the signal that the content is worth trusting. My Love in Tokyo project, for example, gained authority not because I promoted it (rather I do not know who made it viral, even today), but because newspapers, bloggers and film enthusiasts began referencing it whenever the subject of the movie's Japanese locations came up. AI systems observe these signals across the web. In a recent event by Sendenkaigi and Adobe, I used this as a paradigm for Japanese marketers and now referencing that article here (Sendenkaigi-advertimes GEO Seminar) is one way of creating continuing authority

E-E-A-T Trust(信頼性): Earned through accuracy and consistency

The Love in Tokyo project taught me that trust isn't built by publishing a single great article. Every filming location was carefully verified against scenes from the original movie, historical photographs and on-site visits. When new information emerged, I updated the content rather than leaving outdated details online. Over time, readers, film enthusiasts, journalists and researchers began returning to the site because they knew the information could be trusted. In the age of Generative AI, trust is created one verified fact at a time, and it is this confidence that makes both people and AI willing to reference it.  I still update it and now here is the part where I have used GenAI to create some part of the content. I wanted to give a handout of sorts in Hindi and English so that anyone can use it to go to all these locations. I prompted Adobe Firefly to make it and below is the output. Saved time with AI, but also made the output valuable for readers. Not just creating some unreal imagery. In travel "real" matters and I never have played with the photography which is intentionally non AI.