AI-Friendly Content & Metadata Taxonomy

Utrip

 

AI-Friendly Content

Problem

We had to build a database for things to do in as many destinations around the world as we could. This not only meant researching, curating, and writing/editing content, it also meant making sure that the content interacted correctly with backend algorithms.

And then there was the scaling issue, to boot.

 

Solution

I made—and oversaw the creation of—tens of thousands of pieces of content, each of which would surface based on a user’s preferences.

 

Result

  • The best AI-based, personalized travel recommendations

  • Tens of thousands of pieces of content

  • 10x content creation scaling

 

Who I worked with

Engineers, sales, account management, C-suite, biz-dev, marketing

 

What I’d change

  • Focus more on how users interacted with the UI

  • Advocate for gathering user insights and make data-informed content decisions

 

Metadata Taxonomy

problem

Metadata was inconsistent, had overlap, misspellings, and was sometimes way too specific to be useful.

 

solution

Our developers exported a list of our entire tag database, and then I worked with another member of the content team to remove and consolidate hundreds of tags and group them into categories. Then, i grouped those categories to be consistent with our user interface.

 

Result

A more consistent list of metadata, which was eventually used to help a content ingestion/scaling tool.

 

Who I worked with

Developers, other members of the content team

 

What I’d change

I got a little in the weeds putting the tags into the intermediate categories—all in the name of a project that never ended up happening. So instead, I’d focus more on the consolidation and general categories.

 
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