audience

Audience development is crucial in the age of bespoke, niche subscriber-oriented content. Below, find the most recent reviews, essays and guides about audience.

52 posts from audience See another: essays, the business of content, web

Members January 21, 2021 by dc in newsletter

CT No. 70: Everyone’s invited to the first-party data party

1/21: First-party data collection 101, a free-to-use robust survey tool; and great stats on news consumption and audience trust.

January 15, 2021 by dc

Gathering audience data from your content

Data management is a part of your life as a content professional. Learn why content marketing and digital publishers should have a content-based data strategy.

Members January 7, 2021 by dc

What do the Capitol riots say about our storytelling and media practices?

Our culture needs to reconsider -- deeply, honestly -- the economics and standards of the content and media environment.

Members October 29, 2020 by dc

Big marketing stats with no context are (defeatable) monsters

Our professional conversations in the age of data excess and growth hacking don’t often reflect complex narratives. Data should never shut down reasonable dissent.

October 15, 2020 by dc

Google Analytics 4: What content strategists and analysts need to know

Google Analytics 4 will likely change how the web approaches content measurement, and content strategists and marketers should take note: these are changes for the better.

Members September 24, 2020 by dc

Planning to build trust through content in 2021

At the intersection of content, media and technology, we’re in a unique position to ensure facts are correct. What can we do to plan for the future?

Spotlight newsletter

CT No.245: Billy Joel mathletics

CT No.244: Explicating "attention" in LLMs

The words we publish and hold up for peer review remain the best representation of our brains at work in the digital world. A published paper is the best way to look closely at the foundational assumptions of LLMs. And those begin with pop culture.

CT No.243: Disambiguation, sliding doors, hallucinations, and madeleines

Transformers take static vector embeddings, which assign single values to every token, and expand their context, nearly simultaneously as they process the context of every other word in the sentence. But who cares, let's listen to a pop song!

CT No.242: What's your vector, Victor?

How to understand tokens and vector embeddings, for word people.

CT No.241: TF? ID(GA)F: The old faithfuls of language processing

Even in the face of "black box" algorithms, the history of artificial intelligence—natural language processing, more specifically—has left plenty of clues. While we can't understand the full equation, we can see how building blocks create common patterns in how current algorithms process language.