A resource for content professionals working in the age of algorithms

Baby's umpteenth tradeshow: How the news publishing industry is surfing the AI tide

What I heard and did not hear at ONA

Downtown Chicago, featuring the Chicago Tribune.
286 posts

Keep brands weird: The research framework for exceptional data-driven content

A diagram of the Content Research Framework, showing categories of self-collected and co-collected insights.

If you’re feeding yourself the same inputs as everyone else, you run the risk of homogenous, bland, boring content. This content research framework will help you find the right data.

Setting the stage for content project success: Best practices for a strong kickoff meeting

Setting the stage for content project success: Best practices for a strong kickoff meeting

Leave every participant with a clear understanding of what the team aims to accomplish. However, reaching that point involves research and stakeholder input. Check out our tips for running kickass kickoffs.

Is logic modeling a life raft for content teams? Introducing evaluation logic to private companies

Is logic modeling a life raft for content teams? Introducing evaluation logic to private companies

Increased accountability might be frightening to some, but evaluation should also have a place in private companies. Whatever regulation exists isn’t cutting it, especially considering recent rounds of mass layoffs and executive-level scandals that leave well-meaning employees without recourse.

Engagement rate and beyond: The best TikTok, Facebook & Instagram metrics for content analysis

Engagement rate and beyond: The best TikTok, Facebook & Instagram metrics for content analysis

Can’t remember when you last took a look at your social analytics numbers? Today’s the day for a health check-up.

On iteration: Why digital business folks and content producers don’t always see eye-to-eye

On iteration: Why digital business folks and content producers don’t always see eye-to-eye

Iteration is a repetition of a process to solve a specific problem, and it’s a big part of how machine learning algorithms are developed. But the way devs and data scientists think about iteration doesn’t always match with editorial and entertainment industry production methodologies and norms.

Parrots are not stochastic and neither are you

Collage of parrots and mathematical formulas by Arikia Millikan

Like humans, parrots comprehend. They understand options and make choices based on comprehension. While the stochastic output of an LLM can seem like an entity deciding or exercising creative thought patterns, it’s just an algorithm running on a computer.

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