Audience research, digital channel evaluation, brainstorming and ideation, competitive positioning, information architecture, developing pillars, defining success, writing briefs, big thinking about content’s purpose, and the expertise/proof needed to create great content.
There's no point in denying it—the social media landscape has undergone some significant changes. Here's what we're doing to shift our strategy and stay in the game.
As tension in the entertainment industry rises, studios are turning to canonical stories to guarantee ticket sales. But does identifiable content always mean good content?
In the rising world of automation and content proliferation, where search engines are already experimenting with embedding generative AI in their results, how do creators and businesses stand out? Reader experience may just hold the answer.
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.
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.
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.
To put it another way: optimizing with GEO reverse engineering tactics is like entering a house through a small attic window. GEO ignores that the research frameworks literally embedded in the outputs of the model are the keys to the front door.
