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.
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.
Customer feedback has become a precious commodity for content marketers. The lessons ecommerce vendors are learning from reviews apply to any online content business. It's time to listen to your customer feedback.
Visual concepting tools have branched into the strategy, brand, and content disciplines. They present rich canvases to communicate vision, a far cry from algorithms that fill content templates.