The blog of Ready State, a rigorously lean marketing agency
As marketers start evaluating machine-learning systems, it’s crucial to spot when that title is deserved—and when it’s just a buzzword
From a lack of candor to ill-conceived job descriptions, we’ve identified several pervasive issues content marketers within large organizations face—and ways they can handily address them.
Jargon isn’t gibberish to everyone. And it’s not all bad. When you use and target it appropriately, you can considerably improve the efficiency and effectiveness of your message.
To effectively collaborate, marketers and data scientists need a common language. Here are seven of the most important terms to know in our glossary of AI terms for marketing.
We paired a writer with a designer, and asked them to analyze, deconstruct, and rebuild the case study. Here’s what we found and what we recommend doing.
Machine learning’s near-term effect on marketing is underappreciated. Marketers think of it as recommendation engines and mix modeling. It’s much more than that.
You can create wildly varied content by experimenting with different text-driven formats.
Producing great content is nothing like manufacturing SpaghettiOs. The best ingredients, tools, and metrics of success change frequently.
Sometimes, rounds of well-intentioned edits chip away at reader value. Here’s how it happens.