Hubspot is a universe of possibilities, and creativity multiplies the number of problems we can solve in completely new ways.
Creativity is an important tool to generate insights and build solutions that go beyond the obvious.
I talk a little bit more about that in (Linkedin post). I also highlight a great example from Canva in Brazil, where they used creativity to create fictional companies based on what celebrities are known for, and later revealed that all the branding and content had been made using Canva.
After discussing that, I deliver this step-by-step that works for me. What is the process you use to achieve creativity, or what improvements do you include in this model?
Hubspot is a universe of possibilities, and creativity multiplies the number of problems we can solve in completely new ways.
Creativity is an important tool to generate insights and build solutions that go beyond the obvious.
I talk a little bit more about that in (Linkedin post). I also highlight a great example from Canva in Brazil, where they used creativity to create fictional companies based on what celebrities are known for, and later revealed that all the branding and content had been made using Canva.
After discussing that, I deliver this step-by-step that works for me. What is the process you use to achieve creativity, or what improvements do you include in this model?
Great perspective! I really like how you connect creativity with practical problem-solving in HubSpot. The Canva Brazil example is a strong reminder that storytelling and experimentation can unlock new use cases. For me, creativity improves when I combine user insights with small tests and quick iterations refining ideas based on real feedback.
Creativity is a natural ability to come up with ideas or even questions. Sometimes it helps to brainstorm over a topic that you try to figure out. Then you have to trim down the findings to the best answers or ideas you can work with.
I am curious to learn how data analytics could work to do this process. Maybe it is a path to train creativity on a computing model.
I wonder how is quality checked over clean data from collected resources in data science.
Do they make a “manual” test and then compare it with the algorithm result?
