Create unique Work with ChatGPT

Soft natural light coming from a nearby window, supplemented with a fill light to highlight the desk area, A cluttered and busy composition featuring an antique desk, an ergonomic chair, and several stacks of papers and books, Low angle perspective that shows the height of the bookshelves and emphasizes the ceiling height, Non-symmetrical composition, with objects arranged in a way that suggests a...

workspace composition lighting

ChatGPT: Leverage the Growth Marketing Framework to Create a Data-Driven, Iterative Marketing Strategy for [Product/Service] Success

Preview

Write a marketing campaign outline using the 'Growth Marketing Framework' to identify and prioritize growth opportunities for our [product/service] and set clear goals and metrics to measure progress. Describe how you would implement a data-driven, iterative marketing strategy to drive growth and include specific tactics and metrics you would use to measure the effectiveness of this approach.

growth marketing framework product/service data-driven iterative marketing tactics metrics effectiveness

Generate an Opinion about the Content of the Input Using the 'Headline' Framework

Preview

Write a marketing campaign outline using the 'Headline' framework to identify the main benefit or value proposition of our [product/service] and craft a headline that clearly communicates that benefit to [ideal customer persona].

headline framework marketing campaign product/service ideal customer persona value proposition

What is “prompt engineering”?

A “prompt” is the input that guides a generative AI model to generate useful outputs. Generative AI tools like ChatGPT, GPT, DALL·E 2, Stable Diffusion, Midjourney, etc. all require prompting as their input.

In a natural language processing (NLP) context, “prompt engineering” is the process of discovering inputs that yield desirable or useful results. As is the story with any processes, better inputs yield better outputs; or commonly said another way “garbage in, garbage out.”

![Source: https://www.youtube.com/watch?v=1NQWJjgi-_k

Designing effective and efficient prompts will increase the likelihood of receiving a response that is both favorable and contextual. With a good prompt, you can spend less time editing content and more time generating it.

Going from beginner → advanced prompt engineer

As companies like PromptBase arise around the idea that the prompt is the “secret sauce” to using generative AI, prompt engineering could easily become the “career of the future.” But, any generative AI user can become an “advanced” prompt engineer. Here’s how

Spend time with the tools

The more time you spend asking ChatGPT questions and receiving responses, the better your idea will be of various prompting approaches and their individual strengths and weaknesses
Use Open AI’s GPT playground to perform interactive trial and error with variations in your prompt, model, temperature and top_p values (uniqueness of answer, i.e. creativity), and more available within the UI itself.

Become a prompt researcher instead of engineer

If you’re already a subject matter expert in something, consider figuring out how to apply your personal skills to generating the best prompts in your field
For example, if you’re an expert in SEO, what questions do you ask yourself when creating SEO strategies? How can you translate this knowledge into better prompts to generate the same level of output with AI?

Become a prompt researcher instead of engineer

The term prompt engineer glosses over the idea that prompt formulation takes hypothesizing, research, result measurement, and repetition. Instead, approach prompting like a research project.
Try as many different variations and formulations of your prompt as possible. One problem can have hundreds of solutions and one solution can have hundreds of approaches. The same can be said of prompting.