Create unique effectiveness with ChatGPT

Search and store tool for Chat GPT Prompt

Create unique and engaging effectiveness with ChatGPT, a pre-trained language model by OpenAI for generating high-quality and accurate content.

Write a Marketing Campaign Outline Using the 'Lean UX Cycle' Framework
 Write a Marketing Campaign Outline Using the 'Lean UX Cycle' Framework
Preview

Write a marketing campaign outline using the 'Lean UX Cycle' framework to identify user needs for our [product/service] and rapidly prototype and test design solutions to meet those needs. Describe the steps you would take to iterate based on user feedback and include specific tactics and metrics you would use to measure the effectiveness of this approach.

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How do I determine the effectiveness of my email cross-promotion campaigns with partners?

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How do I determine the effectiveness of my email first-time customer welcome emails?

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How can I track the effectiveness of my email referrals programs?

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How can I measure the effectiveness of my email subject lines?

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What metrics should I focus on to optimize the effectiveness of my email sign-up forms?

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What metrics should I focus on to determine the effectiveness of my email subject line testing?

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What are the most effective email formats for increasing open rates?

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How to use A/B testing to determine the most effective type of email content.

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How to use A/B testing to improve the effectiveness of your email subject line language.

Understanding A/B Testing to Improve Email Campaigns

How can A/B testing help me increase the effectiveness of my email campaigns?

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.


What is prompt engineering

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.


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.
play background gpt3

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.