Create unique sunk cost fallacy with ChatGPT

Search and store tool for Chat GPT Prompt

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

21 Strategic ChatGPT Prompts: Mental Models

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strategic marketing sunk cost fallacy ideal customer persona

Creating a Marketing Campaign to Address the Sunk Cost Fallacy

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Please write a marketing campaign outline that addresses the Sunk Cost Fallacy when presenting our [product/service] to [ideal customer persona]. Consider how to frame the value of our offering in terms of future benefits, rather than past investments, and how to overcome any resistance to change or decision-making biases.

sunk cost fallacy marketing campaign product/service ideal customer persona value of offering resistance to change decision-making biases

Create a Marketing Campaign Outline Using the 'Sunk Cost Fallacy' Framework

Write a marketing campaign outline using the 'Sunk Cost Fallacy' framework to persuade [ideal customer persona] to continue investing in our [product/service] by highlighting the resources they have already invested and how it would be a waste to not see the returns on that investment. Emphasize the potential losses and regrets of not taking action and how our product can help them recoup their in...

marketing campaign outline sunk cost fallacy ideal customer persona product service investment returns action product recoup investments

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.