Create unique customer support with ChatGPT
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Create unique and engaging customer support with ChatGPT, a pre-trained language model by OpenAI for generating high-quality and accurate content.
6 Proven ChatGPT Prompts: Writing multilingual customer support responses
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6 Expert ChatGPT Prompts: Generating customer support email responses
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6 Strategic ChatGPT Prompts: Assisting with product returns
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7 Proven ChatGPT Prompts: Offering maintenance tips
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6 Strategic ChatGPT Prompts: Handling chatbot inquiries for returns and refunds
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7 Proven ChatGPT Prompts: Generating training material for customer support
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6 Proven ChatGPT Prompts: Providing account management support
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6 Innovative ChatGPT Prompts: Providing customer support for products
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6 Strategic ChatGPT Prompts: Offering account management support
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6 Strategic ChatGPT Prompts: Responding to lost password emails
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6 Strategic ChatGPT Prompts: Troubleshooting product issues
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7 Strategic ChatGPT Prompts: Building customer trust and loyalty through chat support
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7 Advanced ChatGPT Prompts: Providing instant chat support
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6 Strategic ChatGPT Prompts: Offering account management and security support over the phone
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6 Proven ChatGPT Prompts: Providing instant phone support for urgent issues
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6 Advanced ChatGPT Prompts: Generating automated responses for common issues and inquiries
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6 Advanced ChatGPT Prompts: Troubleshooting technical problems over the phone
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6 Innovative ChatGPT Prompts: Creating FAQs for products
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Learn How ChatGPT Can Help Create a Positive Customer Service Culture
What are the best practices for creating a strong customer service culture?
Set the context surrounding the task in your prompt
This is a conversation between a customer and a friendly, helpful customer support representative. Customer: <input customer question> Customer representative:
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.