7 Reasons Your Prompt Engineering Fails
#1. Too Much Complication
Common mistake:
Goofing up by making the whole prompt complex.
Look at this broad, confusing and complex prompt:
Compose a guide on growing marketing strategies. It should be packed with details and cover a broad spectrum of topics like SEO, social media, content marketing, email campaigns, PPC, and affiliate marketing, all while putting focus on B2B tech startups.
This gonna get the model confused, releasing wordy or even non relevant answers.
To avoid this: Make sure your prompt is simple but also clear and specific! It's about finding that balance between concise and detailed. Like, it's a literal balancing act.
So this much improved prompt is focused and easy to manage:
Give an overview of the most important growth marketing strategies for B2B tech startups but only focus on SEO and content marketing.
#2. Not giving Enough Specification
Common mistake: Not offering enough detail or context.
A prompt lacking attention to detail has no context, like:
Give me some insider tips on copywriting?
Without guidance, the generated AI answer can lose direction becoming totally generic or off topic.
To avoid this: Make sure the prompt has enough of a context to steer the AI in the right direction. This is a biggie when you're dealing with nuanced or complex subject matter.
A well-made prompt will tell you clearly and specifically what you want to do:
Please give me five hands on copywriting tips that can be used to create engaging and heart-catching product descriptions on e-commerce sites.
#3. Misalignment with AI Capabilities
Common mistake: Hopping with eagerness for AI that understands and replies to prompts beyond its training or capacity.
This bad prompt is too much for AI, like:
Predict what would be the most profitable growth marketing channel in the year 2025.
Trigger Warning: This can lead to incorrect or irrelevant answers outside of what the AI can reliably produce.
How to tackle this: Keep yourself well acquainted with the strengths, weakness of the AI model. Avoid prompts that long for real-time data, your personal opinion or knowledge outside the training of the AI.
This improved prompt will stay inside in AI's knowledge range, possibly by offering additional data:
Sum up recent trends in growth marketing channels with the aid of some recent data and info from a pair of articles (that I'd give to you, of course!).
#4. Forgetting about Target Audience and Purpose so the Pitch
Common mistake: not making a prompt that matches up to a specific audience or purpose.
An unsuited prompt doesn't consider the knowledge level of the audience. Case in point:
Explain the concept of market segmentation.
The generated response may not match up with how it's intended to be used thereby losing effectiveness.
Think about: the final user and the purpose of the response. Construct the prompt that aligns with these elements, adjusting the complexity and style as required.
With this tailor-made prompt aimed for beginner audiences the usability of the answer can be ramped up, now that the audience can get it better:
Explain market segmentation in super simple layman's terms for someone who's just starting off with customer research.
#5. Vague and Indeterminate
Common Mistake:
Throwing around big words and vague terms in the prompt.
Now, here's an unclear and hazy prompt:
Draft out a go-to-market strategy for the fitness sector.
The AI's response might not resolve the query or topic accurately as intended.
Clear up this confusion: By using language that is precise and clear cut. Rephrase the prompt if required to get rid of any possible ambiguity.
This prompt keeps things simple and to the point:
Briefly talk about the go-to-market strategy to be used for a new fitness app which targets millennials in NYC!
#6. Ignoring the Importance of the Structure of the Prompt
Common mistake: Ignoring the importance of structuring a prompt properly.
This is how an unstructured, over-broad prompt looks like:
Tell me how to do audience research, also make personas?
Not structuring the prompt right can lead to confusing or disjointed responses.
How you can improve it:
By logically putting together a prompt, especially for tasks that are harder. You can use bullet points, numbering or clear step-by-step instructions where it's fitting.
You can get better results by structuring the prompts:
First provide the step-by-step for conducting audience research. Then follow it up with a detailed guide on how to create customer personas.
Another thing you can try is having an ongoing conversation with the AI which will naturally result in a step by step approach and be a more iterative process overall.
#7. Failing to Repeat
Common mistake: Avoiding refining or repeating the prompt as per the initial responses.
These early prompts such as What are growth strategies in marketing? could be seen as a chance to improve.
This answer will be too broad and unspecific to be of any help, leading people to claim “ChatGPT isn’t working for me” instead of making the most out of this AI assistant.
The most important part here centres around improving the quality of AI's output.
Make use of the initial responses as feedback. Recreate the prompt in different iterations to lead towards the desired output.
The refined prompts, based on initial feedback from AI could look like:
Based on your previous answer's point 3, could you go on to describe three effective growth strategies commonly implemented by digital marketing sector's SaaS companies?
Part to Reflect Back
We hope that these examples which shifted our focus from growth marketing to audience research have shown how it is possible to tackle common prompt engineering mistakes.
Prompt engineering is a tricky business. It's both a science and a discipline. If you learn from the mistakes and keep refining your approach, you will have more effective and accurate interactions with AI models. By avoiding these common pitfalls, you can ensure your prompts, and consequently the AI responses, improve in quality.
Let’s recap:
Over-Complication
Not enough Specification
Misalignment with AI Capabilities
Ignoring Audience and Purpose
Vague and Indeterminate
Neglecting Structure of the Prompt
a. Failing to Repeat
b. Part to Reflect Back
c. Kudos to the contributors.
