Many marketers are missing out on the full potential of AI tools by using vague prompts that generate generic, unhelpful content that fails to stand out in the crowd. This guide explains how “AI prompt engineering” works, including practical techniques to achieve genuinely valuable output from ChatGPT and other AI tools.
Why most AI prompts fail
Marketers have been experimenting with AI tools like ChatGPT for some time now. But many are disappointed and have been left wondering what all the hype is about.
They type “write a blog post about mortgages”, receive 500 words of bland content, and wonder what all the AI fuss is about.
However, the problem isn’t the AI. It’s the prompt.
Prompt engineering is the skill of communicating with AI tools in a way that produces genuinely useful output. It involves understanding how these tools work, and giving them the context they need to be helpful.
Poor prompting affects:
- Content quality and relevance
- Time wasted on unusable drafts
- Brand voice consistency
- Marketing effectiveness
- Team productivity
Imagine a financial planner asking AI to “write content about pensions” and receiving generic information that could apply to anyone, anywhere. That’s not helpful. And it’s a waste of time.
Prompt engineering is about using AI effectively enough to actually save time and improve output quality.
Prompt engineering is more than typing questions
Many assume asking AI a question is enough. It helps, but effective AI prompts require deeper structure. They should include:
- Role definition and context
- Specific task parameters
- Format and length constraints
- Tone and style guidance
- Examples for reference
- Clear success criteria
All of these feed into how AI interprets your request and shapes its response.
A prompt might seem detailed but still fail because:
- Context is too vague
- Examples are missing
- Format isn’t specified
- Brand voice isn’t defined
If your prompt doesn’t give AI enough structure, you’ll get generic output. Every time.
The biggest mistakes marketers make with AI prompts
Some problems are strategic. Others are execution issues. The most common prompt engineering mistakes include:
Vague, undefined requests
“Write something about our services”. This gives AI nothing to work with. Vague prompts generate vague responses. Which services do you want to cover? Who are they for? Why are they helpful?
Asking for too much at once
Requesting an entire marketing strategy or research report in a single prompt overwhelms AI and produces superficial output.
No brand context
AI won’t know your brand voice, positioning, or audience unless you specify it. Unless you want generic output that doesn’t appeal to anyone specifically, go to town on explaining who you are, why you exist, your values, mission and target audience. Provide examples of your tone of voice, and upload any tone of voice guidelines you have prepared.
Not discussing responses
The first AI output should not be considered the final output. Effective prompting is conversational and multi-layered. Take time to ‘train’ your AI tool as you would a new member of staff.
Missing examples
Without examples of what good looks like, AI invents its own interpretation of your requirements. Be specific about what you are expecting.
Look at it like this: good prompt engineering sets AI up for success by providing clear, detailed briefs which save time in the long run.
How to write effective AI prompts
Here are the most important techniques for creating AI prompts that actually work, especially for marketing content:
1. Define the role and context
Tell AI who it needs to be and what expertise to draw on.
Weak prompt:
“Write about pension planning.”
Strong prompt:
“You’re an experienced financial copywriter who specialises in explaining complex pension regulations to non-experts in a friendly, accessible tone.”
This immediately shapes how AI approaches the task. A financial planner creating content about SIPPs gets dramatically different results when they specify the required expertise level and tone upfront.
For a healthcare provider creating patient information, you might say: “You’re a healthcare communications specialist writing for anxious patients who need reassurance alongside medical information.”
2. Specify the exact task
Be precise about what you need. Vague requests get vague responses.
Weak prompt:
“Write about property investment.”
Strong prompt:
“Write a 400-word guide explaining the difference between residential and commercial property investment for first-time investors, focusing on cash flow considerations and tax implications.”
The difference is clear. One is a direction. The other is a proper brief with scope, audience, word count and specific focus areas.
3. Set format and constraints
Specify exactly what format you need and any limitations.
Format examples:
- “Write this as 5 bullet points, each 2-3 sentences long”
- “Structure as an email with a friendly opening, three key points, and a soft call to action”
- “Create a numbered list of steps, each with a brief explanation”
Constraint examples:
- “Maximum 300 words”
- “Avoid jargon or explain any technical terms”
- “Use short paragraphs of no more than three sentences”
- “Don’t use exclamation marks or marketing clichés”
For ChatGPT for marketing tasks, constraints like these prevent AI from adding unnecessary fluff or adopting an overly promotional tone.
4. Provide examples and style references
Show AI what good looks like. Include examples of your best content and ask it to match that style.
Example prompt structure:
“Here’s an example of our brand voice: [paste or attach example content]. Please match this tone and style when writing the following piece about [topic].”
A real estate agent might include a previous successful listing description and ask for similar copy for a new property. AI learns from the example rather than inventing its own interpretation of “compelling property description.”
This is particularly valuable for maintaining brand consistency when multiple team members use AI content creation tools.
5. Use chain-of-thought prompting
Ask AI to “think step-by-step” or tell it to “explain your reasoning” before providing an answer. This produces more thoughtful, nuanced responses.
Example:
“Before suggesting portfolio diversification strategies, first analyse the different risk profiles of investors aged 30, 45, and 60. Then provide tailored recommendations for each.”
This technique forces AI to consider context and nuance rather than jumping to generic answers. It’s especially useful for complex topics where professional credibility matters.
6. Apply negative prompting
Explicitly tell AI what not to do. This prevents common issues before they happen.
Example:
“Don’t use marketing clichés like ‘game-changer’ or ‘cutting-edge’. Don’t make unsubstantiated claims. Always cite sources when quoting any statistics. Don’t use exclamation marks. Don’t write in an overly salesy tone.”
For financial services content, you might say: “Don’t make specific investment recommendations. Don’t guarantee returns. Don’t use overly technical jargon without explanation.”
Negative prompting is particularly effective for maintaining professional tone and avoiding AI’s tendency toward hyperbolic language. It’s especially valuable in regulated industries where citing sources and avoiding making unsubstantiated claims is vital.
Practical prompt templates that work
Here are some examples of proven AI prompts for common marketing tasks, tailored for expert-led businesses:
For thought leadership content
“You’re writing for a respected financial services firm targeting high-net-worth individuals aged 45-65. Write a LinkedIn post (200 words maximum) that explains the recent changes to Capital Gains Tax on second properties. Use a knowledgeable but not condescending tone. Include one practical implication and one question that encourages engagement. Avoid emojis and overly promotional language.”
For client-facing explanations
“You’re a healthcare communications specialist. Explain the difference between MRI and CT scans to a patient who’s been referred for imaging. Use simple language, short paragraphs, and a reassuring tone. Address common concerns about claustrophobia and radiation without being alarming. 300 words maximum.”
For property listings
“Write a property description for a 2-bedroom garden flat in Clapham. Target first-time buyers or young professionals. Highlight period features, outdoor space, and transport links. Use descriptive but not clichéd language. Avoid overused phrases like ‘stunning’ or ‘must be seen’. 200 words.”
For email sequences
“Draft the opening email for a 3-part nurture sequence aimed at property investors who downloaded our guide to buy-to-let mortgages. The email should acknowledge what they downloaded, provide one additional valuable insight about mortgage rates, and preview what’s coming in emails 2 and 3. Friendly, professional tone. 150 words.”
Notice how these include role, audience, tone, constraints and specific guidance about what to avoid. That level of detail is what separates useful output from generic waffle.
Advanced techniques for better results
Once you’ve mastered basic prompt engineering, these advanced techniques take output from good to genuinely impressive:
Create detailed persona briefs
Develop specific persona descriptions and ask AI to tailor content for them.
Example:
“This content is for Sarah, a 52-year-old solicitor in Hampshire who’s concerned about inheritance tax planning for her children. She values detailed information but doesn’t have time for jargon. She’s cautious about financial decisions and wants clear, practical advice.”
The more specific the persona, the more targeted the content becomes.
Build a brand context library
Create a saved prompt containing your brand brief to include at the start of any marketing task.
Include:
- Brand positioning statement
- Tone of voice guidelines
- Key messages
- Typical customer language
- Words and phrases to avoid
This transforms generic AI output into content that actually sounds like your brand.
Refine your prompts
After receiving initial output, use refinement prompts to improve quality:
- “Make this more concise while keeping the key points”
- “Adjust the tone to be more authoritative but still approachable”
- “Add a specific example relevant to the UK property market”
- “Restructure this with the most important information first”
According to research from Stanford and UC Berkeley, well-crafted prompts can improve AI output quality by up to 40% compared to basic requests. That’s not marginal improvement. That’s the difference between usable and unusable content.
Combine multiple techniques
The most effective prompts combine several techniques:
Example combining role, task, format, constraints, and negative prompting:
“You’re an expert financial copywriter. Write a 250-word email explaining what a SIPP is to someone who is self-employed and considering their pension options. Use short paragraphs (max 3 sentences). Structure as: what it is, key benefits, one consideration. Use friendly, clear language. Don’t use financial jargon without immediately explaining it. Don’t make specific investment recommendations. Don’t oversell.”
What prompt engineering can’t fix
Here’s the reality: no amount of clever prompting will turn AI into a substitute for human expertise and judgement.
AI doesn’t understand your clients the way you do. It can’t anticipate unspoken concerns or read between the lines. It hasn’t sat through hundreds of client meetings learning what actually matters to people making major financial, healthcare, or property decisions.
AI content creation is a tool, not a replacement. The best marketing content combines AI’s speed with human insight, experience, and understanding of nuance.
Use prompt engineering to handle:
- Drafting initial outlines
- Rephrasing complex ideas
- Generating variations for testing
- Creating structure from messy notes
- Summarising research
- Brainstorming angles
But always apply human editorial judgement. Always fact-check. Always ensure alignment with your expertise and brand voice. Never publish AI-generated content without thorough review.
The long-term value of AI prompt engineering skills
Prompt engineering isn’t a replacement for marketing skill. It’s a multiplier of the skills you already have.
The marketers winning with AI aren’t the ones with the fanciest prompts. They’re the ones who understand their audience deeply, know their brand inside out, and use AI to execute faster without sacrificing quality.
When you develop strong prompt engineering capabilities, you’re more likely to see:
- Faster content production
- More consistent brand voice
- Better first drafts requiring less editing
- Increased marketing team productivity
- Higher quality output at scale
Prompt engineering isn’t about accommodating new technology. It’s about using it strategically to amplify human expertise.
Ready to use AI more effectively?
AI tools can genuinely enhance marketing productivity when used productively. When your prompts are specific, contextual, and strategic, you’ll see dramatically better output that actually saves time rather than creating more work.
Need support integrating AI tools into your marketing workflows while maintaining quality and brand consistency? Get in touch with Figment and let’s tailor a strategy to get you there.
