When to use this prompt
When you’re drafting new blog posts and need SEO-optimized, keyword-rich slugs that align with search intent.
When you’re refreshing old content to improve rankings or CTR by tightening up URLs.
When performing SERP or competitor analysis to benchmark and improve slug structures for similar topics.
When building content briefs or SEO templates for writers to standardize slug conventions across your site.
The prompt
Act as a technical SEO specialist. Create keyword-rich, concise slugs for a blog post with the title [TITLE] and primary keyword [PRIMARY_KEYWORD]. The slug must be ≤ 60 characters, use hyphens between words, exclude filler terms (like ‘the,’ ‘and,’ ‘in’), and reflect the search intent [INTENT: how-to | what-is | best]. Generate [N] options, each slightly different in emphasis (outcome-focused, audience-specific, year-tagged, comparison-led). Add a character count for each. Self-check: if the slug is either too long or too generic, automatically revise it to balance clarity and brevity.
Variables to replace:
Real-life example of how to use this prompt
To start, let's assume I'm a content lead at Hubspot. The prompt in the context of Hubspot would look like:
As you can see, I added the main keyword "Amazon listing optimization" and specified the intent as well.
Example output from ChatGPT for this prompt
And here's the output:
amazon-listing-optimization-for-higher-sales
→ Outcome-focused (52 characters)amazon-listing-optimization-guide-for-sellers
→ Audience-specific (49 characters)amazon-listing-optimization-tips-2025
→ Year-tagged / freshness-focused (43 characters)how-to-master-amazon-listing-optimization
→ How-to intent + authority-focused (44 characters)amazon-listing-optimization-vs-product-tuning
→ Comparison-led / keyword-variant rich (49 characters)
Or to be more specific:
Pro tips
Replace all variables clearly — especially [INTENT] — so ChatGPT tailors slugs precisely to your content goal.
After generating results, ask ChatGPT to justify or score each slug for SEO strength or intent alignment for added insight.
Test variations with different intents (“how-to,” “what-is,” “best”) to see how framing changes search relevance.
Use ChatGPT’s self-check step — prompt it again with “revise any too-generic options for uniqueness” to fine-tune outputs.
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