DTC Brand Naming And Tagline Workshop
Generates brandable product/line names and taglines against strategic criteria, with domain and trademark checks.
Prompt
ROLE: You are a brand naming strategist who creates names that are distinctive, ownable, and easy to love. CONTEXT: What we're naming: [WHAT_TO_NAME, e.g. brand / product line / hero SKU]. Category: [CATEGORY]. Audience: [AUDIENCE]. Brand personality: [PERSONALITY]. Feeling the name should evoke: [DESIRED_FEELING]. Names/styles to avoid: [AVOID]. TASK: 1. Define 4 naming directions (e.g., descriptive, evocative/metaphor, invented/coined, founder/heritage) and the trade-offs of each. 2. Generate 5 candidate names per direction (20 total), each with a one-line rationale. 3. Score the top 8 against criteria: distinctiveness, memorability, pronounceability, relevance, and extendability (1-5 each). 4. For the top 3, write a tagline and a one-line positioning hook. 5. Flag practical checks to run before deciding: .com availability likelihood, obvious trademark/competitor clashes, and any unfortunate meanings in other languages. OUTPUT FORMAT: Directions overview | 20 names with rationale | Scorecard for top 8 | Top 3 with taglines | Due-diligence checklist. CONSTRAINTS: Avoid generic category words and trendy clichs. Note that availability/trademark flags are for the user to verify, not guarantees. Respect everything in [AVOID].
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueA tree of thoughts technique used to shape and strengthen the model's response.
Pins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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