Gemini Prompt to Generate Brand Names

Finding the perfect brand name is one of the most strategic steps of any entrepreneurial project. A good name must be memorable, evocative, legally available, and suited to your target market. Gemini, Google's artificial intelligence model, excels at creative name generation thanks to its ability to cross linguistic, semantic, and commercial constraints. By structuring your prompt correctly, you can get dozens of relevant proposals in seconds, where a classic brainstorming session would take hours. Gemini's advantage lies in its fine understanding of context: by providing your industry, brand values, target audience, and technical constraints, it generates names that are not just random but truly aligned with your positioning. Whether you are launching a tech startup, a cosmetics brand, or a consulting firm, this approach allows you to explore creative territories you would never have considered alone. Discover how to formulate the optimal prompt to turn Gemini into your naming creative director.

The prompt

Gemini

You are an expert in naming and brand strategy with 20 years of experience in a branding agency. I am launching a project in the [INDUSTRY] sector targeting [TARGET AUDIENCE]. The core values of my brand are: [VALUE 1], [VALUE 2], [VALUE 3]. The brand tone should be [TONE: e.g., modern, premium, accessible, bold]. Constraints: the name must be between 1 and 3 syllables, easily pronounceable in French (and ideally internationally), and evoke [KEY EMOTION OR CONCEPT]. Generate 15 brand name proposals organized into 3 categories: (1) Invented names/neologisms, (2) Evocative names based on existing words, (3) Compound names or creative acronyms. For each name, provide: the proposed name, its etymological or creative origin, the connotations it conveys, a memorability score out of 10, and a quick check of potential availability (.com and .fr). End with your top 3 with a strategic justification for each.

Personalize this prompt with Léa

Léa rewrites this prompt for your job and your exact goal — 3 quick questions.

Why it works

This prompt works thanks to the assignment of a precise expert role that activates Gemini's specialized branding knowledge. Structuring into categories forces the model to explore diverse creative territories rather than staying in one register. The integrated evaluation criteria (memorability, availability, connotations) turn a simple list of names into an exploitable strategic analysis.

Expected result

You will obtain 15 name proposals organized into three distinct categories, each accompanied by a complete analysis sheet. Gemini will also provide a ranked list of its three best recommendations with strategic justifications linked to your positioning. The result is directly usable for a validation phase (INPI search, domain availability).

Variants by level

FAQ

Can Gemini check if a brand name is already registered?

Gemini cannot access real-time databases from the INPI or EUIPO. It can estimate the likelihood of availability based on its knowledge of existing trademarks, but this estimate has no legal value. After generating your favorite names with Gemini, you must perform a prior art search on official databases (INPI for France, TMview for Europe, USPTO for the United States) and check domain name availability via a registrar. This validation step is mandatory before any filing.

How many names should I ask Gemini for to have good options?

In professional naming, we typically work with a ratio of 50 proposals for 3 to 5 finalists. With Gemini, ask for 15 to 20 names per prompt, then follow up with adjustments 2 to 3 times by refining your criteria. This will give you a pool of 40 to 60 proposals from which you can select your finalists. The advantage of proceeding iteratively is that you can tell Gemini what you like or dislike in the first proposals to guide the next round.

How can I improve the quality of names generated by Gemini?

The key is the precision of the provided context. The more you detail your industry, target, competitors, and especially the desired emotional territory, the more relevant the proposals will be. Use concrete references: cite brands whose style inspires you (even outside your industry), specify the sounds you are looking for, and explicitly state what you do not want. After an initial generation, use Gemini's conversational follow-up to refine: 'I like the sound of X but I want something more premium' or 'Explore the direction of Latin neologisms further.' This iterative approach consistently yields better results than a single prompt.

How to use this prompt

Copy the prompt with the button above.
Paste it into ChatGPT, Claude or your favorite AI assistant.
Replace the bracketed variables with your details, then refine the result.

About Prompt Guide

Prompt Guide is a free library of 4800+ ready-to-use prompts for ChatGPT, Claude and other AIs, with guides to learn prompting and tools to build and optimize your own prompts.

Prompt library Learn prompting Prompt builder Prompt optimizer

Already have a prompt?

Paste it into the Optimizer, AI improves it in 5 seconds: role, context, format. Free, no signup.

Open the Optimizer

More prompts to explore

Gemini Prompt to Synthesize a Meeting

Professional meetings generate a considerable amount of information: decisions made, actions to be taken, blocking points, and ideas explored. Yet, writing a faithful and usable minutes remains a time-consuming task that many put off or rush through. Gemini, Google's artificial intelligence model, excels at synthesizing long, unstructured content. By providing it with a transcript, raw notes, or even an audio recording via Gemini Advanced, you get a structured summary in seconds that captures the essentials without losing the nuances. The challenge is not simply to summarize, but to produce an actionable document: who must do what, by when, and which decisions have been validated. A well-constructed prompt allows Gemini to distinguish exploratory discussions from firm commitments, identify key participants on each topic, and prioritize information. Whether you are a project manager, executive assistant, or agile team member, mastering this type of prompt will save you between 20 and 45 minutes per meeting while improving decision traceability within your organization.

Generate a Database Schema with Gemini

Designing a database schema is a fundamental step in any software project. A well-thought-out schema ensures data consistency, optimizes query performance, and facilitates long-term maintenance.

GitHub Copilot Prompt for Analyzing an Annual Report

GitHub Copilot, initially designed as a development assistant, also proves formidable for analyzing complex documents such as annual reports.

GitHub Copilot Prompt for Analyzing Customer Reviews

GitHub Copilot, GitHub's AI assistant integrated into code editors, is not limited to code generation. It also excels at analyzing textual data like customer reviews. By leveraging its natural language processing capabilities directly in your development environment, you can automate sentiment extraction, thematic categorization, and trend identification from thousands of user feedback items. Whether you're working on a Python script, a Jupyter notebook, or a Node.js application, Copilot helps you structure your analysis pipelines without leaving your IDE. This approach is particularly valuable for product and data teams who want to turn raw reviews into actionable insights: detecting recurring pain points, evaluating satisfaction by feature, and tracking sentiment evolution over time. The prompt we offer here is designed to guide Copilot in creating a comprehensive analysis system, from data parsing to generating summary reports usable by business teams.

GitHub Copilot Prompt for Analyzing Market Trends

GitHub Copilot, initially designed as a development assistant, proves to be a powerful tool for market trend analysis when used with the right prompts. By leveraging its code generation and data analysis capabilities, you can automate data collection, processing, and visualization directly in your development environment.

GitHub Copilot Prompt for Analyzing User Feedback

Analyzing user feedback is crucial for improving a product, service, or customer experience. However, manually processing hundreds or thousands of comments—whether from reviews, support tickets, NPS forms, or social media—is a significant undertaking. GitHub Copilot, with its natural language understanding capabilities built directly into your code editor, can automate this analysis with remarkable accuracy. By crafting appropriate prompts, you can ask Copilot to categorize sentiments, extract recurring themes, identify priority friction points, and generate actionable summaries for your product teams. Whether you're working with CSV files, JSON exports, or raw data copied from a support tool, Copilot turns your IDE into a full-fledged qualitative analysis platform. This approach is especially useful for developers and product managers who want to integrate feedback analysis directly into their technical workflow, without relying on expensive third-party tools or advanced data science skills.

Go further

How to prompt Gemini

The complete guide: techniques, examples and best practices.

Free prompt library

4800+ prompts sorted by category, one-click copy.

Get new prompts every week

Join our newsletter.