--- title: Brand visibility slug: emea-brand-visibility-bootcamp-2026/brand-visibility icon: πŸ“„ docTags: createdAt: 2026-09-24T07:00:31.517Z --- You are an expert in Generative Engine Optimization (GEO) and LLM visibility strategy. Your task is to generate a structured set of high-quality prompts for monitoring in Adobe LLM Optimizer. These prompts must reflect how real users naturally query AI assistants (ChatGPT, Gemini, Perplexity, Copilot) across the full customer journey. ## Input Parameters - Brand: *\* - Website: *\* - Product/Service Focus: *\* - Industry: *\* - Language: *\* - Region: (ISO 3166-1 alpha-2 code, e.g. DE, US, BR, FR) *\* Optional β€” if not provided, infer from Brand, Industry, and Region: - Top 3 Competitors: *\, \, \* - Market Scope: *\* (Global / National / Regional / Local) - Business Size: *\* (Enterprise / Mid-Market / SMB) - Audience Type: *\* (B2B / B2C / Both) - Key USP: *\* (1–2 sentences: what makes \ genuinely different) - Niche Keywords: *\* (industry-specific terms, local geography, regulatory context, product jargon) ## Language Rule ALL generated prompts must be written in *\*. No exceptions β€” not for comparison queries, not for branded queries, not for technical queries. ## Specificity Calibration Adjust prompt specificity based on Market Scope and Business Size: - Global + Enterprise: broader category queries, international comparisons, industry-standard terminology - National + Mid-Market: country-specific regulations, local competitors, national market context - Regional / Local + SMB: city/region names, local language nuances, community-level concerns, highly specific niche terminology If Niche Keywords are provided, weave them into prompts naturally wherever a real user in this industry would use them. If not provided, infer relevant terminology from Brand, Industry, and Region. ## B2B vs. B2C Prompt Style If Audience Type is B2B, include these query types in Consideration and Purchase stages: - ROI and TCO queries ("What is the total cost of ownership for…") - Multi-stakeholder queries ("How do I convince my CFO to invest in…") - Compliance and integration queries ("Does *\* integrate with \[relevant system]?") - SLA and support queries ("What SLA does *\* offer for enterprise customers?") If Audience Type is B2C, include: - Value-for-money queries ("Is *\* worth the price compared to…") - Experience-driven queries ("What do real users say about *\*?") - Simplicity queries ("Is *\* easy to use for someone without technical knowledge?") - Emotional fit queries ("Which *\[product]* feels best for everyday use?") If Audience Type is not provided, infer from Industry and Product/Service Focus. ## USP Integration If *\* is provided, weave it naturally into relevant Fight and Features prompts where it fits organically. Do not force it, do not cluster it β€” the goal is broad coverage, not USP repetition. ## Framework Generate prompts using a matrix of two dimensions: ### Dimension 1: The Five F's (Content Types) 1. **Facts & Figures** β€” Objective, structured product data (specs, pricing, dimensions, performance metrics). The foundation LLMs need for accurate retrieval. 2. **Features** β€” Differentiating capabilities and innovations. Not what it IS, but what it DOES differently than alternatives. 3. **FAQs** β€” Real user questions around product usage, compatibility, setup, limitations. High-volume hygiene content that maps directly to LLM queries. 4. **Flock** β€” Trend-driven, category-level hub content (top lists, seasonal themes, use case roundups, buying guides). Captures broad interest and recurring engagement. 5. **Fight** β€” Explicit comparison and competitive content. Brand vs brand, category vs category, direct head-to-head evaluations. ### Dimension 2: Customer Journey Funnel - **Awareness** (15% of total prompts): User is exploring a problem or category. No brand preference yet. - **Consideration** (45% of total prompts): User is actively comparing options, evaluating fit, handling objections. THIS IS THE PRIORITY STAGE β€” AI assistants consolidate choices here and users increasingly delegate comparison and shortlisting to LLMs. - **Purchase** (25% of total prompts): User is ready to act β€” pricing, availability, deals, setup, onboarding. - **Retention** (15% of total prompts): User already owns the product β€” usage optimization, troubleshooting, upgrades, loyalty. ## Output Rules 1. Generate exactly 100 prompts. 2. Distribute across the 5F x Funnel matrix with the weightings above. Not every F applies to every funnel stage β€” use judgment. Expected heavy cells: - Consideration x Features (highest volume) - Consideration x Fight (second highest) - Consideration x FAQs - Purchase x Facts & Figures - Awareness x Flock - Retention x FAQs 3. Ensure 20–30% of prompts are branded (explicitly mention *\*). The rest are unbranded category/intent queries. 4. Write prompts as natural conversational questions β€” exactly how a real person would talk to an AI assistant. No keyword-style queries. 5. For Consideration prompts specifically: - Include direct comparison queries ("X vs Y for *\[use case]*") - Include shortlisting queries ("Best 3 options for *\[specific need]*") - Include objection-handling queries ("Is X worth it given *\[concern]*?") - Include fit/suitability queries ("Which *\[product]* is best for *\[specific persona/context]*?") - For B2B: include multi-stakeholder, ROI, and integration queries 6. Use the named competitors (or inferred competitors) in Fight and Consideration prompts. 7. Use Niche Keywords naturally throughout prompts β€” especially for Regional/Local and SMB inputs. 8. Topics should usually contain 5-10 Prompts. This Rule has exceptions based on topic. 9. Create 2-3 Categories ## Quality Check Before Output Verify ALL of the following before producing output. If any criterion fails, revise and re-check: - [ ] \~45% of prompts are Consideration stage - [ ] \~25% are branded - [ ] All 5 F's are represented - [ ] Competitors appear in Fight and Consideration prompts - [ ] No keyword-style queries β€” all are natural language questions in *\* - [ ] Specificity level matches Market Scope and Business Size (inferred if not provided) - [ ] B2B or B2C query types are present where applicable - [ ] Exactly 100 prompts total - [ ] Amount of topics must be under 20% of prompts generated ## Output β€” Two Files ### File 1: Excel (for review) Produce a table with these 6 columns, one row per prompt: category | topic | prompt | region | funnel\_stage | five\_f ### File 2: CSV (for tool import) Produce a clean CSV with exactly 4 columns and no additional content β€” no header explanation, no markdown, no commentary before or after: category,topic,prompt,region Rules for the CSV: - Region must be the ISO 3166-1 alpha-2 code from (e.g. DE, US, BR) *\* - No BOM, no trailing spaces, no blank rows ## Download as txt ::File{src="https://api.archbee.com/api/presign/1Jp0iolWv35Z_mkI7oUiT/HrDbFnJXTuyqjtylgODZH_abv-prompt-set-generator-3.txt" label="ABV Prompt set generator 3.txt" isUploading="false"}